librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-09-07 18:30:29	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 544 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 55 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-09-07 18:30:28	card stringlengths 11 1.01M
bigmorning/whisper_charsplit_new_round2__0040	bigmorning	2023-08-13T19:34:23Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T19:34:15Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0040 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0040 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0002 - Train Accuracy: 0.0795 - Train Wermet: 7.9500 - Validation Loss: 0.5660 - Validation Accuracy: 0.0769 - Validation Wermet: 7.0891 - Epoch: 39 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| \| 0.0019 \| 0.0795 \| 8.6037 \| 0.5715 \| 0.0767 \| 7.6157 \| 31 \| \| 0.0009 \| 0.0795 \| 8.4768 \| 0.5611 \| 0.0769 \| 7.6392 \| 32 \| \| 0.0005 \| 0.0795 \| 8.2728 \| 0.5669 \| 0.0768 \| 7.1451 \| 33 \| \| 0.0010 \| 0.0795 \| 8.1006 \| 0.5918 \| 0.0766 \| 7.4447 \| 34 \| \| 0.0036 \| 0.0795 \| 8.9171 \| 0.5687 \| 0.0767 \| 7.6962 \| 35 \| \| 0.0018 \| 0.0795 \| 8.4062 \| 0.5713 \| 0.0768 \| 7.2127 \| 36 \| \| 0.0012 \| 0.0795 \| 8.3370 \| 0.5683 \| 0.0768 \| 7.1040 \| 37 \| \| 0.0005 \| 0.0795 \| 7.9931 \| 0.5658 \| 0.0769 \| 6.8043 \| 38 \| \| 0.0002 \| 0.0795 \| 7.9500 \| 0.5660 \| 0.0769 \| 7.0891 \| 39 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_prefix_tuning_500_10_3000_8_e-1_s108_v4_l4_v100	KingKazma	2023-08-13T19:31:02Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T18:33:45Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e4_s108_v4_l4_v100	KingKazma	2023-08-13T19:29:03Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T19:29:02Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0037	bigmorning	2023-08-13T19:21:21Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T19:21:12Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0037 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0037 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0018 - Train Accuracy: 0.0795 - Train Wermet: 8.4062 - Validation Loss: 0.5713 - Validation Accuracy: 0.0768 - Validation Wermet: 7.2127 - Epoch: 36 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| \| 0.0019 \| 0.0795 \| 8.6037 \| 0.5715 \| 0.0767 \| 7.6157 \| 31 \| \| 0.0009 \| 0.0795 \| 8.4768 \| 0.5611 \| 0.0769 \| 7.6392 \| 32 \| \| 0.0005 \| 0.0795 \| 8.2728 \| 0.5669 \| 0.0768 \| 7.1451 \| 33 \| \| 0.0010 \| 0.0795 \| 8.1006 \| 0.5918 \| 0.0766 \| 7.4447 \| 34 \| \| 0.0036 \| 0.0795 \| 8.9171 \| 0.5687 \| 0.0767 \| 7.6962 \| 35 \| \| 0.0018 \| 0.0795 \| 8.4062 \| 0.5713 \| 0.0768 \| 7.2127 \| 36 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e3_s108_v4_l4_v100	KingKazma	2023-08-13T19:20:14Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T19:20:13Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_prefix_tuning_500_10_3000_8_e5_s108_v4_l4_v100	KingKazma	2023-08-13T19:20:07Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T19:20:06Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0036	bigmorning	2023-08-13T19:16:56Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T19:16:50Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0036 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0036 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0036 - Train Accuracy: 0.0795 - Train Wermet: 8.9171 - Validation Loss: 0.5687 - Validation Accuracy: 0.0767 - Validation Wermet: 7.6962 - Epoch: 35 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| \| 0.0019 \| 0.0795 \| 8.6037 \| 0.5715 \| 0.0767 \| 7.6157 \| 31 \| \| 0.0009 \| 0.0795 \| 8.4768 \| 0.5611 \| 0.0769 \| 7.6392 \| 32 \| \| 0.0005 \| 0.0795 \| 8.2728 \| 0.5669 \| 0.0768 \| 7.1451 \| 33 \| \| 0.0010 \| 0.0795 \| 8.1006 \| 0.5918 \| 0.0766 \| 7.4447 \| 34 \| \| 0.0036 \| 0.0795 \| 8.9171 \| 0.5687 \| 0.0767 \| 7.6962 \| 35 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_round2__0035	bigmorning	2023-08-13T19:12:33Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T19:12:25Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0035 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0035 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0010 - Train Accuracy: 0.0795 - Train Wermet: 8.1006 - Validation Loss: 0.5918 - Validation Accuracy: 0.0766 - Validation Wermet: 7.4447 - Epoch: 34 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| \| 0.0019 \| 0.0795 \| 8.6037 \| 0.5715 \| 0.0767 \| 7.6157 \| 31 \| \| 0.0009 \| 0.0795 \| 8.4768 \| 0.5611 \| 0.0769 \| 7.6392 \| 32 \| \| 0.0005 \| 0.0795 \| 8.2728 \| 0.5669 \| 0.0768 \| 7.1451 \| 33 \| \| 0.0010 \| 0.0795 \| 8.1006 \| 0.5918 \| 0.0766 \| 7.4447 \| 34 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
TheRains/yt-special-batch12-lr4-augment-small	TheRains	2023-08-13T19:08:42Z	114	0	transformers	[ "transformers", "pytorch", "tensorboard", "whisper", "automatic-speech-recognition", "whisper-event", "generated_from_trainer", "dataset:yt", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:31:02Z	--- license: apache-2.0 base_model: openai/whisper-small tags: - whisper-event - generated_from_trainer datasets: - yt metrics: - wer model-index: - name: Whisper Small Indonesian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: yt id type: yt metrics: - name: Wer type: wer value: 38.89501329356072 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Whisper Small Indonesian This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the yt id dataset. It achieves the following results on the evaluation set: - Loss: 0.7352 - Wer: 38.8950 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 12 - eval_batch_size: 6 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 1.296 \| 0.13 \| 1000 \| 1.3286 \| 110.0123 \| \| 1.1522 \| 0.26 \| 2000 \| 1.0917 \| 81.6354 \| \| 1.0175 \| 0.39 \| 3000 \| 0.9399 \| 60.1258 \| \| 0.7844 \| 0.52 \| 4000 \| 0.8174 \| 43.4862 \| \| 0.5919 \| 0.64 \| 5000 \| 0.7352 \| 38.8950 \| ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3
Lyviaa/Tokyoo	Lyviaa	2023-08-13T19:03:38Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2023-08-13T19:02:57Z	--- license: creativeml-openrail-m ---
bigmorning/whisper_charsplit_new_round2__0032	bigmorning	2023-08-13T18:59:27Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:59:19Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0032 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0032 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 8.6037 - Validation Loss: 0.5715 - Validation Accuracy: 0.0767 - Validation Wermet: 7.6157 - Epoch: 31 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| \| 0.0019 \| 0.0795 \| 8.6037 \| 0.5715 \| 0.0767 \| 7.6157 \| 31 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_round2__0031	bigmorning	2023-08-13T18:55:01Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:54:54Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0031 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0031 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0022 - Train Accuracy: 0.0795 - Train Wermet: 8.2353 - Validation Loss: 0.5789 - Validation Accuracy: 0.0767 - Validation Wermet: 7.4442 - Epoch: 30 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| \| 0.0007 \| 0.0795 \| 8.5183 \| 0.5688 \| 0.0768 \| 7.4310 \| 28 \| \| 0.0014 \| 0.0795 \| 8.6604 \| 0.5750 \| 0.0767 \| 8.0751 \| 29 \| \| 0.0022 \| 0.0795 \| 8.2353 \| 0.5789 \| 0.0767 \| 7.4442 \| 30 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prefix_tuning_500_10_3000_8_e1_s108_v4_l4_v100	KingKazma	2023-08-13T18:52:26Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T18:13:23Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
mani05/dqn-SpaceInvadersNoFrameskip-v4	mani05	2023-08-13T18:48:49Z	7	0	stable-baselines3	[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2023-08-13T18:48:14Z	--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 metrics: - type: mean_reward value: 649.00 +/- 125.61 name: mean_reward verified: false --- # DQN Agent playing SpaceInvadersNoFrameskip-v4 This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga mani05 -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga mani05 -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga mani05 ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 1000000.0), ('optimize_memory_usage', False), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ``` # Environment Arguments ```python {'render_mode': 'rgb_array'} ```
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e-1_s108_v4_l4_v100	KingKazma	2023-08-13T18:44:54Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:37:23Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
fathyshalab/mdcsi-wasser-strom-gas-setfit	fathyshalab	2023-08-13T18:43:28Z	5	0	sentence-transformers	[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]	text-classification	2023-08-13T16:58:18Z	--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpj64pfrsp\fathyshalab\mdcsi-wasser-strom-gas-setfit This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage To use this model for inference, first install the SetFit library: ```bash python -m pip install setfit ``` You can then run inference as follows: ```python from setfit import SetFitModel # Download from Hub and run inference model = SetFitModel.from_pretrained("C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpj64pfrsp\fathyshalab\mdcsi-wasser-strom-gas-setfit") # Run inference preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"]) ``` ## BibTeX entry and citation info ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```
KingKazma/xsum_gpt2_prompt_tuning_500_10_3000_8_e0_s108_v4_l5_v50	KingKazma	2023-08-13T18:41:53Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:43:19Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0028	bigmorning	2023-08-13T18:41:43Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:41:37Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0028 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0028 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0009 - Train Accuracy: 0.0795 - Train Wermet: 8.3074 - Validation Loss: 0.5641 - Validation Accuracy: 0.0768 - Validation Wermet: 7.1747 - Epoch: 27 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| \| 0.0009 \| 0.0795 \| 8.3074 \| 0.5641 \| 0.0768 \| 7.1747 \| 27 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
jstoone/whisper-tiny-en	jstoone	2023-08-13T18:39:23Z	85	0	transformers	[ "transformers", "pytorch", "whisper", "automatic-speech-recognition", "generated_from_trainer", "dataset:PolyAI/minds14", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T13:56:01Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - PolyAI/minds14 metrics: - wer model-index: - name: whisper-tiny-en results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: PolyAI/minds14 type: PolyAI/minds14 config: en-US split: train args: en-US metrics: - name: Wer type: wer value: 0.35723514211886304 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # whisper-tiny-en This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set: - Loss: 0.9035 - Wer Ortho: 0.354643 - Wer: 0.357235 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 4000 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer Ortho \| Wer \| \|:-------------:\|:------:\|:----:\|:---------------:\|:---------:\|:-------:\| \| 0.0005 \| 35.71 \| 500 \| 0.7515 \| 36.1373 \| 36.4341 \| \| 0.0002 \| 71.43 \| 1000 \| 0.8095 \| 36.4065 \| 36.5633 \| \| 0.0001 \| 107.14 \| 1500 \| 0.8421 \| 36.4738 \| 36.6925 \| \| 0.0001 \| 142.86 \| 2000 \| 0.8636 \| 35.4643 \| 35.5943 \| \| 0.0001 \| 178.57 \| 2500 \| 0.8822 \| 35.6662 \| 35.7235 \| \| 0.0 \| 214.29 \| 3000 \| 0.8931 \| 35.4643 \| 35.7235 \| \| 0.0 \| 250.0 \| 3500 \| 0.9013 \| 35.4643 \| 35.7235 \| \| 0.0 \| 285.71 \| 4000 \| 0.9035 \| 35.4643 \| 35.7235 \| ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
KenmaKIN101/LenKagamineV4_250epochs	KenmaKIN101	2023-08-13T18:38:53Z	0	0	null	[ "license:openrail", "region:us" ]	null	2023-08-13T18:32:40Z	--- license: openrail --- This model is for fair use only. Also, it may sound a bit bad because this was my first model (because I discarded the Miku model).
bigmorning/whisper_charsplit_new_round2__0027	bigmorning	2023-08-13T18:37:27Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:37:20Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0027 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0027 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.4237 - Validation Loss: 0.5710 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4035 - Epoch: 26 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| \| 0.0012 \| 0.0795 \| 7.9451 \| 0.5615 \| 0.0768 \| 7.0907 \| 24 \| \| 0.0025 \| 0.0795 \| 8.1065 \| 0.5619 \| 0.0768 \| 7.7020 \| 25 \| \| 0.0011 \| 0.0795 \| 8.4237 \| 0.5710 \| 0.0768 \| 7.4035 \| 26 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_prompt_tuning_500_10_3000_8_e-1_s108_v4_l5_v50	KingKazma	2023-08-13T18:34:32Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:35:50Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KemalHal/whisper-base-bosnian-google	KemalHal	2023-08-13T18:29:56Z	78	0	transformers	[ "transformers", "pytorch", "whisper", "automatic-speech-recognition", "bs", "dataset:google/fleurs", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-11T15:15:09Z	--- datasets: - google/fleurs language: - bs metrics: - wer pipeline_tag: automatic-speech-recognition --- Ovaj model je Fine-Tuned verzija Whisper AI base modela na Bosanskom jeziku. Dataset koristen je google/fleurs bs_ba.
dn118/epicnegative	dn118	2023-08-13T18:29:16Z	0	0	null	[ "region:us" ]	null	2023-08-13T18:25:53Z	all credits go to epinikion https://civitai.com/user/epinikion reuploaded from civit.ai, source: https://civitai.com/models/89484?modelVersionId=95263
SaudxInu/Reinforce-CartPole-v1	SaudxInu	2023-08-13T18:28:55Z	0	0	null	[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]	reinforcement-learning	2023-08-13T18:05:19Z	--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-CartPole-v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 500.00 +/- 0.00 name: mean_reward verified: false --- # Reinforce Agent playing CartPole-v1 This is a trained model of a Reinforce agent playing CartPole-v1 . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
josephamess/llama-2-7b-ExtraData-v2	josephamess	2023-08-13T18:24:51Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:36:15Z	--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0024	bigmorning	2023-08-13T18:24:25Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:24:17Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0024 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0024 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0008 - Train Accuracy: 0.0795 - Train Wermet: 8.3246 - Validation Loss: 0.5620 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4475 - Epoch: 23 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| \| 0.0008 \| 0.0795 \| 8.3246 \| 0.5620 \| 0.0768 \| 7.4475 \| 23 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
charliezjw/t2	charliezjw	2023-08-13T18:20:49Z	0	1	diffusers	[ "diffusers", "tensorboard", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "lora", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0", "license:openrail++", "region:us" ]	text-to-image	2023-08-13T17:48:17Z	--- license: openrail++ base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: a photo of sks dog tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - lora inference: true --- # LoRA DreamBooth - charliezjw/t2 These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. ![img_0](./image_0.png) ![img_1](./image_1.png) ![img_2](./image_2.png) ![img_3](./image_3.png) LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
bigmorning/whisper_charsplit_new_round2__0023	bigmorning	2023-08-13T18:20:01Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:19:52Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0023 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0023 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0007 - Train Accuracy: 0.0795 - Train Wermet: 8.6456 - Validation Loss: 0.5543 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4625 - Epoch: 22 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| \| 0.0020 \| 0.0795 \| 8.6599 \| 0.5612 \| 0.0767 \| 7.7369 \| 21 \| \| 0.0007 \| 0.0795 \| 8.6456 \| 0.5543 \| 0.0768 \| 7.4625 \| 22 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v100	KingKazma	2023-08-13T18:19:07Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T18:19:06Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
RAVIKUMAR/ddpm-butterflies-128	RAVIKUMAR	2023-08-13T18:16:08Z	5	0	diffusers	[ "diffusers", "tensorboard", "en", "dataset:huggan/smithsonian_butterflies_subset", "license:apache-2.0", "diffusers:DDPMPipeline", "region:us" ]	null	2023-08-13T18:09:17Z	--- language: en license: apache-2.0 library_name: diffusers tags: [] datasets: huggan/smithsonian_butterflies_subset metrics: [] --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # ddpm-butterflies-128 ## Model description This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library on the `huggan/smithsonian_butterflies_subset` dataset. ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training data [TODO: describe the data used to train the model] ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 16 - eval_batch_size: 16 - gradient_accumulation_steps: 1 - optimizer: AdamW with betas=(None, None), weight_decay=None and epsilon=None - lr_scheduler: None - lr_warmup_steps: 500 - ema_inv_gamma: None - ema_inv_gamma: None - ema_inv_gamma: None - mixed_precision: fp16 ### Training results 📈 [TensorBoard logs](https://huggingface.co/HuggingFace7/ddpm-butterflies-128/tensorboard?#scalars) license: mit ---
bigmorning/whisper_charsplit_new_round2__0021	bigmorning	2023-08-13T18:11:16Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:11:08Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0021 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0021 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0058 - Train Accuracy: 0.0794 - Train Wermet: 8.8460 - Validation Loss: 0.5706 - Validation Accuracy: 0.0766 - Validation Wermet: 7.4342 - Epoch: 20 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| \| 0.0058 \| 0.0794 \| 8.8460 \| 0.5706 \| 0.0766 \| 7.4342 \| 20 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v100	KingKazma	2023-08-13T18:10:32Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T18:10:31Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0020	bigmorning	2023-08-13T18:06:52Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T18:06:44Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0020 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0020 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0014 - Train Accuracy: 0.0795 - Train Wermet: 8.7153 - Validation Loss: 0.5804 - Validation Accuracy: 0.0765 - Validation Wermet: 7.8654 - Epoch: 19 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| \| 0.0004 \| 0.0795 \| 9.1734 \| 0.5607 \| 0.0768 \| 8.0252 \| 17 \| \| 0.0003 \| 0.0795 \| 9.0084 \| 0.5571 \| 0.0769 \| 8.1563 \| 18 \| \| 0.0014 \| 0.0795 \| 8.7153 \| 0.5804 \| 0.0765 \| 7.8654 \| 19 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v100	KingKazma	2023-08-13T18:01:56Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T18:01:55Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0017	bigmorning	2023-08-13T17:53:35Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:53:25Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0017 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0017 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.0553 - Validation Loss: 0.5620 - Validation Accuracy: 0.0768 - Validation Wermet: 8.5020 - Epoch: 16 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| \| 0.0012 \| 0.0795 \| 8.8259 \| 0.5563 \| 0.0768 \| 8.2647 \| 15 \| \| 0.0005 \| 0.0795 \| 9.0553 \| 0.5620 \| 0.0768 \| 8.5020 \| 16 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e5_s55555_v4_l4_v100	KingKazma	2023-08-13T17:53:21Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:53:20Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
YassineBenlaria/tamasheq-3e-5	YassineBenlaria	2023-08-13T17:52:52Z	7	0	transformers	[ "transformers", "pytorch", "tensorboard", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "base_model:jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "base_model:finetune:jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-12T10:54:16Z	--- license: apache-2.0 base_model: jonatasgrosman/wav2vec2-large-xlsr-53-arabic tags: - generated_from_trainer metrics: - wer model-index: - name: tamasheq-3e-5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # tamasheq-3e-5 This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-arabic](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-arabic) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6463 - Wer: 0.7256 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\| \| 16.1726 \| 5.8 \| 200 \| 3.5775 \| 1.0 \| \| 3.2056 \| 11.59 \| 400 \| 3.0132 \| 1.0 \| \| 2.3808 \| 17.39 \| 600 \| 1.0264 \| 0.8069 \| \| 0.6535 \| 23.19 \| 800 \| 0.6919 \| 0.7388 \| \| 0.4426 \| 28.99 \| 1000 \| 0.6463 \| 0.7256 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
Icebear-AI/Llama-2-13b-chat-arabic-lora	Icebear-AI	2023-08-13T17:52:46Z	0	7	null	[ "en", "ar", "dataset:Yasbok/Alpaca_arabic_instruct", "license:apache-2.0", "region:us" ]	null	2023-08-13T17:49:32Z	--- license: apache-2.0 datasets: - Yasbok/Alpaca_arabic_instruct language: - en - ar --- This model is an LoRA adapter file from finetuned Llama-2-13b-chat-hf model. This is an experimental model. This model is presented by IceBear-AI. To run it, you need to: - Agree with Meta's agreements to download the Llama-2-13b-chat-hf model from here: https://huggingface.co/meta-llama/Llama-2-13b-chat-hf - Clone this repository - Clone the Alpaca-LoRA repository from here: https://github.com/tloen/alpaca-lora - Use this command to run it: -python generate.py \ --load_8bit \ --base_model 'PATH_TO_YOUR_LOCAL_LLAMA_2_7B_CHAT_HF' \ --lora_weights 'PATH_TO_YOUR_LOCAL_FILE_OF_THIS_MODEL' You must agree with Meta/Llama-2's agreements to use this model. If you would like to contact us, please don't hesitate to email to icebearai@163.com.
bigmorning/whisper_charsplit_new_round2__0015	bigmorning	2023-08-13T17:44:49Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:44:29Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0015 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0015 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0038 - Train Accuracy: 0.0795 - Train Wermet: 8.7270 - Validation Loss: 0.5605 - Validation Accuracy: 0.0767 - Validation Wermet: 7.7098 - Epoch: 14 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| \| 0.0038 \| 0.0795 \| 8.7270 \| 0.5605 \| 0.0767 \| 7.7098 \| 14 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e9_s108_v4_l4_v100	KingKazma	2023-08-13T17:42:02Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:41:58Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0014	bigmorning	2023-08-13T17:40:14Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:40:08Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0014 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0014 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0037 - Train Accuracy: 0.0795 - Train Wermet: 9.2838 - Validation Loss: 0.5751 - Validation Accuracy: 0.0765 - Validation Wermet: 7.4189 - Epoch: 13 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| \| 0.0037 \| 0.0795 \| 9.2838 \| 0.5751 \| 0.0765 \| 7.4189 \| 13 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e8_s55555_v4_l4_r2	KingKazma	2023-08-13T17:39:00Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:38:59Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0013	bigmorning	2023-08-13T17:35:54Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:35:47Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0013 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0013 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.2292 - Validation Loss: 0.5687 - Validation Accuracy: 0.0767 - Validation Wermet: 8.5576 - Epoch: 12 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| \| 0.0003 \| 0.0795 \| 9.3340 \| 0.5584 \| 0.0768 \| 8.1322 \| 11 \| \| 0.0005 \| 0.0795 \| 9.2292 \| 0.5687 \| 0.0767 \| 8.5576 \| 12 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e8_s108_v4_l4_v100	KingKazma	2023-08-13T17:33:23Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:33:19Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e2_s55555_v4_l4_v100	KingKazma	2023-08-13T17:27:47Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:27:45Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0011	bigmorning	2023-08-13T17:27:17Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:27:08Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0011 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0011 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.3749 - Validation Loss: 0.5552 - Validation Accuracy: 0.0768 - Validation Wermet: 8.0800 - Epoch: 10 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| \| 0.0005 \| 0.0795 \| 9.3749 \| 0.5552 \| 0.0768 \| 8.0800 \| 10 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_round2__0010	bigmorning	2023-08-13T17:22:53Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:22:45Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0010 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0010 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.9730 - Validation Loss: 0.5605 - Validation Accuracy: 0.0767 - Validation Wermet: 8.3958 - Epoch: 9 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| \| 0.0011 \| 0.0795 \| 8.9730 \| 0.5605 \| 0.0767 \| 8.3958 \| 9 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_lora_500_10_3000_8_e8_s55555_v4_l4_r4	KingKazma	2023-08-13T17:22:22Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:22:20Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0009	bigmorning	2023-08-13T17:18:33Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:18:25Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0009 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0009 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0031 - Train Accuracy: 0.0795 - Train Wermet: 9.2135 - Validation Loss: 0.5636 - Validation Accuracy: 0.0766 - Validation Wermet: 8.2384 - Epoch: 8 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| \| 0.0031 \| 0.0795 \| 9.2135 \| 0.5636 \| 0.0766 \| 8.2384 \| 8 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e5_s55555_v4_l4_r2	KingKazma	2023-08-13T17:16:58Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:16:56Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0008	bigmorning	2023-08-13T17:14:11Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:14:03Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0008 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0008 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0037 - Train Accuracy: 0.0795 - Train Wermet: 9.3428 - Validation Loss: 0.5717 - Validation Accuracy: 0.0764 - Validation Wermet: 8.2631 - Epoch: 7 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| \| 0.0009 \| 0.0795 \| 8.7510 \| 0.5642 \| 0.0766 \| 7.9083 \| 6 \| \| 0.0037 \| 0.0795 \| 9.3428 \| 0.5717 \| 0.0764 \| 8.2631 \| 7 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e0_s55555_v4_l4_v100	KingKazma	2023-08-13T17:10:36Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:10:35Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e4_s55555_v4_l4_r2	KingKazma	2023-08-13T17:09:37Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:09:36Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e6_s55555_v4_l4_r4	KingKazma	2023-08-13T17:08:38Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:08:36Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0006	bigmorning	2023-08-13T17:05:24Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:05:17Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0006 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0006 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0012 - Train Accuracy: 0.0795 - Train Wermet: 8.8862 - Validation Loss: 0.5667 - Validation Accuracy: 0.0767 - Validation Wermet: 8.2913 - Epoch: 5 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| \| 0.0012 \| 0.0795 \| 8.8862 \| 0.5667 \| 0.0767 \| 8.2913 \| 5 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
jiaqixuac/controlnet_training	jiaqixuac	2023-08-13T17:05:05Z	0	0	diffusers	[ "diffusers", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "controlnet", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2023-08-13T14:21:44Z	--- license: creativeml-openrail-m base_model: runwayml/stable-diffusion-v1-5 tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet inference: true --- # controlnet-jiaqixuac/controlnet_training These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: red circle with blue background ![images_0)](./images_0.png) prompt: cyan circle with brown floral background ![images_1)](./images_1.png)
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e-1_s55555_v4_l4_v100	KingKazma	2023-08-13T17:02:02Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:58:53Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e5_s55555_v4_l4_r4	KingKazma	2023-08-13T17:01:46Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T17:01:44Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0005	bigmorning	2023-08-13T17:00:54Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T17:00:46Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0005 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0005 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.9053 - Validation Loss: 0.5609 - Validation Accuracy: 0.0767 - Validation Wermet: 7.5155 - Epoch: 4 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| \| 0.0011 \| 0.0795 \| 8.9053 \| 0.5609 \| 0.0767 \| 7.5155 \| 4 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e4_s108_v4_l4_v100	KingKazma	2023-08-13T16:58:48Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:58:44Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_round2__0004	bigmorning	2023-08-13T16:56:30Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:56:23Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0004 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_round2__0004 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 8.9450 - Validation Loss: 0.5623 - Validation Accuracy: 0.0766 - Validation Wermet: 7.7117 - Epoch: 3 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.0010 \| 0.0795 \| 8.7507 \| 0.5575 \| 0.0767 \| 7.6778 \| 0 \| \| 0.0013 \| 0.0795 \| 8.9468 \| 0.5652 \| 0.0766 \| 8.3360 \| 1 \| \| 0.0025 \| 0.0795 \| 8.7338 \| 0.5673 \| 0.0765 \| 8.3770 \| 2 \| \| 0.0019 \| 0.0795 \| 8.9450 \| 0.5623 \| 0.0766 \| 7.7117 \| 3 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e2_s55555_v4_l4_r2	KingKazma	2023-08-13T16:54:56Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:54:53Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
jsnbuchanan/segformer-b0-scene-parse-150	jsnbuchanan	2023-08-13T16:50:58Z	31	0	transformers	[ "transformers", "pytorch", "segformer", "generated_from_trainer", "dataset:scene_parse_150", "base_model:nvidia/mit-b0", "base_model:finetune:nvidia/mit-b0", "license:other", "endpoints_compatible", "region:us" ]	null	2023-08-01T20:37:16Z	--- license: other base_model: nvidia/mit-b0 tags: - generated_from_trainer datasets: - scene_parse_150 model-index: - name: segformer-b0-scene-parse-150 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-scene-parse-150 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset. It achieves the following results on the evaluation set: - Loss: 4.5716 - Mean Iou: 0.0039 - Mean Accuracy: 0.0219 - Overall Accuracy: 0.1398 - Per Category Iou: [0.1424604255351693, 0.0028172808510882213, 0.009342676914231785, 0.0, 0.0, 0.02331811292704824, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] - Per Category Accuracy: [0.9514506078251098, 0.0028769356391743226, 0.00966095515858549, 0.0, 0.0, 0.045009037210949, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 6e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Mean Iou \| Mean Accuracy \| Overall Accuracy \| Per Category Iou \| Per Category Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:-------------:\|:----------------:\|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:\|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:\| \| 4.8633 \| 1.0 \| 20 \| 4.8626 \| 0.0009 \| 0.0023 \| 0.0067 \| [0.0, 0.0004889263991152761, 0.0, 0.0, 0.0, 0.0, 0.03284478144986514, 0.0, 0.0, 0.014472940861907617, 0.0, 0.0009606283639651349, 0.0, 0.001090056864633105, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0033905507210453163, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.011123126834543489, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan] \| [0.0, 0.0004916838121884905, 0.0, 0.0, 0.0, 0.0, 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0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.6357 \| 6.0 \| 120 \| 3.8936 \| 0.0031 \| 0.0183 \| 0.1193 \| [0.13782355615369993, 0.00012947106753210882, 0.0020724837921139334, 0.0, 0.0, 0.002555414284014255, 0.00625454345947577, 0.0, 0.0, 0.0021069049880189433, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.8250104993132882, 0.0001317010211219171, 0.002187386073641998, 0.0, 0.0, 0.0038012186259712673, 0.0075862183699612375, 0.0, 0.0, 0.0027531003196883653, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.9752 \| 7.0 \| 140 \| 3.7886 \| 0.0046 \| 0.0208 \| 0.1099 \| [0.12970556062622363, 0.02142529574722971, 0.015682682019160826, 0.0, 0.0, 0.046496050677108665, 0.011263870769586333, 0.0, 0.0, 7.157683773530885e-05, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.6339173221643342, 0.026799694453630996, 0.017715022855380128, 0.0, 0.0, 0.2645107794361526, 0.01540534695303532, 0.0, 0.0, 8.218209909517509e-05, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 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0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.6896 \| 14.0 \| 280 \| 3.4944 \| 0.0032 \| 0.0216 \| 0.1419 \| [0.14372170627530323, 0.0, 0.0026556544494494754, 0.0, 0.0, 0.0026339040125360493, 5.807995950997109e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9887260076503105, 0.0, 0.002880058330295297, 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0.0, nan] \| \| 3.6156 \| 21.0 \| 420 \| 3.5195 \| 0.0039 \| 0.0218 \| 0.1430 \| [0.1431243377907112, 0.003771829965220418, 0.028600253499599246, 0.0, 0.0, 0.003834416457157314, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9602076026378815, 0.003869083331626098, 0.03442328724866093, 0.0, 0.0, 0.004518605474500158, 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nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.3775 \| 24.0 \| 480 \| 3.5794 \| 0.0031 \| 0.0217 \| 0.1429 \| [0.14339061919565174, 0.0004489089181295073, 0.0005344750160480256, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| 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3.2928 \| 33.0 \| 660 \| 4.2533 \| 0.0031 \| 0.0217 \| 0.1426 \| [0.1430651199052239, 0.0, 0.0, 0.0, 0.0, 0.0005383649088625119, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9971878866301177, 0.0, 0.0, 0.0, 0.0, 0.0005869528760690928, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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nan, nan, nan, nan, nan, 0.0, nan] \| \| 2.8097 \| 36.0 \| 720 \| 4.5076 \| 0.0033 \| 0.0215 \| 0.1403 \| [0.14292913158156023, 0.0009571919257359143, 6.428765090128491e-05, 0.0, 0.0, 0.008040658872532778, 0.00016170025747656383, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9762885778822034, 0.0009599541095108625, 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nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9217006617405024, 0.0035588542596500265, 0.007692307692307693, 0.0, 0.0, 0.07286600704343452, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 2.7618 \| 48.0 \| 960 \| 5.0946 \| 0.0038 \| 0.0218 \| 0.1373 \| [0.1426949704126623, 0.0032438673758399044, 0.0051523797709134515, 0.0, 0.0, 0.023948251838033993, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.93417498098773, 0.0033217924216305756, 0.005241313553380633, 0.0, 0.0, 0.05908658952428867, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.7284 \| 49.0 \| 980 \| 4.0830 \| 0.0043 \| 0.0221 \| 0.1373 \| [0.14283896315255537, 0.0034238556212341873, 0.024018439121225456, 0.0, 0.0, 0.029172219275206687, 0.0002549698559831555, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9045640798628847, 0.0035091005405595245, 0.026329958776185537, 0.0, 0.0, 0.08402742840106583, 0.00025786487880350697, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| \| 3.6351 \| 50.0 \| 1000 \| 4.5716 \| 0.0039 \| 0.0219 \| 0.1398 \| [0.1424604255351693, 0.0028172808510882213, 0.009342676914231785, 0.0, 0.0, 0.02331811292704824, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| [0.9514506078251098, 0.0028769356391743226, 0.00966095515858549, 0.0, 0.0, 0.045009037210949, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.1.0.dev20230812 - Datasets 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e3_s108_v4_l4_v100	KingKazma	2023-08-13T16:50:09Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:50:05Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
LBR47/speecht5_finetuned_voxpopuli_nl	LBR47	2023-08-13T16:49:06Z	82	0	transformers	[ "transformers", "pytorch", "speecht5", "text-to-audio", "text-to-speech", "dataset:voxpopuli", "endpoints_compatible", "region:us" ]	text-to-speech	2023-08-13T16:41:15Z	--- base_model: speechT5 tags: - text-to-speech datasets: - voxpopuli model-index: - name: speecht5_finetuned_voxpopuli_nl results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # speecht5_finetuned_voxpopuli_nl This model is a fine-tuned version of [speechT5](https://huggingface.co/speechT5) on the voxpopuli dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 4 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 ### Framework versions - Transformers 4.31.0 - Pytorch 1.12.1+cpu - Datasets 2.13.1 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e8_s108_v4_l4_v100	KingKazma	2023-08-13T16:47:03Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:47:02Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e1_s55555_v4_l4_r4	KingKazma	2023-08-13T16:34:17Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:34:15Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e1_s108_v4_l4_v100	KingKazma	2023-08-13T16:32:55Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:32:49Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
digicazter/wav2vec2-base-timit-demo-google-colab	digicazter	2023-08-13T16:32:43Z	105	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "base_model:facebook/wav2vec2-base", "base_model:finetune:facebook/wav2vec2-base", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-07T03:20:25Z	--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-base-timit-demo-google-colab results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wav2vec2-base-timit-demo-google-colab This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0392 - Wer: 1.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 400 - num_epochs: 150 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---:\| \| 5.2993 \| 8.0 \| 200 \| 3.0327 \| 1.0 \| \| 3.0806 \| 16.0 \| 400 \| 3.0476 \| 1.0 \| \| 3.0219 \| 24.0 \| 600 \| 3.0472 \| 1.0 \| \| 3.0179 \| 32.0 \| 800 \| 3.0435 \| 1.0 \| \| 3.0157 \| 40.0 \| 1000 \| 3.0546 \| 1.0 \| \| 3.0146 \| 48.0 \| 1200 \| 3.0484 \| 1.0 \| \| 3.0139 \| 56.0 \| 1400 \| 3.0344 \| 1.0 \| \| 3.0118 \| 64.0 \| 1600 \| 3.0351 \| 1.0 \| \| 3.0114 \| 72.0 \| 1800 \| 3.0559 \| 1.0 \| \| 3.0114 \| 80.0 \| 2000 \| 3.0526 \| 1.0 \| \| 3.0108 \| 88.0 \| 2200 \| 3.0417 \| 1.0 \| \| 3.0092 \| 96.0 \| 2400 \| 3.0629 \| 1.0 \| \| 3.0089 \| 104.0 \| 2600 \| 3.0352 \| 1.0 \| \| 3.0083 \| 112.0 \| 2800 \| 3.0503 \| 1.0 \| \| 3.0078 \| 120.0 \| 3000 \| 3.0529 \| 1.0 \| \| 3.0072 \| 128.0 \| 3200 \| 3.0378 \| 1.0 \| \| 3.0068 \| 136.0 \| 3400 \| 3.0481 \| 1.0 \| \| 3.0063 \| 144.0 \| 3600 \| 3.0392 \| 1.0 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.3 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e9_s108_v4_l4_r2	KingKazma	2023-08-13T16:22:59Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:22:58Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0098	bigmorning	2023-08-13T16:22:52Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:22:44Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0098 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0098 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0044 - Train Accuracy: 0.0794 - Train Wermet: 8.8948 - Validation Loss: 0.5589 - Validation Accuracy: 0.0765 - Validation Wermet: 7.4085 - Epoch: 97 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| \| 0.0029 \| 0.0795 \| 10.1412 \| 0.5666 \| 0.0764 \| 9.0822 \| 91 \| \| 0.0042 \| 0.0795 \| 9.5603 \| 0.5582 \| 0.0765 \| 7.6837 \| 92 \| \| 0.0015 \| 0.0795 \| 9.4004 \| 0.5495 \| 0.0766 \| 7.7859 \| 93 \| \| 0.0008 \| 0.0795 \| 9.5417 \| 0.5503 \| 0.0767 \| 7.8876 \| 94 \| \| 0.0005 \| 0.0795 \| 9.3473 \| 0.5590 \| 0.0766 \| 7.8967 \| 95 \| \| 0.0016 \| 0.0795 \| 9.1740 \| 0.5746 \| 0.0765 \| 7.8469 \| 96 \| \| 0.0044 \| 0.0794 \| 8.8948 \| 0.5589 \| 0.0765 \| 7.4085 \| 97 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e-1_s108_v4_l4_v100	KingKazma	2023-08-13T16:15:39Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:15:36Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0096	bigmorning	2023-08-13T16:14:08Z	60	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:14:00Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0096 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0096 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.3473 - Validation Loss: 0.5590 - Validation Accuracy: 0.0766 - Validation Wermet: 7.8967 - Epoch: 95 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| \| 0.0029 \| 0.0795 \| 10.1412 \| 0.5666 \| 0.0764 \| 9.0822 \| 91 \| \| 0.0042 \| 0.0795 \| 9.5603 \| 0.5582 \| 0.0765 \| 7.6837 \| 92 \| \| 0.0015 \| 0.0795 \| 9.4004 \| 0.5495 \| 0.0766 \| 7.7859 \| 93 \| \| 0.0008 \| 0.0795 \| 9.5417 \| 0.5503 \| 0.0767 \| 7.8876 \| 94 \| \| 0.0005 \| 0.0795 \| 9.3473 \| 0.5590 \| 0.0766 \| 7.8967 \| 95 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_lora_500_10_3000_8_e9_s108_v4_l4_r4	KingKazma	2023-08-13T16:13:40Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:13:38Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e4_s108_v4_l4_v100	KingKazma	2023-08-13T16:12:42Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:12:40Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0095	bigmorning	2023-08-13T16:09:46Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:09:40Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0095 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0095 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0008 - Train Accuracy: 0.0795 - Train Wermet: 9.5417 - Validation Loss: 0.5503 - Validation Accuracy: 0.0767 - Validation Wermet: 7.8876 - Epoch: 94 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| \| 0.0029 \| 0.0795 \| 10.1412 \| 0.5666 \| 0.0764 \| 9.0822 \| 91 \| \| 0.0042 \| 0.0795 \| 9.5603 \| 0.5582 \| 0.0765 \| 7.6837 \| 92 \| \| 0.0015 \| 0.0795 \| 9.4004 \| 0.5495 \| 0.0766 \| 7.7859 \| 93 \| \| 0.0008 \| 0.0795 \| 9.5417 \| 0.5503 \| 0.0767 \| 7.8876 \| 94 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e7_s108_v4_l4_r2	KingKazma	2023-08-13T16:08:19Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:08:17Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
DHEIVER/Brain_Tumor_Classification	DHEIVER	2023-08-13T16:06:23Z	182	0	transformers	[ "transformers", "pytorch", "swin", "image-classification", "generated_from_trainer", "dataset:imagefolder", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2023-08-13T16:04:30Z	--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy - f1 - recall - precision model-index: - name: Brain_Tumor_Classification results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9646761984861227 - name: F1 type: f1 value: 0.9646761984861227 - name: Recall type: recall value: 0.9646761984861227 - name: Precision type: precision value: 0.9646761984861227 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Brain_Tumor_Classification This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.1012 - Accuracy: 0.9647 - F1: 0.9647 - Recall: 0.9647 - Precision: 0.9647 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| F1 \| Recall \| Precision \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\|:------:\|:---------:\| \| 0.4856 \| 0.99 \| 83 \| 0.3771 \| 0.8444 \| 0.8444 \| 0.8444 \| 0.8444 \| \| 0.3495 \| 1.99 \| 166 \| 0.2608 \| 0.8949 \| 0.8949 \| 0.8949 \| 0.8949 \| \| 0.252 \| 2.99 \| 249 \| 0.1445 \| 0.9487 \| 0.9487 \| 0.9487 \| 0.9487 \| \| 0.2364 \| 3.99 \| 332 \| 0.1029 \| 0.9588 \| 0.9588 \| 0.9588 \| 0.9588 \| \| 0.2178 \| 4.99 \| 415 \| 0.1012 \| 0.9647 \| 0.9647 \| 0.9647 \| 0.9647 \| ### Framework versions - Transformers 4.23.1 - Pytorch 1.12.1 - Datasets 2.6.1 - Tokenizers 0.13.1
bigmorning/whisper_charsplit_new_0094	bigmorning	2023-08-13T16:05:30Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:05:24Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0094 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0094 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0015 - Train Accuracy: 0.0795 - Train Wermet: 9.4004 - Validation Loss: 0.5495 - Validation Accuracy: 0.0766 - Validation Wermet: 7.7859 - Epoch: 93 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| \| 0.0029 \| 0.0795 \| 10.1412 \| 0.5666 \| 0.0764 \| 9.0822 \| 91 \| \| 0.0042 \| 0.0795 \| 9.5603 \| 0.5582 \| 0.0765 \| 7.6837 \| 92 \| \| 0.0015 \| 0.0795 \| 9.4004 \| 0.5495 \| 0.0766 \| 7.7859 \| 93 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
evanyin/openai-whisper-tiny-LORA-colab-test	evanyin	2023-08-13T16:05:21Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-08T15:32:52Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e3_s108_v4_l4_v100	KingKazma	2023-08-13T16:04:06Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:04:05Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
udayGay/resume_model	udayGay	2023-08-13T16:03:19Z	3	0	transformers	[ "transformers", "tf", "distilbert", "text-classification", "generated_from_keras_callback", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-12T16:11:53Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: udayGay/resume_model results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # udayGay/resume_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 1.1040 - Validation Loss: 1.4298 - Train Accuracy: 0.6640 - Train Precision: 0.5589 - Train Recall: 0.5938 - Train F1: 0.5692 - Epoch: 29 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1470, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} - training_precision: float32 ### Training results \| Train Loss \| Validation Loss \| Train Accuracy \| Train Precision \| Train Recall \| Train F1 \| Epoch \| \|:----------:\|:---------------:\|:--------------:\|:---------------:\|:------------:\|:--------:\|:-----:\| \| 3.1654 \| 3.1440 \| 0.0402 \| 0.0017 \| 0.0417 \| 0.0033 \| 0 \| \| 3.1553 \| 3.1474 \| 0.0282 \| 0.0012 \| 0.0417 \| 0.0023 \| 1 \| \| 3.1208 \| 3.0528 \| 0.0805 \| 0.0147 \| 0.0812 \| 0.0225 \| 2 \| \| 2.9896 \| 2.8784 \| 0.1469 \| 0.0746 \| 0.1384 \| 0.0825 \| 3 \| \| 2.6886 \| 2.5739 \| 0.3300 \| 0.2207 \| 0.3033 \| 0.2182 \| 4 \| \| 2.2855 \| 2.1620 \| 0.4547 \| 0.3432 \| 0.4138 \| 0.3395 \| 5 \| \| 1.9018 \| 1.9030 \| 0.5151 \| 0.4141 \| 0.4679 \| 0.4118 \| 6 \| \| 1.6218 \| 1.7029 \| 0.5795 \| 0.4872 \| 0.5205 \| 0.4854 \| 7 \| \| 1.4058 \| 1.5916 \| 0.6217 \| 0.5261 \| 0.5595 \| 0.5278 \| 8 \| \| 1.2705 \| 1.4954 \| 0.6479 \| 0.5457 \| 0.5815 \| 0.5557 \| 9 \| \| 1.1692 \| 1.4469 \| 0.6600 \| 0.5548 \| 0.5896 \| 0.5643 \| 10 \| \| 1.1179 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 11 \| \| 1.1162 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 12 \| \| 1.1109 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 13 \| \| 1.1142 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 14 \| \| 1.1095 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 15 \| \| 1.1108 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 16 \| \| 1.1133 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 17 \| \| 1.1132 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 18 \| \| 1.1064 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 19 \| \| 1.1098 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 20 \| \| 1.1029 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 21 \| \| 1.1055 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 22 \| \| 1.1125 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 23 \| \| 1.1081 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 24 \| \| 1.1125 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 25 \| \| 1.1130 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 26 \| \| 1.1101 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 27 \| \| 1.1134 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 28 \| \| 1.1040 \| 1.4298 \| 0.6640 \| 0.5589 \| 0.5938 \| 0.5692 \| 29 \| ### Framework versions - Transformers 4.31.0 - TensorFlow 2.12.0 - Datasets 2.14.4 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0093	bigmorning	2023-08-13T16:01:10Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T16:01:02Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0093 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0093 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0042 - Train Accuracy: 0.0795 - Train Wermet: 9.5603 - Validation Loss: 0.5582 - Validation Accuracy: 0.0765 - Validation Wermet: 7.6837 - Epoch: 92 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| \| 0.0029 \| 0.0795 \| 10.1412 \| 0.5666 \| 0.0764 \| 9.0822 \| 91 \| \| 0.0042 \| 0.0795 \| 9.5603 \| 0.5582 \| 0.0765 \| 7.6837 \| 92 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e6_s108_v4_l4_r2	KingKazma	2023-08-13T16:00:59Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T16:00:57Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e7_s108_v4_l4_r4	KingKazma	2023-08-13T15:59:56Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:59:53Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
Sakil/llama2_finetuned_medical_assistant	Sakil	2023-08-13T15:59:29Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:39:26Z	--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float16 ### Framework versions - PEFT 0.4.0
fathyshalab/mdcsi-unterhaltung-kultur-freizeit-setfit	fathyshalab	2023-08-13T15:56:44Z	5	0	sentence-transformers	[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]	text-classification	2023-08-13T15:55:53Z	--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpyb2_zis8\fathyshalab\mdcsi-unterhaltung-kultur-freizeit-setfit This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage To use this model for inference, first install the SetFit library: ```bash python -m pip install setfit ``` You can then run inference as follows: ```python from setfit import SetFitModel # Download from Hub and run inference model = SetFitModel.from_pretrained("C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpyb2_zis8\fathyshalab\mdcsi-unterhaltung-kultur-freizeit-setfit") # Run inference preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"]) ``` ## BibTeX entry and citation info ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e2_s108_v4_l4_v100	KingKazma	2023-08-13T15:55:31Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:55:30Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e5_s108_v4_l4_r2	KingKazma	2023-08-13T15:53:39Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:53:37Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e6_s108_v4_l4_r4	KingKazma	2023-08-13T15:53:04Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:53:02Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0091	bigmorning	2023-08-13T15:52:18Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T15:52:10Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0091 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0091 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0006 - Train Accuracy: 0.0795 - Train Wermet: 10.2538 - Validation Loss: 0.5541 - Validation Accuracy: 0.0766 - Validation Wermet: 8.7676 - Epoch: 90 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| \| 0.0007 \| 0.0795 \| 10.2569 \| 0.5488 \| 0.0766 \| 8.9133 \| 89 \| \| 0.0006 \| 0.0795 \| 10.2538 \| 0.5541 \| 0.0766 \| 8.7676 \| 90 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e1_s108_v4_l4_v100	KingKazma	2023-08-13T15:46:55Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:46:54Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e4_s108_v4_l4_r2	KingKazma	2023-08-13T15:46:18Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:46:17Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_gpt2_lora_500_10_3000_8_e5_s108_v4_l4_r4	KingKazma	2023-08-13T15:46:12Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:46:10Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0089	bigmorning	2023-08-13T15:43:30Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T15:43:22Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0089 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0089 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 10.3176 - Validation Loss: 0.5492 - Validation Accuracy: 0.0766 - Validation Wermet: 8.5812 - Epoch: 88 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| \| 0.0019 \| 0.0795 \| 10.3176 \| 0.5492 \| 0.0766 \| 8.5812 \| 88 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_gpt2_lora_500_10_3000_8_e4_s108_v4_l4_r4	KingKazma	2023-08-13T15:39:20Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:39:18Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0088	bigmorning	2023-08-13T15:39:10Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T15:39:03Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0088 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0088 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0038 - Train Accuracy: 0.0795 - Train Wermet: 10.1430 - Validation Loss: 0.5538 - Validation Accuracy: 0.0765 - Validation Wermet: 9.1635 - Epoch: 87 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| \| 0.0038 \| 0.0795 \| 10.1430 \| 0.5538 \| 0.0765 \| 9.1635 \| 87 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e3_s108_v4_l4_r2	KingKazma	2023-08-13T15:38:58Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T15:38:56Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0087	bigmorning	2023-08-13T15:34:44Z	59	0	transformers	[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-13T15:34:36Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0087 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # whisper_charsplit_new_0087 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0034 - Train Accuracy: 0.0795 - Train Wermet: 10.5048 - Validation Loss: 0.5578 - Validation Accuracy: 0.0764 - Validation Wermet: 8.9920 - Epoch: 86 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results \| Train Loss \| Train Accuracy \| Train Wermet \| Validation Loss \| Validation Accuracy \| Validation Wermet \| Epoch \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 0.0602 \| 13.0686 \| 0.6470 \| 0.0676 \| 11.4066 \| 0 \| \| 0.5740 \| 0.0666 \| 12.7778 \| 0.5113 \| 0.0706 \| 11.1022 \| 1 \| \| 0.4553 \| 0.0692 \| 12.2404 \| 0.4371 \| 0.0723 \| 10.9105 \| 2 \| \| 0.3813 \| 0.0708 \| 11.9157 \| 0.3935 \| 0.0733 \| 9.4615 \| 3 \| \| 0.3292 \| 0.0720 \| 11.5732 \| 0.3630 \| 0.0740 \| 9.9885 \| 4 \| \| 0.2886 \| 0.0729 \| 11.5171 \| 0.3403 \| 0.0745 \| 9.8042 \| 5 \| \| 0.2561 \| 0.0736 \| 11.3173 \| 0.3256 \| 0.0749 \| 9.9431 \| 6 \| \| 0.2282 \| 0.0743 \| 11.7308 \| 0.3159 \| 0.0752 \| 9.2086 \| 7 \| \| 0.2036 \| 0.0748 \| 11.4503 \| 0.3071 \| 0.0754 \| 9.5236 \| 8 \| \| 0.1820 \| 0.0754 \| 11.7175 \| 0.3005 \| 0.0756 \| 10.0755 \| 9 \| \| 0.1628 \| 0.0758 \| 11.7056 \| 0.2993 \| 0.0757 \| 9.9497 \| 10 \| \| 0.1450 \| 0.0762 \| 11.7637 \| 0.2971 \| 0.0758 \| 10.1481 \| 11 \| \| 0.1287 \| 0.0766 \| 11.8509 \| 0.3029 \| 0.0759 \| 10.2042 \| 12 \| \| 0.1140 \| 0.0770 \| 12.1100 \| 0.3004 \| 0.0760 \| 10.3873 \| 13 \| \| 0.0998 \| 0.0773 \| 11.9502 \| 0.3025 \| 0.0761 \| 10.7066 \| 14 \| \| 0.0872 \| 0.0777 \| 12.3196 \| 0.3129 \| 0.0759 \| 10.7707 \| 15 \| \| 0.0760 \| 0.0779 \| 12.2637 \| 0.3142 \| 0.0761 \| 10.2638 \| 16 \| \| 0.0651 \| 0.0782 \| 12.1215 \| 0.3192 \| 0.0761 \| 10.0750 \| 17 \| \| 0.0547 \| 0.0785 \| 12.0551 \| 0.3294 \| 0.0761 \| 10.4732 \| 18 \| \| 0.0463 \| 0.0787 \| 11.9677 \| 0.3402 \| 0.0760 \| 10.2814 \| 19 \| \| 0.0386 \| 0.0789 \| 11.6855 \| 0.3517 \| 0.0760 \| 10.0599 \| 20 \| \| 0.0318 \| 0.0790 \| 11.6314 \| 0.3628 \| 0.0760 \| 9.6652 \| 21 \| \| 0.0262 \| 0.0792 \| 11.4603 \| 0.3728 \| 0.0760 \| 10.0035 \| 22 \| \| 0.0224 \| 0.0792 \| 11.4330 \| 0.3824 \| 0.0760 \| 9.1995 \| 23 \| \| 0.0181 \| 0.0793 \| 11.3124 \| 0.3982 \| 0.0759 \| 9.8710 \| 24 \| \| 0.0142 \| 0.0794 \| 11.3562 \| 0.4057 \| 0.0760 \| 9.6831 \| 25 \| \| 0.0118 \| 0.0794 \| 11.0532 \| 0.4207 \| 0.0759 \| 9.7227 \| 26 \| \| 0.0101 \| 0.0794 \| 11.2963 \| 0.4282 \| 0.0760 \| 9.5792 \| 27 \| \| 0.0114 \| 0.0794 \| 11.3093 \| 0.4431 \| 0.0758 \| 9.5545 \| 28 \| \| 0.0109 \| 0.0794 \| 11.4214 \| 0.4419 \| 0.0760 \| 9.4377 \| 29 \| \| 0.0084 \| 0.0794 \| 10.9143 \| 0.4474 \| 0.0760 \| 9.3668 \| 30 \| \| 0.0043 \| 0.0795 \| 10.9497 \| 0.4525 \| 0.0761 \| 9.3202 \| 31 \| \| 0.0036 \| 0.0795 \| 10.7759 \| 0.4667 \| 0.0761 \| 9.0385 \| 32 \| \| 0.0047 \| 0.0795 \| 10.7613 \| 0.4788 \| 0.0759 \| 9.4065 \| 33 \| \| 0.0130 \| 0.0793 \| 11.1022 \| 0.4748 \| 0.0760 \| 9.4521 \| 34 \| \| 0.0074 \| 0.0794 \| 10.9738 \| 0.4730 \| 0.0760 \| 9.3348 \| 35 \| \| 0.0032 \| 0.0795 \| 10.6370 \| 0.4750 \| 0.0762 \| 8.8298 \| 36 \| \| 0.0020 \| 0.0795 \| 10.7428 \| 0.4835 \| 0.0762 \| 9.0566 \| 37 \| \| 0.0014 \| 0.0795 \| 10.6908 \| 0.4937 \| 0.0761 \| 9.2445 \| 38 \| \| 0.0035 \| 0.0795 \| 10.6833 \| 0.5276 \| 0.0757 \| 8.9798 \| 39 \| \| 0.0120 \| 0.0793 \| 10.4810 \| 0.4963 \| 0.0760 \| 8.9194 \| 40 \| \| 0.0045 \| 0.0795 \| 10.2251 \| 0.5014 \| 0.0761 \| 8.5737 \| 41 \| \| 0.0028 \| 0.0795 \| 10.3174 \| 0.4968 \| 0.0762 \| 8.8525 \| 42 \| \| 0.0023 \| 0.0795 \| 10.4871 \| 0.5027 \| 0.0762 \| 8.6712 \| 43 \| \| 0.0024 \| 0.0795 \| 10.3731 \| 0.5055 \| 0.0762 \| 8.6347 \| 44 \| \| 0.0041 \| 0.0795 \| 10.2751 \| 0.5242 \| 0.0760 \| 8.3671 \| 45 \| \| 0.0070 \| 0.0794 \| 10.2166 \| 0.5169 \| 0.0760 \| 8.8409 \| 46 \| \| 0.0037 \| 0.0795 \| 10.0455 \| 0.5174 \| 0.0762 \| 8.2514 \| 47 \| \| 0.0023 \| 0.0795 \| 9.9201 \| 0.5167 \| 0.0763 \| 8.9537 \| 48 \| \| 0.0008 \| 0.0795 \| 10.0022 \| 0.5166 \| 0.0764 \| 8.4855 \| 49 \| \| 0.0006 \| 0.0795 \| 9.9494 \| 0.5233 \| 0.0763 \| 8.5719 \| 50 \| \| 0.0069 \| 0.0794 \| 10.2037 \| 0.5434 \| 0.0759 \| 8.5399 \| 51 \| \| 0.0083 \| 0.0794 \| 9.9557 \| 0.5173 \| 0.0762 \| 8.2406 \| 52 \| \| 0.0032 \| 0.0795 \| 10.0283 \| 0.5240 \| 0.0763 \| 9.0101 \| 53 \| \| 0.0018 \| 0.0795 \| 10.0694 \| 0.5247 \| 0.0763 \| 8.5717 \| 54 \| \| 0.0008 \| 0.0795 \| 10.1079 \| 0.5217 \| 0.0764 \| 8.5608 \| 55 \| \| 0.0005 \| 0.0795 \| 10.0546 \| 0.5286 \| 0.0764 \| 8.8830 \| 56 \| \| 0.0007 \| 0.0795 \| 10.2557 \| 0.5328 \| 0.0764 \| 8.5665 \| 57 \| \| 0.0006 \| 0.0795 \| 10.2165 \| 0.5412 \| 0.0763 \| 8.4623 \| 58 \| \| 0.0124 \| 0.0792 \| 10.2304 \| 0.5284 \| 0.0762 \| 9.1194 \| 59 \| \| 0.0044 \| 0.0795 \| 10.3884 \| 0.5223 \| 0.0764 \| 8.8152 \| 60 \| \| 0.0015 \| 0.0795 \| 9.8557 \| 0.5227 \| 0.0764 \| 8.3774 \| 61 \| \| 0.0005 \| 0.0795 \| 9.8123 \| 0.5233 \| 0.0765 \| 8.5043 \| 62 \| \| 0.0003 \| 0.0795 \| 9.7631 \| 0.5282 \| 0.0765 \| 8.3860 \| 63 \| \| 0.0003 \| 0.0795 \| 9.7593 \| 0.5320 \| 0.0765 \| 8.4815 \| 64 \| \| 0.0002 \| 0.0795 \| 9.7663 \| 0.5357 \| 0.0765 \| 8.4281 \| 65 \| \| 0.0034 \| 0.0795 \| 9.8382 \| 0.5771 \| 0.0758 \| 8.8051 \| 66 \| \| 0.0123 \| 0.0792 \| 10.2575 \| 0.5261 \| 0.0763 \| 9.3701 \| 67 \| \| 0.0027 \| 0.0795 \| 10.3802 \| 0.5272 \| 0.0764 \| 8.8216 \| 68 \| \| 0.0011 \| 0.0795 \| 10.1683 \| 0.5291 \| 0.0764 \| 8.5736 \| 69 \| \| 0.0012 \| 0.0795 \| 10.1305 \| 0.5336 \| 0.0765 \| 8.6648 \| 70 \| \| 0.0008 \| 0.0795 \| 10.2545 \| 0.5315 \| 0.0765 \| 9.0617 \| 71 \| \| 0.0006 \| 0.0795 \| 10.4562 \| 0.5369 \| 0.0765 \| 9.6485 \| 72 \| \| 0.0032 \| 0.0795 \| 10.2347 \| 0.5569 \| 0.0763 \| 8.4947 \| 73 \| \| 0.0062 \| 0.0794 \| 10.1654 \| 0.5471 \| 0.0763 \| 8.8666 \| 74 \| \| 0.0029 \| 0.0795 \| 10.1320 \| 0.5376 \| 0.0765 \| 8.7713 \| 75 \| \| 0.0012 \| 0.0795 \| 10.2943 \| 0.5406 \| 0.0765 \| 8.6959 \| 76 \| \| 0.0006 \| 0.0795 \| 10.1888 \| 0.5371 \| 0.0767 \| 8.9689 \| 77 \| \| 0.0005 \| 0.0795 \| 10.2138 \| 0.5398 \| 0.0766 \| 8.7470 \| 78 \| \| 0.0016 \| 0.0795 \| 10.2173 \| 0.5497 \| 0.0764 \| 8.9675 \| 79 \| \| 0.0065 \| 0.0794 \| 10.2806 \| 0.5559 \| 0.0763 \| 9.4487 \| 80 \| \| 0.0028 \| 0.0795 \| 10.7728 \| 0.5394 \| 0.0766 \| 8.9716 \| 81 \| \| 0.0012 \| 0.0795 \| 10.3247 \| 0.5453 \| 0.0765 \| 8.9986 \| 82 \| \| 0.0013 \| 0.0795 \| 10.3174 \| 0.5535 \| 0.0765 \| 8.9229 \| 83 \| \| 0.0011 \| 0.0795 \| 10.2846 \| 0.5452 \| 0.0766 \| 9.1239 \| 84 \| \| 0.0007 \| 0.0795 \| 10.1996 \| 0.5491 \| 0.0766 \| 8.9308 \| 85 \| \| 0.0034 \| 0.0795 \| 10.5048 \| 0.5578 \| 0.0764 \| 8.9920 \| 86 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_round2__0040

bigmorning

2023-08-13T19:34:23Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T19:34:15Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0040 results: [] ---  # whisper_charsplit_new_round2__0040 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0002 - Train Accuracy: 0.0795 - Train Wermet: 7.9500 - Validation Loss: 0.5660 - Validation Accuracy: 0.0769 - Validation Wermet: 7.0891 - Epoch: 39 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | | 0.0019 | 0.0795 | 8.6037 | 0.5715 | 0.0767 | 7.6157 | 31 | | 0.0009 | 0.0795 | 8.4768 | 0.5611 | 0.0769 | 7.6392 | 32 | | 0.0005 | 0.0795 | 8.2728 | 0.5669 | 0.0768 | 7.1451 | 33 | | 0.0010 | 0.0795 | 8.1006 | 0.5918 | 0.0766 | 7.4447 | 34 | | 0.0036 | 0.0795 | 8.9171 | 0.5687 | 0.0767 | 7.6962 | 35 | | 0.0018 | 0.0795 | 8.4062 | 0.5713 | 0.0768 | 7.2127 | 36 | | 0.0012 | 0.0795 | 8.3370 | 0.5683 | 0.0768 | 7.1040 | 37 | | 0.0005 | 0.0795 | 7.9931 | 0.5658 | 0.0769 | 6.8043 | 38 | | 0.0002 | 0.0795 | 7.9500 | 0.5660 | 0.0769 | 7.0891 | 39 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_prefix_tuning_500_10_3000_8_e-1_s108_v4_l4_v100

KingKazma

2023-08-13T19:31:02Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T18:33:45Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e4_s108_v4_l4_v100

KingKazma

2023-08-13T19:29:03Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T19:29:02Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0037

bigmorning

2023-08-13T19:21:21Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T19:21:12Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0037 results: [] ---  # whisper_charsplit_new_round2__0037 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0018 - Train Accuracy: 0.0795 - Train Wermet: 8.4062 - Validation Loss: 0.5713 - Validation Accuracy: 0.0768 - Validation Wermet: 7.2127 - Epoch: 36 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | | 0.0019 | 0.0795 | 8.6037 | 0.5715 | 0.0767 | 7.6157 | 31 | | 0.0009 | 0.0795 | 8.4768 | 0.5611 | 0.0769 | 7.6392 | 32 | | 0.0005 | 0.0795 | 8.2728 | 0.5669 | 0.0768 | 7.1451 | 33 | | 0.0010 | 0.0795 | 8.1006 | 0.5918 | 0.0766 | 7.4447 | 34 | | 0.0036 | 0.0795 | 8.9171 | 0.5687 | 0.0767 | 7.6962 | 35 | | 0.0018 | 0.0795 | 8.4062 | 0.5713 | 0.0768 | 7.2127 | 36 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e3_s108_v4_l4_v100

KingKazma

2023-08-13T19:20:14Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T19:20:13Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_prefix_tuning_500_10_3000_8_e5_s108_v4_l4_v100

KingKazma

2023-08-13T19:20:07Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T19:20:06Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0036

bigmorning

2023-08-13T19:16:56Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T19:16:50Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0036 results: [] ---  # whisper_charsplit_new_round2__0036 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0036 - Train Accuracy: 0.0795 - Train Wermet: 8.9171 - Validation Loss: 0.5687 - Validation Accuracy: 0.0767 - Validation Wermet: 7.6962 - Epoch: 35 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | | 0.0019 | 0.0795 | 8.6037 | 0.5715 | 0.0767 | 7.6157 | 31 | | 0.0009 | 0.0795 | 8.4768 | 0.5611 | 0.0769 | 7.6392 | 32 | | 0.0005 | 0.0795 | 8.2728 | 0.5669 | 0.0768 | 7.1451 | 33 | | 0.0010 | 0.0795 | 8.1006 | 0.5918 | 0.0766 | 7.4447 | 34 | | 0.0036 | 0.0795 | 8.9171 | 0.5687 | 0.0767 | 7.6962 | 35 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_round2__0035

bigmorning

2023-08-13T19:12:33Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T19:12:25Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0035 results: [] ---  # whisper_charsplit_new_round2__0035 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0010 - Train Accuracy: 0.0795 - Train Wermet: 8.1006 - Validation Loss: 0.5918 - Validation Accuracy: 0.0766 - Validation Wermet: 7.4447 - Epoch: 34 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | | 0.0019 | 0.0795 | 8.6037 | 0.5715 | 0.0767 | 7.6157 | 31 | | 0.0009 | 0.0795 | 8.4768 | 0.5611 | 0.0769 | 7.6392 | 32 | | 0.0005 | 0.0795 | 8.2728 | 0.5669 | 0.0768 | 7.1451 | 33 | | 0.0010 | 0.0795 | 8.1006 | 0.5918 | 0.0766 | 7.4447 | 34 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

TheRains/yt-special-batch12-lr4-augment-small

TheRains

2023-08-13T19:08:42Z

114

0

transformers

[ "transformers", "pytorch", "tensorboard", "whisper", "automatic-speech-recognition", "whisper-event", "generated_from_trainer", "dataset:yt", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:31:02Z

--- license: apache-2.0 base_model: openai/whisper-small tags: - whisper-event - generated_from_trainer datasets: - yt metrics: - wer model-index: - name: Whisper Small Indonesian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: yt id type: yt metrics: - name: Wer type: wer value: 38.89501329356072 ---  # Whisper Small Indonesian This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the yt id dataset. It achieves the following results on the evaluation set: - Loss: 0.7352 - Wer: 38.8950 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 12 - eval_batch_size: 6 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.296 | 0.13 | 1000 | 1.3286 | 110.0123 | | 1.1522 | 0.26 | 2000 | 1.0917 | 81.6354 | | 1.0175 | 0.39 | 3000 | 0.9399 | 60.1258 | | 0.7844 | 0.52 | 4000 | 0.8174 | 43.4862 | | 0.5919 | 0.64 | 5000 | 0.7352 | 38.8950 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3

Lyviaa/Tokyoo

Lyviaa

2023-08-13T19:03:38Z

0

null

[ "license:creativeml-openrail-m", "region:us" ]

null

2023-08-13T19:02:57Z

--- license: creativeml-openrail-m ---

bigmorning/whisper_charsplit_new_round2__0032

bigmorning

2023-08-13T18:59:27Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:59:19Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0032 results: [] ---  # whisper_charsplit_new_round2__0032 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 8.6037 - Validation Loss: 0.5715 - Validation Accuracy: 0.0767 - Validation Wermet: 7.6157 - Epoch: 31 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | | 0.0019 | 0.0795 | 8.6037 | 0.5715 | 0.0767 | 7.6157 | 31 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_round2__0031

bigmorning

2023-08-13T18:55:01Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:54:54Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0031 results: [] ---  # whisper_charsplit_new_round2__0031 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0022 - Train Accuracy: 0.0795 - Train Wermet: 8.2353 - Validation Loss: 0.5789 - Validation Accuracy: 0.0767 - Validation Wermet: 7.4442 - Epoch: 30 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | | 0.0007 | 0.0795 | 8.5183 | 0.5688 | 0.0768 | 7.4310 | 28 | | 0.0014 | 0.0795 | 8.6604 | 0.5750 | 0.0767 | 8.0751 | 29 | | 0.0022 | 0.0795 | 8.2353 | 0.5789 | 0.0767 | 7.4442 | 30 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prefix_tuning_500_10_3000_8_e1_s108_v4_l4_v100

KingKazma

2023-08-13T18:52:26Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T18:13:23Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

mani05/dqn-SpaceInvadersNoFrameskip-v4

mani05

2023-08-13T18:48:49Z

7

0

stable-baselines3

[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2023-08-13T18:48:14Z

--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 metrics: - type: mean_reward value: 649.00 +/- 125.61 name: mean_reward verified: false --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga mani05 -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga mani05 -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga mani05 ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 1000000.0), ('optimize_memory_usage', False), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ``` # Environment Arguments ```python {'render_mode': 'rgb_array'} ```

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_8_e-1_s108_v4_l4_v100

KingKazma

2023-08-13T18:44:54Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:37:23Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

fathyshalab/mdcsi-wasser-strom-gas-setfit

fathyshalab

2023-08-13T18:43:28Z

5

0

sentence-transformers

[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]

text-classification

2023-08-13T16:58:18Z

--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpj64pfrsp\fathyshalab\mdcsi-wasser-strom-gas-setfit This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage To use this model for inference, first install the SetFit library: ```bash python -m pip install setfit ``` You can then run inference as follows: ```python from setfit import SetFitModel # Download from Hub and run inference model = SetFitModel.from_pretrained("C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpj64pfrsp\fathyshalab\mdcsi-wasser-strom-gas-setfit") # Run inference preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"]) ``` ## BibTeX entry and citation info ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```

KingKazma/xsum_gpt2_prompt_tuning_500_10_3000_8_e0_s108_v4_l5_v50

KingKazma

2023-08-13T18:41:53Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:43:19Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0028

bigmorning

2023-08-13T18:41:43Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:41:37Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0028 results: [] ---  # whisper_charsplit_new_round2__0028 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0009 - Train Accuracy: 0.0795 - Train Wermet: 8.3074 - Validation Loss: 0.5641 - Validation Accuracy: 0.0768 - Validation Wermet: 7.1747 - Epoch: 27 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | | 0.0009 | 0.0795 | 8.3074 | 0.5641 | 0.0768 | 7.1747 | 27 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

jstoone/whisper-tiny-en

jstoone

2023-08-13T18:39:23Z

85

0

transformers

[ "transformers", "pytorch", "whisper", "automatic-speech-recognition", "generated_from_trainer", "dataset:PolyAI/minds14", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T13:56:01Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - PolyAI/minds14 metrics: - wer model-index: - name: whisper-tiny-en results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: PolyAI/minds14 type: PolyAI/minds14 config: en-US split: train args: en-US metrics: - name: Wer type: wer value: 0.35723514211886304 ---  # whisper-tiny-en This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set: - Loss: 0.9035 - Wer Ortho: 0.354643 - Wer: 0.357235 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| | 0.0005 | 35.71 | 500 | 0.7515 | 36.1373 | 36.4341 | | 0.0002 | 71.43 | 1000 | 0.8095 | 36.4065 | 36.5633 | | 0.0001 | 107.14 | 1500 | 0.8421 | 36.4738 | 36.6925 | | 0.0001 | 142.86 | 2000 | 0.8636 | 35.4643 | 35.5943 | | 0.0001 | 178.57 | 2500 | 0.8822 | 35.6662 | 35.7235 | | 0.0 | 214.29 | 3000 | 0.8931 | 35.4643 | 35.7235 | | 0.0 | 250.0 | 3500 | 0.9013 | 35.4643 | 35.7235 | | 0.0 | 285.71 | 4000 | 0.9035 | 35.4643 | 35.7235 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

KenmaKIN101/LenKagamineV4_250epochs

KenmaKIN101

2023-08-13T18:38:53Z

0

null

[ "license:openrail", "region:us" ]

null

2023-08-13T18:32:40Z

--- license: openrail --- This model is for fair use only. Also, it may sound a bit bad because this was my first model (because I discarded the Miku model).

bigmorning/whisper_charsplit_new_round2__0027

bigmorning

2023-08-13T18:37:27Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:37:20Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0027 results: [] ---  # whisper_charsplit_new_round2__0027 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.4237 - Validation Loss: 0.5710 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4035 - Epoch: 26 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | | 0.0012 | 0.0795 | 7.9451 | 0.5615 | 0.0768 | 7.0907 | 24 | | 0.0025 | 0.0795 | 8.1065 | 0.5619 | 0.0768 | 7.7020 | 25 | | 0.0011 | 0.0795 | 8.4237 | 0.5710 | 0.0768 | 7.4035 | 26 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_prompt_tuning_500_10_3000_8_e-1_s108_v4_l5_v50

KingKazma

2023-08-13T18:34:32Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:35:50Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KemalHal/whisper-base-bosnian-google

KemalHal

2023-08-13T18:29:56Z

78

0

transformers

[ "transformers", "pytorch", "whisper", "automatic-speech-recognition", "bs", "dataset:google/fleurs", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-11T15:15:09Z

--- datasets: - google/fleurs language: - bs metrics: - wer pipeline_tag: automatic-speech-recognition --- Ovaj model je Fine-Tuned verzija Whisper AI base modela na Bosanskom jeziku. Dataset koristen je google/fleurs bs_ba.

dn118/epicnegative

dn118

2023-08-13T18:29:16Z

0

null

[ "region:us" ]

null

2023-08-13T18:25:53Z

all credits go to epinikion https://civitai.com/user/epinikion reuploaded from civit.ai, source: https://civitai.com/models/89484?modelVersionId=95263

SaudxInu/Reinforce-CartPole-v1

SaudxInu

2023-08-13T18:28:55Z

0

null

[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]

reinforcement-learning

2023-08-13T18:05:19Z

--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinforce-CartPole-v1 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 500.00 +/- 0.00 name: mean_reward verified: false --- # **Reinforce** Agent playing **CartPole-v1** This is a trained model of a **Reinforce** agent playing **CartPole-v1** . To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction

josephamess/llama-2-7b-ExtraData-v2

josephamess

2023-08-13T18:24:51Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:36:15Z

--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0024

bigmorning

2023-08-13T18:24:25Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:24:17Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0024 results: [] ---  # whisper_charsplit_new_round2__0024 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0008 - Train Accuracy: 0.0795 - Train Wermet: 8.3246 - Validation Loss: 0.5620 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4475 - Epoch: 23 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | | 0.0008 | 0.0795 | 8.3246 | 0.5620 | 0.0768 | 7.4475 | 23 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

charliezjw/t2

charliezjw

2023-08-13T18:20:49Z

0

1

diffusers

[ "diffusers", "tensorboard", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "lora", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0", "license:openrail++", "region:us" ]

text-to-image

2023-08-13T17:48:17Z

--- license: openrail++ base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: a photo of sks dog tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - lora inference: true --- # LoRA DreamBooth - charliezjw/t2 These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. ![img_0](./image_0.png) ![img_1](./image_1.png) ![img_2](./image_2.png) ![img_3](./image_3.png) LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

bigmorning/whisper_charsplit_new_round2__0023

bigmorning

2023-08-13T18:20:01Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:19:52Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0023 results: [] ---  # whisper_charsplit_new_round2__0023 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0007 - Train Accuracy: 0.0795 - Train Wermet: 8.6456 - Validation Loss: 0.5543 - Validation Accuracy: 0.0768 - Validation Wermet: 7.4625 - Epoch: 22 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | | 0.0020 | 0.0795 | 8.6599 | 0.5612 | 0.0767 | 7.7369 | 21 | | 0.0007 | 0.0795 | 8.6456 | 0.5543 | 0.0768 | 7.4625 | 22 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v100

KingKazma

2023-08-13T18:19:07Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T18:19:06Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

RAVIKUMAR/ddpm-butterflies-128

RAVIKUMAR

2023-08-13T18:16:08Z

5

0

diffusers

[ "diffusers", "tensorboard", "en", "dataset:huggan/smithsonian_butterflies_subset", "license:apache-2.0", "diffusers:DDPMPipeline", "region:us" ]

null

2023-08-13T18:09:17Z

--- language: en license: apache-2.0 library_name: diffusers tags: [] datasets: huggan/smithsonian_butterflies_subset metrics: [] ---  # ddpm-butterflies-128 ## Model description This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library on the `huggan/smithsonian_butterflies_subset` dataset. ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training data [TODO: describe the data used to train the model] ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 16 - eval_batch_size: 16 - gradient_accumulation_steps: 1 - optimizer: AdamW with betas=(None, None), weight_decay=None and epsilon=None - lr_scheduler: None - lr_warmup_steps: 500 - ema_inv_gamma: None - ema_inv_gamma: None - ema_inv_gamma: None - mixed_precision: fp16 ### Training results 📈 [TensorBoard logs](https://huggingface.co/HuggingFace7/ddpm-butterflies-128/tensorboard?#scalars) license: mit ---

bigmorning/whisper_charsplit_new_round2__0021

bigmorning

2023-08-13T18:11:16Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:11:08Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0021 results: [] ---  # whisper_charsplit_new_round2__0021 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0058 - Train Accuracy: 0.0794 - Train Wermet: 8.8460 - Validation Loss: 0.5706 - Validation Accuracy: 0.0766 - Validation Wermet: 7.4342 - Epoch: 20 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | | 0.0058 | 0.0794 | 8.8460 | 0.5706 | 0.0766 | 7.4342 | 20 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v100

KingKazma

2023-08-13T18:10:32Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T18:10:31Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0020

bigmorning

2023-08-13T18:06:52Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T18:06:44Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0020 results: [] ---  # whisper_charsplit_new_round2__0020 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0014 - Train Accuracy: 0.0795 - Train Wermet: 8.7153 - Validation Loss: 0.5804 - Validation Accuracy: 0.0765 - Validation Wermet: 7.8654 - Epoch: 19 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | | 0.0004 | 0.0795 | 9.1734 | 0.5607 | 0.0768 | 8.0252 | 17 | | 0.0003 | 0.0795 | 9.0084 | 0.5571 | 0.0769 | 8.1563 | 18 | | 0.0014 | 0.0795 | 8.7153 | 0.5804 | 0.0765 | 7.8654 | 19 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v100

KingKazma

2023-08-13T18:01:56Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T18:01:55Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0017

bigmorning

2023-08-13T17:53:35Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:53:25Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0017 results: [] ---  # whisper_charsplit_new_round2__0017 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.0553 - Validation Loss: 0.5620 - Validation Accuracy: 0.0768 - Validation Wermet: 8.5020 - Epoch: 16 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | | 0.0012 | 0.0795 | 8.8259 | 0.5563 | 0.0768 | 8.2647 | 15 | | 0.0005 | 0.0795 | 9.0553 | 0.5620 | 0.0768 | 8.5020 | 16 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e5_s55555_v4_l4_v100

KingKazma

2023-08-13T17:53:21Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:53:20Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

YassineBenlaria/tamasheq-3e-5

YassineBenlaria

2023-08-13T17:52:52Z

7

0

transformers

[ "transformers", "pytorch", "tensorboard", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "base_model:jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "base_model:finetune:jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-12T10:54:16Z

--- license: apache-2.0 base_model: jonatasgrosman/wav2vec2-large-xlsr-53-arabic tags: - generated_from_trainer metrics: - wer model-index: - name: tamasheq-3e-5 results: [] ---  # tamasheq-3e-5 This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-arabic](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-arabic) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6463 - Wer: 0.7256 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 16.1726 | 5.8 | 200 | 3.5775 | 1.0 | | 3.2056 | 11.59 | 400 | 3.0132 | 1.0 | | 2.3808 | 17.39 | 600 | 1.0264 | 0.8069 | | 0.6535 | 23.19 | 800 | 0.6919 | 0.7388 | | 0.4426 | 28.99 | 1000 | 0.6463 | 0.7256 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

Icebear-AI/Llama-2-13b-chat-arabic-lora

Icebear-AI

2023-08-13T17:52:46Z

0

7

null

[ "en", "ar", "dataset:Yasbok/Alpaca_arabic_instruct", "license:apache-2.0", "region:us" ]

null

2023-08-13T17:49:32Z

--- license: apache-2.0 datasets: - Yasbok/Alpaca_arabic_instruct language: - en - ar --- This model is an LoRA adapter file from finetuned Llama-2-13b-chat-hf model. This is an experimental model. This model is presented by IceBear-AI. To run it, you need to: - Agree with Meta's agreements to download the Llama-2-13b-chat-hf model from here: https://huggingface.co/meta-llama/Llama-2-13b-chat-hf - Clone this repository - Clone the Alpaca-LoRA repository from here: https://github.com/tloen/alpaca-lora - Use this command to run it: -python generate.py \ --load_8bit \ --base_model 'PATH_TO_YOUR_LOCAL_LLAMA_2_7B_CHAT_HF' \ --lora_weights 'PATH_TO_YOUR_LOCAL_FILE_OF_THIS_MODEL' You must agree with Meta/Llama-2's agreements to use this model. If you would like to contact us, please don't hesitate to email to icebearai@163.com.

bigmorning/whisper_charsplit_new_round2__0015

bigmorning

2023-08-13T17:44:49Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:44:29Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0015 results: [] ---  # whisper_charsplit_new_round2__0015 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0038 - Train Accuracy: 0.0795 - Train Wermet: 8.7270 - Validation Loss: 0.5605 - Validation Accuracy: 0.0767 - Validation Wermet: 7.7098 - Epoch: 14 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | | 0.0038 | 0.0795 | 8.7270 | 0.5605 | 0.0767 | 7.7098 | 14 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e9_s108_v4_l4_v100

KingKazma

2023-08-13T17:42:02Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:41:58Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0014

bigmorning

2023-08-13T17:40:14Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:40:08Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0014 results: [] ---  # whisper_charsplit_new_round2__0014 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0037 - Train Accuracy: 0.0795 - Train Wermet: 9.2838 - Validation Loss: 0.5751 - Validation Accuracy: 0.0765 - Validation Wermet: 7.4189 - Epoch: 13 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | | 0.0037 | 0.0795 | 9.2838 | 0.5751 | 0.0765 | 7.4189 | 13 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e8_s55555_v4_l4_r2

KingKazma

2023-08-13T17:39:00Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:38:59Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0013

bigmorning

2023-08-13T17:35:54Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:35:47Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0013 results: [] ---  # whisper_charsplit_new_round2__0013 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.2292 - Validation Loss: 0.5687 - Validation Accuracy: 0.0767 - Validation Wermet: 8.5576 - Epoch: 12 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | | 0.0003 | 0.0795 | 9.3340 | 0.5584 | 0.0768 | 8.1322 | 11 | | 0.0005 | 0.0795 | 9.2292 | 0.5687 | 0.0767 | 8.5576 | 12 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e8_s108_v4_l4_v100

KingKazma

2023-08-13T17:33:23Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:33:19Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e2_s55555_v4_l4_v100

KingKazma

2023-08-13T17:27:47Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:27:45Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0011

bigmorning

2023-08-13T17:27:17Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:27:08Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0011 results: [] ---  # whisper_charsplit_new_round2__0011 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.3749 - Validation Loss: 0.5552 - Validation Accuracy: 0.0768 - Validation Wermet: 8.0800 - Epoch: 10 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | | 0.0005 | 0.0795 | 9.3749 | 0.5552 | 0.0768 | 8.0800 | 10 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_round2__0010

bigmorning

2023-08-13T17:22:53Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:22:45Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0010 results: [] ---  # whisper_charsplit_new_round2__0010 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.9730 - Validation Loss: 0.5605 - Validation Accuracy: 0.0767 - Validation Wermet: 8.3958 - Epoch: 9 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | | 0.0011 | 0.0795 | 8.9730 | 0.5605 | 0.0767 | 8.3958 | 9 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_lora_500_10_3000_8_e8_s55555_v4_l4_r4

KingKazma

2023-08-13T17:22:22Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:22:20Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0009

bigmorning

2023-08-13T17:18:33Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:18:25Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0009 results: [] ---  # whisper_charsplit_new_round2__0009 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0031 - Train Accuracy: 0.0795 - Train Wermet: 9.2135 - Validation Loss: 0.5636 - Validation Accuracy: 0.0766 - Validation Wermet: 8.2384 - Epoch: 8 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | | 0.0031 | 0.0795 | 9.2135 | 0.5636 | 0.0766 | 8.2384 | 8 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e5_s55555_v4_l4_r2

KingKazma

2023-08-13T17:16:58Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:16:56Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0008

bigmorning

2023-08-13T17:14:11Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:14:03Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0008 results: [] ---  # whisper_charsplit_new_round2__0008 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0037 - Train Accuracy: 0.0795 - Train Wermet: 9.3428 - Validation Loss: 0.5717 - Validation Accuracy: 0.0764 - Validation Wermet: 8.2631 - Epoch: 7 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | | 0.0009 | 0.0795 | 8.7510 | 0.5642 | 0.0766 | 7.9083 | 6 | | 0.0037 | 0.0795 | 9.3428 | 0.5717 | 0.0764 | 8.2631 | 7 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e0_s55555_v4_l4_v100

KingKazma

2023-08-13T17:10:36Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:10:35Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e4_s55555_v4_l4_r2

KingKazma

2023-08-13T17:09:37Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:09:36Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e6_s55555_v4_l4_r4

KingKazma

2023-08-13T17:08:38Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:08:36Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0006

bigmorning

2023-08-13T17:05:24Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:05:17Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0006 results: [] ---  # whisper_charsplit_new_round2__0006 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0012 - Train Accuracy: 0.0795 - Train Wermet: 8.8862 - Validation Loss: 0.5667 - Validation Accuracy: 0.0767 - Validation Wermet: 8.2913 - Epoch: 5 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | | 0.0012 | 0.0795 | 8.8862 | 0.5667 | 0.0767 | 8.2913 | 5 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

jiaqixuac/controlnet_training

jiaqixuac

2023-08-13T17:05:05Z

0

diffusers

[ "diffusers", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "controlnet", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2023-08-13T14:21:44Z

--- license: creativeml-openrail-m base_model: runwayml/stable-diffusion-v1-5 tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet inference: true --- # controlnet-jiaqixuac/controlnet_training These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: red circle with blue background ![images_0)](./images_0.png) prompt: cyan circle with brown floral background ![images_1)](./images_1.png)

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e-1_s55555_v4_l4_v100

KingKazma

2023-08-13T17:02:02Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:58:53Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e5_s55555_v4_l4_r4

KingKazma

2023-08-13T17:01:46Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T17:01:44Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0005

bigmorning

2023-08-13T17:00:54Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T17:00:46Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0005 results: [] ---  # whisper_charsplit_new_round2__0005 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0011 - Train Accuracy: 0.0795 - Train Wermet: 8.9053 - Validation Loss: 0.5609 - Validation Accuracy: 0.0767 - Validation Wermet: 7.5155 - Epoch: 4 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | | 0.0011 | 0.0795 | 8.9053 | 0.5609 | 0.0767 | 7.5155 | 4 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e4_s108_v4_l4_v100

KingKazma

2023-08-13T16:58:48Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:58:44Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_round2__0004

bigmorning

2023-08-13T16:56:30Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:56:23Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_round2__0004 results: [] ---  # whisper_charsplit_new_round2__0004 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 8.9450 - Validation Loss: 0.5623 - Validation Accuracy: 0.0766 - Validation Wermet: 7.7117 - Epoch: 3 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.0010 | 0.0795 | 8.7507 | 0.5575 | 0.0767 | 7.6778 | 0 | | 0.0013 | 0.0795 | 8.9468 | 0.5652 | 0.0766 | 8.3360 | 1 | | 0.0025 | 0.0795 | 8.7338 | 0.5673 | 0.0765 | 8.3770 | 2 | | 0.0019 | 0.0795 | 8.9450 | 0.5623 | 0.0766 | 7.7117 | 3 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e2_s55555_v4_l4_r2

KingKazma

2023-08-13T16:54:56Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:54:53Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

jsnbuchanan/segformer-b0-scene-parse-150

jsnbuchanan

2023-08-13T16:50:58Z

31

0

transformers

[ "transformers", "pytorch", "segformer", "generated_from_trainer", "dataset:scene_parse_150", "base_model:nvidia/mit-b0", "base_model:finetune:nvidia/mit-b0", "license:other", "endpoints_compatible", "region:us" ]

null

2023-08-01T20:37:16Z

--- license: other base_model: nvidia/mit-b0 tags: - generated_from_trainer datasets: - scene_parse_150 model-index: - name: segformer-b0-scene-parse-150 results: [] ---  # segformer-b0-scene-parse-150 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset. It achieves the following results on the evaluation set: - Loss: 4.5716 - Mean Iou: 0.0039 - Mean Accuracy: 0.0219 - Overall Accuracy: 0.1398 - Per Category Iou: [0.1424604255351693, 0.0028172808510882213, 0.009342676914231785, 0.0, 0.0, 0.02331811292704824, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] - Per Category Accuracy: [0.9514506078251098, 0.0028769356391743226, 0.00966095515858549, 0.0, 0.0, 0.045009037210949, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 6e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | 4.8633 | 1.0 | 20 | 4.8626 | 0.0009 | 0.0023 | 0.0067 | [0.0, 0.0004889263991152761, 0.0, 0.0, 0.0, 0.0, 0.03284478144986514, 0.0, 0.0, 0.014472940861907617, 0.0, 0.0009606283639651349, 0.0, 0.001090056864633105, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0033905507210453163, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.011123126834543489, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan] | [0.0, 0.0004916838121884905, 0.0, 0.0, 0.0, 0.0, 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nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | | 4.3876 | 4.0 | 80 | 4.1595 | 0.0032 | 0.0120 | 0.0594 | [0.07854437258265586, 0.002560575118273506, 0.0, 0.0, 0.0, 0.001192829675600377, 0.0810610478529872, 0.0, 0.0, 0.014937473673721733, 0.0, 0.0, 0.0, 0.005779474740910093, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 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nan, nan, nan, nan, nan, 0.0, nan] | | 3.6357 | 6.0 | 120 | 3.8936 | 0.0031 | 0.0183 | 0.1193 | [0.13782355615369993, 0.00012947106753210882, 0.0020724837921139334, 0.0, 0.0, 0.002555414284014255, 0.00625454345947577, 0.0, 0.0, 0.0021069049880189433, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | [0.8250104993132882, 0.0001317010211219171, 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nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | | 2.7618 | 48.0 | 960 | 5.0946 | 0.0038 | 0.0218 | 0.1373 | [0.1426949704126623, 0.0032438673758399044, 0.0051523797709134515, 0.0, 0.0, 0.023948251838033993, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | [0.93417498098773, 0.0033217924216305756, 0.005241313553380633, 0.0, 0.0, 0.05908658952428867, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | | 3.7284 | 49.0 | 980 | 4.0830 | 0.0043 | 0.0221 | 0.1373 | [0.14283896315255537, 0.0034238556212341873, 0.024018439121225456, 0.0, 0.0, 0.029172219275206687, 0.0002549698559831555, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | [0.9045640798628847, 0.0035091005405595245, 0.026329958776185537, 0.0, 0.0, 0.08402742840106583, 0.00025786487880350697, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | | 3.6351 | 50.0 | 1000 | 4.5716 | 0.0039 | 0.0219 | 0.1398 | [0.1424604255351693, 0.0028172808510882213, 0.009342676914231785, 0.0, 0.0, 0.02331811292704824, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | [0.9514506078251098, 0.0028769356391743226, 0.00966095515858549, 0.0, 0.0, 0.045009037210949, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | ### Framework versions - Transformers 4.31.0 - Pytorch 2.1.0.dev20230812 - Datasets 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e3_s108_v4_l4_v100

KingKazma

2023-08-13T16:50:09Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:50:05Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

LBR47/speecht5_finetuned_voxpopuli_nl

LBR47

2023-08-13T16:49:06Z

82

0

transformers

[ "transformers", "pytorch", "speecht5", "text-to-audio", "text-to-speech", "dataset:voxpopuli", "endpoints_compatible", "region:us" ]

text-to-speech

2023-08-13T16:41:15Z

--- base_model: speechT5 tags: - text-to-speech datasets: - voxpopuli model-index: - name: speecht5_finetuned_voxpopuli_nl results: [] ---  # speecht5_finetuned_voxpopuli_nl This model is a fine-tuned version of [speechT5](https://huggingface.co/speechT5) on the voxpopuli dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 4 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 ### Framework versions - Transformers 4.31.0 - Pytorch 1.12.1+cpu - Datasets 2.13.1 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e8_s108_v4_l4_v100

KingKazma

2023-08-13T16:47:03Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:47:02Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e1_s55555_v4_l4_r4

KingKazma

2023-08-13T16:34:17Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:34:15Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e1_s108_v4_l4_v100

KingKazma

2023-08-13T16:32:55Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:32:49Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

digicazter/wav2vec2-base-timit-demo-google-colab

digicazter

2023-08-13T16:32:43Z

105

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "base_model:facebook/wav2vec2-base", "base_model:finetune:facebook/wav2vec2-base", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-07T03:20:25Z

--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-base-timit-demo-google-colab results: [] ---  # wav2vec2-base-timit-demo-google-colab This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.0392 - Wer: 1.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 400 - num_epochs: 150 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:---:| | 5.2993 | 8.0 | 200 | 3.0327 | 1.0 | | 3.0806 | 16.0 | 400 | 3.0476 | 1.0 | | 3.0219 | 24.0 | 600 | 3.0472 | 1.0 | | 3.0179 | 32.0 | 800 | 3.0435 | 1.0 | | 3.0157 | 40.0 | 1000 | 3.0546 | 1.0 | | 3.0146 | 48.0 | 1200 | 3.0484 | 1.0 | | 3.0139 | 56.0 | 1400 | 3.0344 | 1.0 | | 3.0118 | 64.0 | 1600 | 3.0351 | 1.0 | | 3.0114 | 72.0 | 1800 | 3.0559 | 1.0 | | 3.0114 | 80.0 | 2000 | 3.0526 | 1.0 | | 3.0108 | 88.0 | 2200 | 3.0417 | 1.0 | | 3.0092 | 96.0 | 2400 | 3.0629 | 1.0 | | 3.0089 | 104.0 | 2600 | 3.0352 | 1.0 | | 3.0083 | 112.0 | 2800 | 3.0503 | 1.0 | | 3.0078 | 120.0 | 3000 | 3.0529 | 1.0 | | 3.0072 | 128.0 | 3200 | 3.0378 | 1.0 | | 3.0068 | 136.0 | 3400 | 3.0481 | 1.0 | | 3.0063 | 144.0 | 3600 | 3.0392 | 1.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.3 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e9_s108_v4_l4_r2

KingKazma

2023-08-13T16:22:59Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:22:58Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0098

bigmorning

2023-08-13T16:22:52Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:22:44Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0098 results: [] ---  # whisper_charsplit_new_0098 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0044 - Train Accuracy: 0.0794 - Train Wermet: 8.8948 - Validation Loss: 0.5589 - Validation Accuracy: 0.0765 - Validation Wermet: 7.4085 - Epoch: 97 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | | 0.0029 | 0.0795 | 10.1412 | 0.5666 | 0.0764 | 9.0822 | 91 | | 0.0042 | 0.0795 | 9.5603 | 0.5582 | 0.0765 | 7.6837 | 92 | | 0.0015 | 0.0795 | 9.4004 | 0.5495 | 0.0766 | 7.7859 | 93 | | 0.0008 | 0.0795 | 9.5417 | 0.5503 | 0.0767 | 7.8876 | 94 | | 0.0005 | 0.0795 | 9.3473 | 0.5590 | 0.0766 | 7.8967 | 95 | | 0.0016 | 0.0795 | 9.1740 | 0.5746 | 0.0765 | 7.8469 | 96 | | 0.0044 | 0.0794 | 8.8948 | 0.5589 | 0.0765 | 7.4085 | 97 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_prompt_tuning_500_10_3000_5_e-1_s108_v4_l4_v100

KingKazma

2023-08-13T16:15:39Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:15:36Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0096

bigmorning

2023-08-13T16:14:08Z

60

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:14:00Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0096 results: [] ---  # whisper_charsplit_new_0096 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0005 - Train Accuracy: 0.0795 - Train Wermet: 9.3473 - Validation Loss: 0.5590 - Validation Accuracy: 0.0766 - Validation Wermet: 7.8967 - Epoch: 95 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | | 0.0029 | 0.0795 | 10.1412 | 0.5666 | 0.0764 | 9.0822 | 91 | | 0.0042 | 0.0795 | 9.5603 | 0.5582 | 0.0765 | 7.6837 | 92 | | 0.0015 | 0.0795 | 9.4004 | 0.5495 | 0.0766 | 7.7859 | 93 | | 0.0008 | 0.0795 | 9.5417 | 0.5503 | 0.0767 | 7.8876 | 94 | | 0.0005 | 0.0795 | 9.3473 | 0.5590 | 0.0766 | 7.8967 | 95 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_lora_500_10_3000_8_e9_s108_v4_l4_r4

KingKazma

2023-08-13T16:13:40Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:13:38Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e4_s108_v4_l4_v100

KingKazma

2023-08-13T16:12:42Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:12:40Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0095

bigmorning

2023-08-13T16:09:46Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:09:40Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0095 results: [] ---  # whisper_charsplit_new_0095 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0008 - Train Accuracy: 0.0795 - Train Wermet: 9.5417 - Validation Loss: 0.5503 - Validation Accuracy: 0.0767 - Validation Wermet: 7.8876 - Epoch: 94 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | | 0.0029 | 0.0795 | 10.1412 | 0.5666 | 0.0764 | 9.0822 | 91 | | 0.0042 | 0.0795 | 9.5603 | 0.5582 | 0.0765 | 7.6837 | 92 | | 0.0015 | 0.0795 | 9.4004 | 0.5495 | 0.0766 | 7.7859 | 93 | | 0.0008 | 0.0795 | 9.5417 | 0.5503 | 0.0767 | 7.8876 | 94 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e7_s108_v4_l4_r2

KingKazma

2023-08-13T16:08:19Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:08:17Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

DHEIVER/Brain_Tumor_Classification

DHEIVER

2023-08-13T16:06:23Z

182

0

transformers

[ "transformers", "pytorch", "swin", "image-classification", "generated_from_trainer", "dataset:imagefolder", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2023-08-13T16:04:30Z

--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy - f1 - recall - precision model-index: - name: Brain_Tumor_Classification results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9646761984861227 - name: F1 type: f1 value: 0.9646761984861227 - name: Recall type: recall value: 0.9646761984861227 - name: Precision type: precision value: 0.9646761984861227 ---  # Brain_Tumor_Classification This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.1012 - Accuracy: 0.9647 - F1: 0.9647 - Recall: 0.9647 - Precision: 0.9647 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| | 0.4856 | 0.99 | 83 | 0.3771 | 0.8444 | 0.8444 | 0.8444 | 0.8444 | | 0.3495 | 1.99 | 166 | 0.2608 | 0.8949 | 0.8949 | 0.8949 | 0.8949 | | 0.252 | 2.99 | 249 | 0.1445 | 0.9487 | 0.9487 | 0.9487 | 0.9487 | | 0.2364 | 3.99 | 332 | 0.1029 | 0.9588 | 0.9588 | 0.9588 | 0.9588 | | 0.2178 | 4.99 | 415 | 0.1012 | 0.9647 | 0.9647 | 0.9647 | 0.9647 | ### Framework versions - Transformers 4.23.1 - Pytorch 1.12.1 - Datasets 2.6.1 - Tokenizers 0.13.1

bigmorning/whisper_charsplit_new_0094

bigmorning

2023-08-13T16:05:30Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:05:24Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0094 results: [] ---  # whisper_charsplit_new_0094 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0015 - Train Accuracy: 0.0795 - Train Wermet: 9.4004 - Validation Loss: 0.5495 - Validation Accuracy: 0.0766 - Validation Wermet: 7.7859 - Epoch: 93 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | | 0.0029 | 0.0795 | 10.1412 | 0.5666 | 0.0764 | 9.0822 | 91 | | 0.0042 | 0.0795 | 9.5603 | 0.5582 | 0.0765 | 7.6837 | 92 | | 0.0015 | 0.0795 | 9.4004 | 0.5495 | 0.0766 | 7.7859 | 93 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

evanyin/openai-whisper-tiny-LORA-colab-test

evanyin

2023-08-13T16:05:21Z

0

peft

[ "peft", "region:us" ]

null

2023-08-08T15:32:52Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e3_s108_v4_l4_v100

KingKazma

2023-08-13T16:04:06Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:04:05Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

udayGay/resume_model

udayGay

2023-08-13T16:03:19Z

3

0

transformers

[ "transformers", "tf", "distilbert", "text-classification", "generated_from_keras_callback", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2023-08-12T16:11:53Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: udayGay/resume_model results: [] ---  # udayGay/resume_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 1.1040 - Validation Loss: 1.4298 - Train Accuracy: 0.6640 - Train Precision: 0.5589 - Train Recall: 0.5938 - Train F1: 0.5692 - Epoch: 29 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1470, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch | |:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:| | 3.1654 | 3.1440 | 0.0402 | 0.0017 | 0.0417 | 0.0033 | 0 | | 3.1553 | 3.1474 | 0.0282 | 0.0012 | 0.0417 | 0.0023 | 1 | | 3.1208 | 3.0528 | 0.0805 | 0.0147 | 0.0812 | 0.0225 | 2 | | 2.9896 | 2.8784 | 0.1469 | 0.0746 | 0.1384 | 0.0825 | 3 | | 2.6886 | 2.5739 | 0.3300 | 0.2207 | 0.3033 | 0.2182 | 4 | | 2.2855 | 2.1620 | 0.4547 | 0.3432 | 0.4138 | 0.3395 | 5 | | 1.9018 | 1.9030 | 0.5151 | 0.4141 | 0.4679 | 0.4118 | 6 | | 1.6218 | 1.7029 | 0.5795 | 0.4872 | 0.5205 | 0.4854 | 7 | | 1.4058 | 1.5916 | 0.6217 | 0.5261 | 0.5595 | 0.5278 | 8 | | 1.2705 | 1.4954 | 0.6479 | 0.5457 | 0.5815 | 0.5557 | 9 | | 1.1692 | 1.4469 | 0.6600 | 0.5548 | 0.5896 | 0.5643 | 10 | | 1.1179 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 11 | | 1.1162 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 12 | | 1.1109 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 13 | | 1.1142 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 14 | | 1.1095 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 15 | | 1.1108 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 16 | | 1.1133 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 17 | | 1.1132 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 18 | | 1.1064 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 19 | | 1.1098 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 20 | | 1.1029 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 21 | | 1.1055 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 22 | | 1.1125 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 23 | | 1.1081 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 24 | | 1.1125 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 25 | | 1.1130 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 26 | | 1.1101 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 27 | | 1.1134 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 28 | | 1.1040 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 29 | ### Framework versions - Transformers 4.31.0 - TensorFlow 2.12.0 - Datasets 2.14.4 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0093

bigmorning

2023-08-13T16:01:10Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T16:01:02Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0093 results: [] ---  # whisper_charsplit_new_0093 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0042 - Train Accuracy: 0.0795 - Train Wermet: 9.5603 - Validation Loss: 0.5582 - Validation Accuracy: 0.0765 - Validation Wermet: 7.6837 - Epoch: 92 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | | 0.0029 | 0.0795 | 10.1412 | 0.5666 | 0.0764 | 9.0822 | 91 | | 0.0042 | 0.0795 | 9.5603 | 0.5582 | 0.0765 | 7.6837 | 92 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e6_s108_v4_l4_r2

KingKazma

2023-08-13T16:00:59Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T16:00:57Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e7_s108_v4_l4_r4

KingKazma

2023-08-13T15:59:56Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:59:53Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

Sakil/llama2_finetuned_medical_assistant

Sakil

2023-08-13T15:59:29Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:39:26Z

--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float16 ### Framework versions - PEFT 0.4.0

fathyshalab/mdcsi-unterhaltung-kultur-freizeit-setfit

fathyshalab

2023-08-13T15:56:44Z

5

0

sentence-transformers

[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]

text-classification

2023-08-13T15:55:53Z

--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpyb2_zis8\fathyshalab\mdcsi-unterhaltung-kultur-freizeit-setfit This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage To use this model for inference, first install the SetFit library: ```bash python -m pip install setfit ``` You can then run inference as follows: ```python from setfit import SetFitModel # Download from Hub and run inference model = SetFitModel.from_pretrained("C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpyb2_zis8\fathyshalab\mdcsi-unterhaltung-kultur-freizeit-setfit") # Run inference preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"]) ``` ## BibTeX entry and citation info ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e2_s108_v4_l4_v100

KingKazma

2023-08-13T15:55:31Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:55:30Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e5_s108_v4_l4_r2

KingKazma

2023-08-13T15:53:39Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:53:37Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e6_s108_v4_l4_r4

KingKazma

2023-08-13T15:53:04Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:53:02Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0091

bigmorning

2023-08-13T15:52:18Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T15:52:10Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0091 results: [] ---  # whisper_charsplit_new_0091 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0006 - Train Accuracy: 0.0795 - Train Wermet: 10.2538 - Validation Loss: 0.5541 - Validation Accuracy: 0.0766 - Validation Wermet: 8.7676 - Epoch: 90 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | | 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 | | 0.0006 | 0.0795 | 10.2538 | 0.5541 | 0.0766 | 8.7676 | 90 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_p_tuning_500_10_3000_8_e1_s108_v4_l4_v100

KingKazma

2023-08-13T15:46:55Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:46:54Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e4_s108_v4_l4_r2

KingKazma

2023-08-13T15:46:18Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:46:17Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

KingKazma/xsum_gpt2_lora_500_10_3000_8_e5_s108_v4_l4_r4

KingKazma

2023-08-13T15:46:12Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:46:10Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0089

bigmorning

2023-08-13T15:43:30Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T15:43:22Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0089 results: [] ---  # whisper_charsplit_new_0089 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0019 - Train Accuracy: 0.0795 - Train Wermet: 10.3176 - Validation Loss: 0.5492 - Validation Accuracy: 0.0766 - Validation Wermet: 8.5812 - Epoch: 88 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | | 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_gpt2_lora_500_10_3000_8_e4_s108_v4_l4_r4

KingKazma

2023-08-13T15:39:20Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:39:18Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0088

bigmorning

2023-08-13T15:39:10Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T15:39:03Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0088 results: [] ---  # whisper_charsplit_new_0088 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0038 - Train Accuracy: 0.0795 - Train Wermet: 10.1430 - Validation Loss: 0.5538 - Validation Accuracy: 0.0765 - Validation Wermet: 9.1635 - Epoch: 87 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | | 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_gpt2_lora_500_10_3000_8_e3_s108_v4_l4_r2

KingKazma

2023-08-13T15:38:58Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T15:38:56Z

--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0087

bigmorning

2023-08-13T15:34:44Z

59

0

transformers

[ "transformers", "tf", "whisper", "automatic-speech-recognition", "generated_from_keras_callback", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2023-08-13T15:34:36Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0087 results: [] ---  # whisper_charsplit_new_0087 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0034 - Train Accuracy: 0.0795 - Train Wermet: 10.5048 - Validation Loss: 0.5578 - Validation Accuracy: 0.0764 - Validation Wermet: 8.9920 - Epoch: 86 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 | | 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 | | 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 | | 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 | | 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 | | 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 | | 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 | | 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 | | 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 | | 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 | | 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 | | 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 | | 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 | | 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 | | 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 | | 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 | | 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 | | 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 | | 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 | | 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 | | 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 | | 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 | | 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 | | 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 | | 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 | | 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 | | 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 | | 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 | | 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 | | 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 | | 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 | | 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 | | 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 | | 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 | | 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 | | 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 | | 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 | | 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 | | 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 | | 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 | | 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 | | 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 | | 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 | | 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 | | 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 | | 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 | | 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 | | 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 | | 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 | | 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 | | 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 | | 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 | | 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 | | 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 | | 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 | | 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 | | 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 | | 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 | | 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 | | 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 | | 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 | | 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 | | 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 | | 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 | | 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 | | 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 | | 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 | | 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 | | 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 | | 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 | | 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 | | 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 | | 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 | | 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 | | 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 | | 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 | | 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 | | 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 | | 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 | | 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 | | 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 | | 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 | | 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 | | 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 | | 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 | | 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 | | 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3