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 2025-09-02 12:32:32	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 534 values	tags listlengths 1 4.05k	pipeline_tag stringclasses 55 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-09-02 12:31:20	card stringlengths 11 1.01M
bigmorning/whisper_charsplit_new_0072	bigmorning	2023-08-13T14:29:00Z	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	2023-08-13T14:28:53Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0072 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_0072 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: 10.2545 - Validation Loss: 0.5315 - Validation Accuracy: 0.0765 - Validation Wermet: 9.0617 - Epoch: 71 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e9_s55555_v4_l4_v50	KingKazma	2023-08-13T14:28:55Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:28:51Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v50	KingKazma	2023-08-13T14:25:39Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:25:36Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e-1_s108_v4_l6_v20_manual	KingKazma	2023-08-13T14:25:35Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:25:33Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e9_s55555_v4_l4_v100	KingKazma	2023-08-13T14:24:41Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:24:40Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e10_s108_v4_l6_v20	KingKazma	2023-08-13T14:24:22Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:24:20Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
nightdude/config_4	nightdude	2023-08-13T14:23:39Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:23:30Z	--- 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: True - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.4.0.dev0
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e8_s108_v4_l4_v20	KingKazma	2023-08-13T14:23:00Z	2	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:22:59Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v50	KingKazma	2023-08-13T14:22:22Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:22:18Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e9_s108_v4_l6_v20	KingKazma	2023-08-13T14:21:42Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:21:41Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v100	KingKazma	2023-08-13T14:21:41Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:21:40Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e7_s108_v4_l4_v20	KingKazma	2023-08-13T14:19:53Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:19:52Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v50	KingKazma	2023-08-13T14:19:03Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:18:59Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
fathyshalab/mdcsi-versicherungen-recht-setfit	fathyshalab	2023-08-13T14:19:01Z	6	0	sentence-transformers	[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]	text-classification	2023-08-13T14:18:10Z	--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpnodc6f2g\fathyshalab\mdcsi-versicherungen-recht-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\tmpnodc6f2g\fathyshalab\mdcsi-versicherungen-recht-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_t5-small_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v100	KingKazma	2023-08-13T14:18:36Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:18:35Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e6_s108_v4_l4_v20	KingKazma	2023-08-13T14:16:47Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:16:46Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e7_s108_v4_l6_v20	KingKazma	2023-08-13T14:16:27Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:16:25Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0069	bigmorning	2023-08-13T14:15:52Z	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	2023-08-13T14:15:45Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0069 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_0069 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: 0.0027 - Train Accuracy: 0.0795 - Train Wermet: 10.3802 - Validation Loss: 0.5272 - Validation Accuracy: 0.0764 - Validation Wermet: 8.8216 - Epoch: 68 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v100	KingKazma	2023-08-13T14:15:34Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:15:32Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e5_s108_v4_l4_v20	KingKazma	2023-08-13T14:13:39Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:13:38Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0068	bigmorning	2023-08-13T14:11:27Z	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	2023-08-13T14:11:19Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0068 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_0068 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: 0.0123 - Train Accuracy: 0.0792 - Train Wermet: 10.2575 - Validation Loss: 0.5261 - Validation Accuracy: 0.0763 - Validation Wermet: 9.3701 - Epoch: 67 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e4_s108_v4_l4_v20	KingKazma	2023-08-13T14:10:34Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:10:33Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e4_s55555_v4_l4_v100	KingKazma	2023-08-13T14:09:30Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:09:29Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e4_s108_v4_l6_v20	KingKazma	2023-08-13T14:08:33Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:08:32Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
peymansyh/whisper-tiny-en	peymansyh	2023-08-13T14:08:21Z	75	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	2023-08-13T14:08:03Z	--- 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[450:] args: en-US metrics: - name: Wer type: wer value: 0.358913813459268 --- <!-- 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: 0.6260 - Wer Ortho: 0.3646 - Wer: 0.3589 ## 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: 7e-06 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 50 - training_steps: 250 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer Ortho \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---------:\|:------:\| \| 2.0491 \| 3.57 \| 50 \| 1.0332 \| 0.4670 \| 0.4008 \| \| 0.294 \| 7.14 \| 100 \| 0.5294 \| 0.3646 \| 0.3506 \| \| 0.0894 \| 10.71 \| 150 \| 0.5465 \| 0.3837 \| 0.3636 \| \| 0.0163 \| 14.29 \| 200 \| 0.6034 \| 0.3757 \| 0.3660 \| \| 0.0044 \| 17.86 \| 250 \| 0.6260 \| 0.3646 \| 0.3589 \| ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e3_s108_v4_l4_v20	KingKazma	2023-08-13T14:07:28Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:07:26Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
phanvu1905/test1	phanvu1905	2023-08-13T14:07:27Z	0	0	null	[ "arxiv:1910.09700", "region:us" ]	null	2023-08-13T14:06:49Z	--- # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/model-cards {} --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Developed by: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Data Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
bigmorning/whisper_charsplit_new_0067	bigmorning	2023-08-13T14:07:05Z	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	2023-08-13T14:06:58Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0067 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_0067 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: 9.8382 - Validation Loss: 0.5771 - Validation Accuracy: 0.0758 - Validation Wermet: 8.8051 - Epoch: 66 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e3_s55555_v4_l4_v100	KingKazma	2023-08-13T14:06:26Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T14:06:25Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
Binettebob22/test	Binettebob22	2023-08-13T14:06:07Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2023-08-13T14:06:07Z	--- license: creativeml-openrail-m ---
KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e2_s108_v4_l6_v20	KingKazma	2023-08-13T14:03:16Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:58:20Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0066	bigmorning	2023-08-13T14:02:43Z	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	2023-08-13T14:02:35Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0066 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_0066 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: 9.7663 - Validation Loss: 0.5357 - Validation Accuracy: 0.0765 - Validation Wermet: 8.4281 - Epoch: 65 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0065	bigmorning	2023-08-13T13:58:22Z	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	2023-08-13T13:58:13Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0065 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_0065 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: 0.0003 - Train Accuracy: 0.0795 - Train Wermet: 9.7593 - Validation Loss: 0.5320 - Validation Accuracy: 0.0765 - Validation Wermet: 8.4815 - Epoch: 64 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e-1_s108_v4_l4_v50_manual	KingKazma	2023-08-13T13:57:01Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:56:57Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e-1_s108_v4_l4_v100_manual	KingKazma	2023-08-13T13:54:37Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:54:36Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
har1/hs2-model	har1	2023-08-13T13:54:15Z	7	0	transformers.js	[ "transformers.js", "onnx", "bert", "text-classification", "region:us" ]	text-classification	2023-08-08T14:18:43Z	--- library_name: transformers.js pipeline_tag: text-classification --- https://huggingface.co/Hate-speech-CNERG/malayalam-codemixed-abusive-MuRILwith ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e10_s108_v4_l4_v100	KingKazma	2023-08-13T13:53:17Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:53:16Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e9_s108_v4_l4_v50	KingKazma	2023-08-13T13:52:17Z	2	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:52:13Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0063	bigmorning	2023-08-13T13:49:49Z	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	2023-08-13T13:49:42Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0063 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_0063 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: 9.8123 - Validation Loss: 0.5233 - Validation Accuracy: 0.0765 - Validation Wermet: 8.5043 - Epoch: 62 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e8_s108_v4_l4_v50	KingKazma	2023-08-13T13:49:03Z	4	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:48:59Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0062	bigmorning	2023-08-13T13:45:30Z	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	2023-08-13T13:45:22Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0062 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_0062 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: 9.8557 - Validation Loss: 0.5227 - Validation Accuracy: 0.0764 - Validation Wermet: 8.3774 - Epoch: 61 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e6_s108_v4_l4_v50	KingKazma	2023-08-13T13:42:27Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:42:23Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0061	bigmorning	2023-08-13T13:41:13Z	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	2023-08-13T13:41:06Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0061 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_0061 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: 0.0795 - Train Wermet: 10.3884 - Validation Loss: 0.5223 - Validation Accuracy: 0.0764 - Validation Wermet: 8.8152 - Epoch: 60 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e5_s108_v4_l4_v50	KingKazma	2023-08-13T13:39:10Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:39:05Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_lora_500_10_3000_8_e7_s55555_v4_l4_r4	KingKazma	2023-08-13T13:37:41Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:37:39Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0060	bigmorning	2023-08-13T13:36:53Z	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	2023-08-13T13:36:45Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0060 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_0060 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: 0.0124 - Train Accuracy: 0.0792 - Train Wermet: 10.2304 - Validation Loss: 0.5284 - Validation Accuracy: 0.0762 - Validation Wermet: 9.1194 - Epoch: 59 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e4_s108_v4_l4_v50	KingKazma	2023-08-13T13:35:55Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:35:51Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e4_s108_v4_l4_v100	KingKazma	2023-08-13T13:35:03Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:35:02Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_lora_500_10_3000_8_e6_s55555_v4_l4_r4	KingKazma	2023-08-13T13:34:50Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:34:48Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e3_s108_v4_l4_v50	KingKazma	2023-08-13T13:32:36Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:32:32Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
fathyshalab/mdcsi-transport-logistik-setfit	fathyshalab	2023-08-13T13:32:34Z	5	0	sentence-transformers	[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]	text-classification	2023-08-13T13:31:43Z	--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmp0kxa9se7\fathyshalab\mdcsi-transport-logistik-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\tmp0kxa9se7\fathyshalab\mdcsi-transport-logistik-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} } ```
helamri/rl_course_vizdoom_health_gathering_supreme	helamri	2023-08-13T13:32:25Z	0	0	sample-factory	[ "sample-factory", "tensorboard", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2023-08-13T13:24:16Z	--- library_name: sample-factory tags: - deep-reinforcement-learning - reinforcement-learning - sample-factory model-index: - name: APPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: doom_health_gathering_supreme type: doom_health_gathering_supreme metrics: - type: mean_reward value: 11.97 +/- 4.61 name: mean_reward verified: false --- A(n) APPO model trained on the doom_health_gathering_supreme environment. This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory. Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/ ## Downloading the model After installing Sample-Factory, download the model with: ``` python -m sample_factory.huggingface.load_from_hub -r helamri/rl_course_vizdoom_health_gathering_supreme ``` ## Using the model To run the model after download, use the `enjoy` script corresponding to this environment: ``` python -m <path.to.enjoy.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme ``` You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag. See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details ## Training with this model To continue training with this model, use the `train` script corresponding to this environment: ``` python -m <path.to.train.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000 ``` Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
KingKazma/xsum_t5-small_lora_500_10_3000_8_e5_s55555_v4_l4_r4	KingKazma	2023-08-13T13:31:57Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:31:55Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
Mtc2/poca-SoccerTwos	Mtc2	2023-08-13T13:31:31Z	33	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos", "region:us" ]	reinforcement-learning	2023-08-13T13:27:24Z	--- library_name: ml-agents tags: - SoccerTwos - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SoccerTwos --- # poca Agent playing SoccerTwos This is a trained model of a poca agent playing SoccerTwos using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A short tutorial where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: Mtc2/poca-SoccerTwos 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
Binettebob22/Lactation	Binettebob22	2023-08-13T13:30:01Z	3	0	diffusers	[ "diffusers", "text-to-image", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2023-08-04T12:59:37Z	--- license: creativeml-openrail-m library_name: diffusers pipeline_tag: text-to-image ---
shkwon98/llama2-qlora-finetunined-french	shkwon98	2023-08-13T13:29:17Z	2	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:28:37Z	--- 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 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e2_s108_v4_l4_v50	KingKazma	2023-08-13T13:29:16Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:29:12Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_lora_500_10_3000_8_e4_s55555_v4_l4_r4	KingKazma	2023-08-13T13:29:06Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:29:04Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0058	bigmorning	2023-08-13T13:28:01Z	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	2023-08-13T13:27:55Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0058 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_0058 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: 10.2557 - Validation Loss: 0.5328 - Validation Accuracy: 0.0764 - Validation Wermet: 8.5665 - Epoch: 57 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e3_s55555_v4_l4_r4	KingKazma	2023-08-13T13:27:43Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:27:41Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_lora_500_10_3000_8_e3_s55555_v4_l4_r4	KingKazma	2023-08-13T13:26:13Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:26:11Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e1_s108_v4_l4_v50	KingKazma	2023-08-13T13:25:57Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:25:54Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e2_s55555_v4_l4_r4	KingKazma	2023-08-13T13:24:18Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:24:17Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
antonjaragon/wav2vec2-base-ft-keyword-spotting	antonjaragon	2023-08-13T13:23:40Z	164	0	transformers	[ "transformers", "pytorch", "wav2vec2", "audio-classification", "generated_from_trainer", "dataset:superb", "base_model:facebook/wav2vec2-base", "base_model:finetune:facebook/wav2vec2-base", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	audio-classification	2023-08-13T13:03:13Z	--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - audio-classification - generated_from_trainer datasets: - superb metrics: - accuracy model-index: - name: wav2vec2-base-ft-keyword-spotting results: - task: name: Audio Classification type: audio-classification dataset: name: superb type: superb config: ks split: validation args: ks metrics: - name: Accuracy type: accuracy value: 0.9832303618711385 --- <!-- 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-ft-keyword-spotting This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. It achieves the following results on the evaluation set: - Loss: 0.0827 - Accuracy: 0.9832 ## 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: 32 - eval_batch_size: 32 - seed: 0 - 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: 5.0 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.4547 \| 1.0 \| 399 \| 0.3372 \| 0.9710 \| \| 0.2625 \| 2.0 \| 798 \| 0.1182 \| 0.9779 \| \| 0.1575 \| 3.0 \| 1197 \| 0.0963 \| 0.9787 \| \| 0.1314 \| 4.0 \| 1597 \| 0.0827 \| 0.9832 \| \| 0.1307 \| 5.0 \| 1995 \| 0.0789 \| 0.9831 \| ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3
KingKazma/xsum_t5-small_lora_500_10_3000_8_e2_s55555_v4_l4_r4	KingKazma	2023-08-13T13:23:18Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:23:16Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e1_s55555_v4_l4_r4	KingKazma	2023-08-13T13:20:56Z	0	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:20:54Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
KingKazma/xsum_t5-small_lora_500_10_3000_8_e1_s55555_v4_l4_r4	KingKazma	2023-08-13T13:20:25Z	1	0	peft	[ "peft", "region:us" ]	null	2023-08-13T13:20:23Z	--- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
aurioldegbelo/slm-edge-detection	aurioldegbelo	2023-08-13T13:19:53Z	0	0	null	[ "license:mit", "region:us" ]	null	2023-08-13T13:12:42Z	--- license: mit --- This repository contains two functions used for boundary detection. The two functions were tested with respect to their respective performance on a boundary extraction task for sketched maps.
bigmorning/whisper_charsplit_new_0056	bigmorning	2023-08-13T13:19:10Z	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	2023-08-13T13:19:02Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0056 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_0056 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: 10.1079 - Validation Loss: 0.5217 - Validation Accuracy: 0.0764 - Validation Wermet: 8.5608 - Epoch: 55 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
Dayanand4574/stable-diffusion-chair	Dayanand4574	2023-08-13T13:15:29Z	3	0	diffusers	[ "diffusers", "safetensors", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]	text-to-image	2023-08-13T13:11:48Z	--- license: creativeml-openrail-m tags: - text-to-image - stable-diffusion --- ### Stable-diffusion-chair Dreambooth model trained by Dayanand4574 with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb) Sample pictures of this concept:
ShowCarSign/car-show-display-signs-and-boards	ShowCarSign	2023-08-13T13:14:29Z	0	0	null	[ "region:us" ]	null	2023-08-13T12:56:16Z	Welcome to the ShowCarSign <a href="https://showcarsign.com/product/show-car-sign/">car show display boards</a>. ! Here, you'll find an excellent selection of boards that will showcase your cars in style. Whether you're a seasoned pro with a fleet of vehicles or a first-time buyer with just one car, we've got something for everyone. Our boards are designed to turn heads and get attention. That means they have to look just as great on the outside as they do the inside. Choose from our wide range of <a href="http://https://showcarsign.com/">car show display ideas</a>. Plus, our state-of-the-art printing techniques make sure that whatever board you choose, it'll be vibrant and strong - ready to show off your precious vehicles in all their glory. For those with more unique tastes, we can even design and create custom <a href="http://https://showcarsign.com/product/car-show-boards/">car show reader boards</a> made to measure. So come take a look at what we have to offer here at ShowCarSign and make sure your cars get the display they deserve. Visit: https://showcarsign.com
bigmorning/whisper_charsplit_new_0053	bigmorning	2023-08-13T13:05:58Z	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	2023-08-13T13:05:49Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0053 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_0053 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: 0.0083 - Train Accuracy: 0.0794 - Train Wermet: 9.9557 - Validation Loss: 0.5173 - Validation Accuracy: 0.0762 - Validation Wermet: 8.2406 - Epoch: 52 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
ailabturkiye/tonguc	ailabturkiye	2023-08-13T13:01:01Z	0	0	null	[ "music", "tr", "license:openrail", "region:us" ]	null	2023-08-13T12:50:26Z	--- license: openrail language: - tr tags: - music ---
bigmorning/whisper_charsplit_new_0050	bigmorning	2023-08-13T12:52:38Z	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	2023-08-13T12:52:29Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0050 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_0050 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: 10.0022 - Validation Loss: 0.5166 - Validation Accuracy: 0.0764 - Validation Wermet: 8.4855 - Epoch: 49 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
fp16-guy/Cetus-Mix_v4_fp16_cleaned	fp16-guy	2023-08-13T12:51:38Z	0	1	null	[ "text-to-image", "region:us" ]	text-to-image	2023-07-31T14:37:04Z	--- pipeline_tag: text-to-image --- Cetus-Mix v4, but fp16/cleaned - smaller size, same result. ======== /// [original checkpoint link](https://civitai.com/models/6755?modelVersionId=126564) (all rights to the model belong to Eagelaxis) --- [grid 01](https://huggingface.co/datasets/fp16-guy/grids/blob/main/cetusmixv4%2001%2020230807110113-111-cetusMix_v4-Euler%20a-6.png) (1.99gb version)* [grid 02](https://huggingface.co/datasets/fp16-guy/grids/blob/main/cetusmixv4%2002%2020230807110204-111-cetusMix_v4-Euler%20a-6.png) (1.83gb version - no vae)* [grid 03](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/cetusMix_v4%20inp%2001%2020230813151521-111-cetusMix_v4_fp16-Euler%20a-5.5.png) (1.99gb inpainting version)* [grid 04](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/cetusMix_v4%20inp%2002%2020230813151628-111-cetusMix_v4_fp16_no_vae-Euler%20a-5.5.png) (1.83gb inpainting version - no vae)*
bigmorning/whisper_charsplit_new_0048	bigmorning	2023-08-13T12:43:50Z	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	2023-08-13T12:43:42Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0048 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_0048 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: 10.0455 - Validation Loss: 0.5174 - Validation Accuracy: 0.0762 - Validation Wermet: 8.2514 - Epoch: 47 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
Ding-Qiang/Reinfore-MLP-Cartpole	Ding-Qiang	2023-08-13T12:36:09Z	0	0	null	[ "CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class", "model-index", "region:us" ]	reinforcement-learning	2023-08-13T12:35:59Z	--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinfore-MLP results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 457.00 +/- 87.33 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
bigmorning/whisper_charsplit_new_0045	bigmorning	2023-08-13T12:30:32Z	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	2023-08-13T12:30:23Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0045 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_0045 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: 0.0024 - Train Accuracy: 0.0795 - Train Wermet: 10.3731 - Validation Loss: 0.5055 - Validation Accuracy: 0.0762 - Validation Wermet: 8.6347 - Epoch: 44 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
hafidzmrizky/stress-detection-500	hafidzmrizky	2023-08-13T12:30:30Z	0	0	peft	[ "peft", "doi:10.57967/hf/0976", "region:us" ]	null	2023-08-13T11:30:51Z	--- library_name: peft --- ## Training procedure failed model, cant delete. 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: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.5.0.dev0
bigmorning/whisper_charsplit_new_0044	bigmorning	2023-08-13T12:26:06Z	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	2023-08-13T12:25:59Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0044 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_0044 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: 0.0023 - Train Accuracy: 0.0795 - Train Wermet: 10.4871 - Validation Loss: 0.5027 - Validation Accuracy: 0.0762 - Validation Wermet: 8.6712 - Epoch: 43 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0043	bigmorning	2023-08-13T12:21:48Z	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	2023-08-13T12:21:41Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0043 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_0043 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: 0.0028 - Train Accuracy: 0.0795 - Train Wermet: 10.3174 - Validation Loss: 0.4968 - Validation Accuracy: 0.0762 - Validation Wermet: 8.8525 - Epoch: 42 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0042	bigmorning	2023-08-13T12:17:26Z	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	2023-08-13T12:17:18Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0042 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_0042 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: 0.0045 - Train Accuracy: 0.0795 - Train Wermet: 10.2251 - Validation Loss: 0.5014 - Validation Accuracy: 0.0761 - Validation Wermet: 8.5737 - Epoch: 41 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
mosama/Llama-2-LoRA-Weights	mosama	2023-08-13T12:17:09Z	6	1	peft	[ "peft", "safetensors", "region:us" ]	null	2023-07-27T20:50:46Z	--- 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: True - bnb_4bit_compute_dtype: float16 ### Framework versions - PEFT 0.4.0
Pierre-Arthur/T5_small_eurlexsum	Pierre-Arthur	2023-08-13T12:16:31Z	106	0	transformers	[ "transformers", "pytorch", "tensorboard", "safetensors", "t5", "text2text-generation", "generated_from_trainer", "dataset:eur-lex-sum", "base_model:google-t5/t5-small", "base_model:finetune:google-t5/t5-small", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2023-07-24T20:26:43Z	--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - eur-lex-sum metrics: - rouge model-index: - name: T5_small_eurlexsum results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: eur-lex-sum type: eur-lex-sum config: french split: test args: french metrics: - name: Rouge1 type: rouge value: 0.2 --- <!-- 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. --> # T5_small_eurlexsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eur-lex-sum dataset. It achieves the following results on the evaluation set: - Loss: 1.1159 - Rouge1: 0.2 - Rouge2: 0.1394 - Rougel: 0.1833 - Rougelsum: 0.1829 - Gen Len: 19.0 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\|:------:\|:---------:\|:-------:\| \| No log \| 1.0 \| 71 \| 1.4740 \| 0.1718 \| 0.0935 \| 0.1476 \| 0.1476 \| 19.0 \| \| No log \| 2.0 \| 142 \| 1.2138 \| 0.1915 \| 0.1207 \| 0.1719 \| 0.1719 \| 19.0 \| \| No log \| 3.0 \| 213 \| 1.1368 \| 0.1953 \| 0.1306 \| 0.1759 \| 0.1759 \| 19.0 \| \| No log \| 4.0 \| 284 \| 1.1159 \| 0.2 \| 0.1394 \| 0.1833 \| 0.1829 \| 19.0 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.0 - Tokenizers 0.13.3
lizsergeeva/vit-base-patch16-224-finetuned-vit	lizsergeeva	2023-08-13T12:13:49Z	193	0	transformers	[ "transformers", "pytorch", "tensorboard", "vit", "image-classification", "generated_from_trainer", "dataset:imagefolder", "base_model:google/vit-base-patch16-224", "base_model:finetune:google/vit-base-patch16-224", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	image-classification	2023-08-13T08:28:07Z	--- license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-base-patch16-224-finetuned-vit 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: 0.9160530191458026 --- <!-- 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. --> # vit-base-patch16-224-finetuned-vit This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2549 - Accuracy: 0.9161 ## 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: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.6065 \| 0.99 \| 47 \| 0.4006 \| 0.8748 \| \| 0.335 \| 2.0 \| 95 \| 0.2745 \| 0.9175 \| \| 0.2707 \| 2.97 \| 141 \| 0.2549 \| 0.9161 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0041	bigmorning	2023-08-13T12:12:58Z	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	2023-08-13T12:12:51Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0041 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_0041 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: 0.0120 - Train Accuracy: 0.0793 - Train Wermet: 10.4810 - Validation Loss: 0.4963 - Validation Accuracy: 0.0760 - Validation Wermet: 8.9194 - Epoch: 40 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
Evan-Lin/Bart-large-abs-amazon-allure	Evan-Lin	2023-08-13T12:06:06Z	47	0	transformers	[ "transformers", "pytorch", "bart", "text2text-generation", "trl", "reinforcement-learning", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	reinforcement-learning	2023-08-13T11:59:19Z	--- license: apache-2.0 tags: - trl - transformers - reinforcement-learning --- # TRL Model This is a [TRL language model](https://github.com/lvwerra/trl) that has been fine-tuned with reinforcement learning to guide the model outputs according to a value, function, or human feedback. The model can be used for text generation. ## Usage To use this model for inference, first install the TRL library: ```bash python -m pip install trl ``` You can then generate text as follows: ```python from transformers import pipeline generator = pipeline("text-generation", model="Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") outputs = generator("Hello, my llama is cute") ``` If you want to use the model for training or to obtain the outputs from the value head, load the model as follows: ```python from transformers import AutoTokenizer from trl import AutoModelForCausalLMWithValueHead tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") inputs = tokenizer("Hello, my llama is cute", return_tensors="pt") outputs = model(**inputs, labels=inputs["input_ids"]) ```
bigmorning/whisper_charsplit_new_0038	bigmorning	2023-08-13T11:59:47Z	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	2023-08-13T11:59:40Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0038 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_0038 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: 0.0020 - Train Accuracy: 0.0795 - Train Wermet: 10.7428 - Validation Loss: 0.4835 - Validation Accuracy: 0.0762 - Validation Wermet: 9.0566 - Epoch: 37 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
fathyshalab/mdcsi-unternehmen-verbaende-setfit	fathyshalab	2023-08-13T11:51:49Z	5	0	sentence-transformers	[ "sentence-transformers", "pytorch", "roberta", "setfit", "text-classification", "arxiv:2209.11055", "license:apache-2.0", "region:us" ]	text-classification	2023-08-13T11:50:59Z	--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmp8z_73twb\fathyshalab\mdcsi-unternehmen-verbaende-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\tmp8z_73twb\fathyshalab\mdcsi-unternehmen-verbaende-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} } ```
manvik28/FinBERT_Tuned	manvik28	2023-08-13T11:47:14Z	106	0	transformers	[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "base_model:ProsusAI/finbert", "base_model:finetune:ProsusAI/finbert", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-13T11:15:40Z	--- base_model: ProsusAI/finbert tags: - generated_from_trainer model-index: - name: FinBERT_Tuned 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. --> # FinBERT_Tuned This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| No log \| 1.0 \| 148 \| 0.4307 \| 0.7776 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0035	bigmorning	2023-08-13T11:46:46Z	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	2023-08-13T11:46:39Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_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_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: 0.0130 - Train Accuracy: 0.0793 - Train Wermet: 11.1022 - Validation Loss: 0.4748 - Validation Accuracy: 0.0760 - Validation Wermet: 9.4521 - 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 \| \|:----------:\|:--------------:\|:------------:\|:---------------:\|:-------------------:\|:-----------------:\|:-----:\| \| 0.8733 \| 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0034	bigmorning	2023-08-13T11:42:29Z	61	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	2023-08-13T11:42:22Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0034 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_0034 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: 0.0047 - Train Accuracy: 0.0795 - Train Wermet: 10.7613 - Validation Loss: 0.4788 - Validation Accuracy: 0.0759 - Validation Wermet: 9.4065 - Epoch: 33 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0029	bigmorning	2023-08-13T11:20:47Z	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	2023-08-13T11:20:40Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0029 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_0029 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: 0.0114 - Train Accuracy: 0.0794 - Train Wermet: 11.3093 - Validation Loss: 0.4431 - Validation Accuracy: 0.0758 - Validation Wermet: 9.5545 - Epoch: 28 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
bigmorning/whisper_charsplit_new_0026	bigmorning	2023-08-13T11:07:34Z	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	2023-08-13T11:07:26Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0026 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_0026 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: 0.0142 - Train Accuracy: 0.0794 - Train Wermet: 11.3562 - Validation Loss: 0.4057 - Validation Accuracy: 0.0760 - Validation Wermet: 9.6831 - Epoch: 25 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
morell23/3dmm	morell23	2023-08-13T11:04:37Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2023-08-13T11:03:45Z	--- license: creativeml-openrail-m ---
Falah/Iyad_Radi_SDXL1.0_Lora	Falah	2023-08-13T11:01:53Z	3	2	diffusers	[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]	text-to-image	2023-08-13T08:27:32Z	--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a Iyad Radi tags: - text-to-image - diffusers - autotrain inference: true --- # ART Text-to-Image Generation using stabilityai/stable-diffusion-xl-base-1.0 This repository contains code and instructions for using the `stabilityai/stable-diffusion-xl-base-1.0` model from Hugging Face's Transformers library to generate images from textual descriptions. The model utilizes diffusion models for high-quality image synthesis based on the provided text prompts. ![1](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/12.png) ![2](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/2.png) ![3](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/3.png) ![4](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/4.png) ![5](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/6.png) ![6](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/8.png) ## Model Information - Base Model: stabilityai/stable-diffusion-xl-base-1.0 - Instance Prompt: "photo of Iyad Radi" - Tags: - text-to-image - diffusers - autotrain ## Inference To use this model for generating images from text prompts, follow these steps: 1. Environment Setup: Make sure you have Python installed on your system. You can also use a virtual environment for isolation. 2. Install Dependencies: Install the required Python packages by running the following command: ```bash pip install -r requirements.txt ``` 3.## Usage Here is an example of how you can use the `stabilityai/stable-diffusion-xl-base-1.0` model for text-to-image generation in Python using the `diffusers` library. ```python from diffusers import DiffusionPipeline import torch # Load LoRA weights lora_weights = torch.load("/path/to/lora_weights/pytorch_lora_weights.safetensors") # Initialize the DiffusionPipeline pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16) pipe.to("cuda") # Load LoRA weights into the pipeline pipe.load_lora_weights(lora_weights) # Text prompt for image generation prompt = "photo of Iyad Radi with cat in the pool" # Generate Images image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images ``` 4. Generated Images: The generated images will be saved in the `output_images` directory by default. ## Application in Art and Cinema Industry This model can be incredibly useful in the art and cinema movie production industry, especially for creating visuals based on textual descriptions. In the case of Aiyad Radi, an Iraqi actor and comedian, this tool can aid in visualizing character designs, scenes, and concepts before actual production. Directors, artists, and producers can utilize the generated images as a reference to plan and visualize their projects effectively. ## Credits - Model developed by [stabilityai](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) - This repository is created and maintained by [Falah.G.Saleih] ## Disclaimer Please note that the model's outputs might vary, and the generated images are based on the input text prompts. The model's behavior is influenced by its training data and might not always produce accurate or desired results. Feel free to experiment, provide feedback, and contribute to this repository if you'd like to enhance its functionality! ---
bigmorning/whisper_charsplit_new_0022	bigmorning	2023-08-13T10:50:13Z	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	2023-08-13T10:50:05Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0022 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_0022 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: 0.0318 - Train Accuracy: 0.0790 - Train Wermet: 11.6314 - Validation Loss: 0.3628 - Validation Accuracy: 0.0760 - Validation Wermet: 9.6652 - Epoch: 21 ## 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 \| ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3
steve-tong/opus-mt-en-zh-tw	steve-tong	2023-08-13T10:39:43Z	107	2	transformers	[ "transformers", "pytorch", "tensorboard", "marian", "text2text-generation", "generated_from_trainer", "base_model:Helsinki-NLP/opus-mt-en-zh", "base_model:finetune:Helsinki-NLP/opus-mt-en-zh", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2023-08-13T10:36:48Z	--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-zh tags: - generated_from_trainer model-index: - name: opus-mt-en-zh-tw 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. --> # opus-mt-en-zh-tw This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) on the None 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.0 - Tokenizers 0.13.3
snob/HeungEol-KoAlpaca-12.8B-v1.0_LoRA	snob	2023-08-13T10:38:31Z	0	0	peft	[ "peft", "HeungEol", "ko", "region:us" ]	null	2023-08-10T12:38:00Z	--- library_name: peft language: - ko tags: - HeungEol --- ## Training procedure ### Framework versions - PEFT 0.4.0.dev0
snob/HeungEol-KoAlpaca-12.8B-v1.0	snob	2023-08-13T10:38:08Z	13	0	transformers	[ "transformers", "pytorch", "gpt_neox", "text-generation", "HeungEol", "ko", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2023-08-10T13:56:44Z	--- tags: - HeungEol language: - ko ---

bigmorning/whisper_charsplit_new_0072

bigmorning

2023-08-13T14:29:00Z

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

2023-08-13T14:28:53Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0072 results: [] ---  # whisper_charsplit_new_0072 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: 10.2545 - Validation Loss: 0.5315 - Validation Accuracy: 0.0765 - Validation Wermet: 9.0617 - Epoch: 71 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e9_s55555_v4_l4_v50

KingKazma

2023-08-13T14:28:55Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:28:51Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v50

KingKazma

2023-08-13T14:25:39Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:25:36Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e-1_s108_v4_l6_v20_manual

KingKazma

2023-08-13T14:25:35Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:25:33Z

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

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e9_s55555_v4_l4_v100

KingKazma

2023-08-13T14:24:41Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:24:40Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e10_s108_v4_l6_v20

KingKazma

2023-08-13T14:24:22Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:24:20Z

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

nightdude/config_4

nightdude

2023-08-13T14:23:39Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:23:30Z

--- 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: True - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.4.0.dev0

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e8_s108_v4_l4_v20

KingKazma

2023-08-13T14:23:00Z

2

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:22:59Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v50

KingKazma

2023-08-13T14:22:22Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:22:18Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e9_s108_v4_l6_v20

KingKazma

2023-08-13T14:21:42Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:21:41Z

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

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e8_s55555_v4_l4_v100

KingKazma

2023-08-13T14:21:41Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:21:40Z

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

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e7_s108_v4_l4_v20

KingKazma

2023-08-13T14:19:53Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:19:52Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v50

KingKazma

2023-08-13T14:19:03Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:18:59Z

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

fathyshalab/mdcsi-versicherungen-recht-setfit

fathyshalab

2023-08-13T14:19:01Z

6

0

sentence-transformers

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

text-classification

2023-08-13T14:18:10Z

--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmpnodc6f2g\fathyshalab\mdcsi-versicherungen-recht-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\tmpnodc6f2g\fathyshalab\mdcsi-versicherungen-recht-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_t5-small_p_tuning_500_10_3000_8_e7_s55555_v4_l4_v100

KingKazma

2023-08-13T14:18:36Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:18:35Z

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

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e6_s108_v4_l4_v20

KingKazma

2023-08-13T14:16:47Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:16:46Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e7_s108_v4_l6_v20

KingKazma

2023-08-13T14:16:27Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:16:25Z

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

bigmorning/whisper_charsplit_new_0069

bigmorning

2023-08-13T14:15:52Z

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

2023-08-13T14:15:45Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0069 results: [] ---  # whisper_charsplit_new_0069 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: 0.0027 - Train Accuracy: 0.0795 - Train Wermet: 10.3802 - Validation Loss: 0.5272 - Validation Accuracy: 0.0764 - Validation Wermet: 8.8216 - Epoch: 68 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e6_s55555_v4_l4_v100

KingKazma

2023-08-13T14:15:34Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:15:32Z

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

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e5_s108_v4_l4_v20

KingKazma

2023-08-13T14:13:39Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:13:38Z

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

bigmorning/whisper_charsplit_new_0068

bigmorning

2023-08-13T14:11:27Z

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

2023-08-13T14:11:19Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0068 results: [] ---  # whisper_charsplit_new_0068 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: 0.0123 - Train Accuracy: 0.0792 - Train Wermet: 10.2575 - Validation Loss: 0.5261 - Validation Accuracy: 0.0763 - Validation Wermet: 9.3701 - Epoch: 67 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e4_s108_v4_l4_v20

KingKazma

2023-08-13T14:10:34Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:10:33Z

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

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e4_s55555_v4_l4_v100

KingKazma

2023-08-13T14:09:30Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:09:29Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e4_s108_v4_l6_v20

KingKazma

2023-08-13T14:08:33Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:08:32Z

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

peymansyh/whisper-tiny-en

peymansyh

2023-08-13T14:08:21Z

75

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

2023-08-13T14:08:03Z

--- 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[450:] args: en-US metrics: - name: Wer type: wer value: 0.358913813459268 ---  # 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: 0.6260 - Wer Ortho: 0.3646 - Wer: 0.3589 ## 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: 7e-06 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 50 - training_steps: 250 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 2.0491 | 3.57 | 50 | 1.0332 | 0.4670 | 0.4008 | | 0.294 | 7.14 | 100 | 0.5294 | 0.3646 | 0.3506 | | 0.0894 | 10.71 | 150 | 0.5465 | 0.3837 | 0.3636 | | 0.0163 | 14.29 | 200 | 0.6034 | 0.3757 | 0.3660 | | 0.0044 | 17.86 | 250 | 0.6260 | 0.3646 | 0.3589 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_prompt_tuning_500_10_3000_8_e3_s108_v4_l4_v20

KingKazma

2023-08-13T14:07:28Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:07:26Z

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

phanvu1905/test1

phanvu1905

2023-08-13T14:07:27Z

0

null

[ "arxiv:1910.09700", "region:us" ]

null

2023-08-13T14:06:49Z

--- # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/model-cards {} --- # Model Card for Model ID  This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Model Details ### Model Description  - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

bigmorning/whisper_charsplit_new_0067

bigmorning

2023-08-13T14:07:05Z

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

2023-08-13T14:06:58Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0067 results: [] ---  # whisper_charsplit_new_0067 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: 9.8382 - Validation Loss: 0.5771 - Validation Accuracy: 0.0758 - Validation Wermet: 8.8051 - Epoch: 66 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e3_s55555_v4_l4_v100

KingKazma

2023-08-13T14:06:26Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T14:06:25Z

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

Binettebob22/test

Binettebob22

2023-08-13T14:06:07Z

0

null

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

null

2023-08-13T14:06:07Z

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

KingKazma/xsum_t5-small_prompt_tuning_500_10_3000_8_e2_s108_v4_l6_v20

KingKazma

2023-08-13T14:03:16Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:58:20Z

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

bigmorning/whisper_charsplit_new_0066

bigmorning

2023-08-13T14:02:43Z

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

2023-08-13T14:02:35Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0066 results: [] ---  # whisper_charsplit_new_0066 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: 9.7663 - Validation Loss: 0.5357 - Validation Accuracy: 0.0765 - Validation Wermet: 8.4281 - Epoch: 65 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0065

bigmorning

2023-08-13T13:58:22Z

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

2023-08-13T13:58:13Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0065 results: [] ---  # whisper_charsplit_new_0065 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: 0.0003 - Train Accuracy: 0.0795 - Train Wermet: 9.7593 - Validation Loss: 0.5320 - Validation Accuracy: 0.0765 - Validation Wermet: 8.4815 - Epoch: 64 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e-1_s108_v4_l4_v50_manual

KingKazma

2023-08-13T13:57:01Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:56:57Z

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

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e-1_s108_v4_l4_v100_manual

KingKazma

2023-08-13T13:54:37Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:54:36Z

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

har1/hs2-model

har1

2023-08-13T13:54:15Z

7

0

transformers.js

[ "transformers.js", "onnx", "bert", "text-classification", "region:us" ]

text-classification

2023-08-08T14:18:43Z

--- library_name: transformers.js pipeline_tag: text-classification --- https://huggingface.co/Hate-speech-CNERG/malayalam-codemixed-abusive-MuRILwith ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e10_s108_v4_l4_v100

KingKazma

2023-08-13T13:53:17Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:53:16Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e9_s108_v4_l4_v50

KingKazma

2023-08-13T13:52:17Z

2

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:52:13Z

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

bigmorning/whisper_charsplit_new_0063

bigmorning

2023-08-13T13:49:49Z

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

2023-08-13T13:49:42Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0063 results: [] ---  # whisper_charsplit_new_0063 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: 9.8123 - Validation Loss: 0.5233 - Validation Accuracy: 0.0765 - Validation Wermet: 8.5043 - Epoch: 62 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e8_s108_v4_l4_v50

KingKazma

2023-08-13T13:49:03Z

4

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:48:59Z

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

bigmorning/whisper_charsplit_new_0062

bigmorning

2023-08-13T13:45:30Z

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

2023-08-13T13:45:22Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0062 results: [] ---  # whisper_charsplit_new_0062 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: 9.8557 - Validation Loss: 0.5227 - Validation Accuracy: 0.0764 - Validation Wermet: 8.3774 - Epoch: 61 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e6_s108_v4_l4_v50

KingKazma

2023-08-13T13:42:27Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:42:23Z

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

bigmorning/whisper_charsplit_new_0061

bigmorning

2023-08-13T13:41:13Z

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

2023-08-13T13:41:06Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0061 results: [] ---  # whisper_charsplit_new_0061 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: 0.0795 - Train Wermet: 10.3884 - Validation Loss: 0.5223 - Validation Accuracy: 0.0764 - Validation Wermet: 8.8152 - Epoch: 60 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e5_s108_v4_l4_v50

KingKazma

2023-08-13T13:39:10Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:39:05Z

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

KingKazma/xsum_t5-small_lora_500_10_3000_8_e7_s55555_v4_l4_r4

KingKazma

2023-08-13T13:37:41Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:37:39Z

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

bigmorning/whisper_charsplit_new_0060

bigmorning

2023-08-13T13:36:53Z

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

2023-08-13T13:36:45Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0060 results: [] ---  # whisper_charsplit_new_0060 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: 0.0124 - Train Accuracy: 0.0792 - Train Wermet: 10.2304 - Validation Loss: 0.5284 - Validation Accuracy: 0.0762 - Validation Wermet: 9.1194 - Epoch: 59 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e4_s108_v4_l4_v50

KingKazma

2023-08-13T13:35:55Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:35:51Z

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

KingKazma/xsum_t5-small_p_tuning_500_10_3000_8_e4_s108_v4_l4_v100

KingKazma

2023-08-13T13:35:03Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:35:02Z

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

KingKazma/xsum_t5-small_lora_500_10_3000_8_e6_s55555_v4_l4_r4

KingKazma

2023-08-13T13:34:50Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:34:48Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e3_s108_v4_l4_v50

KingKazma

2023-08-13T13:32:36Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:32:32Z

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

fathyshalab/mdcsi-transport-logistik-setfit

fathyshalab

2023-08-13T13:32:34Z

5

0

sentence-transformers

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

text-classification

2023-08-13T13:31:43Z

--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmp0kxa9se7\fathyshalab\mdcsi-transport-logistik-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\tmp0kxa9se7\fathyshalab\mdcsi-transport-logistik-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} } ```

helamri/rl_course_vizdoom_health_gathering_supreme

helamri

2023-08-13T13:32:25Z

0

sample-factory

[ "sample-factory", "tensorboard", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2023-08-13T13:24:16Z

--- library_name: sample-factory tags: - deep-reinforcement-learning - reinforcement-learning - sample-factory model-index: - name: APPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: doom_health_gathering_supreme type: doom_health_gathering_supreme metrics: - type: mean_reward value: 11.97 +/- 4.61 name: mean_reward verified: false --- A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment. This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory. Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/ ## Downloading the model After installing Sample-Factory, download the model with: ``` python -m sample_factory.huggingface.load_from_hub -r helamri/rl_course_vizdoom_health_gathering_supreme ``` ## Using the model To run the model after download, use the `enjoy` script corresponding to this environment: ``` python -m <path.to.enjoy.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme ``` You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag. See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details ## Training with this model To continue training with this model, use the `train` script corresponding to this environment: ``` python -m <path.to.train.module> --algo=APPO --env=doom_health_gathering_supreme --train_dir=./train_dir --experiment=rl_course_vizdoom_health_gathering_supreme --restart_behavior=resume --train_for_env_steps=10000000000 ``` Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.

KingKazma/xsum_t5-small_lora_500_10_3000_8_e5_s55555_v4_l4_r4

KingKazma

2023-08-13T13:31:57Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:31:55Z

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

Mtc2/poca-SoccerTwos

Mtc2

2023-08-13T13:31:31Z

33

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos", "region:us" ]

reinforcement-learning

2023-08-13T13:27:24Z

--- library_name: ml-agents tags: - SoccerTwos - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SoccerTwos --- # **poca** Agent playing **SoccerTwos** This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: Mtc2/poca-SoccerTwos 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

Binettebob22/Lactation

Binettebob22

2023-08-13T13:30:01Z

3

0

diffusers

[ "diffusers", "text-to-image", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2023-08-04T12:59:37Z

--- license: creativeml-openrail-m library_name: diffusers pipeline_tag: text-to-image ---

shkwon98/llama2-qlora-finetunined-french

shkwon98

2023-08-13T13:29:17Z

2

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:28:37Z

--- 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 0.5.0.dev0

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e2_s108_v4_l4_v50

KingKazma

2023-08-13T13:29:16Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:29:12Z

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

KingKazma/xsum_t5-small_lora_500_10_3000_8_e4_s55555_v4_l4_r4

KingKazma

2023-08-13T13:29:06Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:29:04Z

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

bigmorning/whisper_charsplit_new_0058

bigmorning

2023-08-13T13:28:01Z

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

2023-08-13T13:27:55Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0058 results: [] ---  # whisper_charsplit_new_0058 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: 10.2557 - Validation Loss: 0.5328 - Validation Accuracy: 0.0764 - Validation Wermet: 8.5665 - Epoch: 57 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e3_s55555_v4_l4_r4

KingKazma

2023-08-13T13:27:43Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:27:41Z

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

KingKazma/xsum_t5-small_lora_500_10_3000_8_e3_s55555_v4_l4_r4

KingKazma

2023-08-13T13:26:13Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:26:11Z

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

KingKazma/cnn_dailymail_t5-small_p_tuning_500_10_3000_8_e1_s108_v4_l4_v50

KingKazma

2023-08-13T13:25:57Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:25:54Z

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

KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e2_s55555_v4_l4_r4

KingKazma

2023-08-13T13:24:18Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:24:17Z

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

antonjaragon/wav2vec2-base-ft-keyword-spotting

antonjaragon

2023-08-13T13:23:40Z

164

0

transformers

[ "transformers", "pytorch", "wav2vec2", "audio-classification", "generated_from_trainer", "dataset:superb", "base_model:facebook/wav2vec2-base", "base_model:finetune:facebook/wav2vec2-base", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

audio-classification

2023-08-13T13:03:13Z

--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - audio-classification - generated_from_trainer datasets: - superb metrics: - accuracy model-index: - name: wav2vec2-base-ft-keyword-spotting results: - task: name: Audio Classification type: audio-classification dataset: name: superb type: superb config: ks split: validation args: ks metrics: - name: Accuracy type: accuracy value: 0.9832303618711385 ---  # wav2vec2-base-ft-keyword-spotting This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. It achieves the following results on the evaluation set: - Loss: 0.0827 - Accuracy: 0.9832 ## 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: 32 - eval_batch_size: 32 - seed: 0 - 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: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.4547 | 1.0 | 399 | 0.3372 | 0.9710 | | 0.2625 | 2.0 | 798 | 0.1182 | 0.9779 | | 0.1575 | 3.0 | 1197 | 0.0963 | 0.9787 | | 0.1314 | 4.0 | 1597 | 0.0827 | 0.9832 | | 0.1307 | 5.0 | 1995 | 0.0789 | 0.9831 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3

KingKazma/xsum_t5-small_lora_500_10_3000_8_e2_s55555_v4_l4_r4

KingKazma

2023-08-13T13:23:18Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:23:16Z

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

KingKazma/cnn_dailymail_t5-small_lora_500_10_3000_8_e1_s55555_v4_l4_r4

KingKazma

2023-08-13T13:20:56Z

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:20:54Z

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

KingKazma/xsum_t5-small_lora_500_10_3000_8_e1_s55555_v4_l4_r4

KingKazma

2023-08-13T13:20:25Z

1

0

peft

[ "peft", "region:us" ]

null

2023-08-13T13:20:23Z

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

aurioldegbelo/slm-edge-detection

aurioldegbelo

2023-08-13T13:19:53Z

0

null

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

null

2023-08-13T13:12:42Z

--- license: mit --- This repository contains two functions used for boundary detection. The two functions were tested with respect to their respective performance on a boundary extraction task for sketched maps.

bigmorning/whisper_charsplit_new_0056

bigmorning

2023-08-13T13:19:10Z

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

2023-08-13T13:19:02Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0056 results: [] ---  # whisper_charsplit_new_0056 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: 10.1079 - Validation Loss: 0.5217 - Validation Accuracy: 0.0764 - Validation Wermet: 8.5608 - Epoch: 55 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

Dayanand4574/stable-diffusion-chair

Dayanand4574

2023-08-13T13:15:29Z

3

0

diffusers

[ "diffusers", "safetensors", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]

text-to-image

2023-08-13T13:11:48Z

--- license: creativeml-openrail-m tags: - text-to-image - stable-diffusion --- ### Stable-diffusion-chair Dreambooth model trained by Dayanand4574 with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb) Sample pictures of this concept:

ShowCarSign/car-show-display-signs-and-boards

ShowCarSign

2023-08-13T13:14:29Z

0

null

[ "region:us" ]

null

2023-08-13T12:56:16Z

Welcome to the ShowCarSign <a href="https://showcarsign.com/product/show-car-sign/">car show display boards</a>. ! Here, you'll find an excellent selection of boards that will showcase your cars in style. Whether you're a seasoned pro with a fleet of vehicles or a first-time buyer with just one car, we've got something for everyone. Our boards are designed to turn heads and get attention. That means they have to look just as great on the outside as they do the inside. Choose from our wide range of <a href="http://https://showcarsign.com/">car show display ideas</a>. Plus, our state-of-the-art printing techniques make sure that whatever board you choose, it'll be vibrant and strong - ready to show off your precious vehicles in all their glory. For those with more unique tastes, we can even design and create custom <a href="http://https://showcarsign.com/product/car-show-boards/">car show reader boards</a> made to measure. So come take a look at what we have to offer here at ShowCarSign and make sure your cars get the display they deserve. Visit: https://showcarsign.com

bigmorning/whisper_charsplit_new_0053

bigmorning

2023-08-13T13:05:58Z

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

2023-08-13T13:05:49Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0053 results: [] ---  # whisper_charsplit_new_0053 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: 0.0083 - Train Accuracy: 0.0794 - Train Wermet: 9.9557 - Validation Loss: 0.5173 - Validation Accuracy: 0.0762 - Validation Wermet: 8.2406 - Epoch: 52 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

ailabturkiye/tonguc

ailabturkiye

2023-08-13T13:01:01Z

0

null

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

null

2023-08-13T12:50:26Z

--- license: openrail language: - tr tags: - music ---

bigmorning/whisper_charsplit_new_0050

bigmorning

2023-08-13T12:52:38Z

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

2023-08-13T12:52:29Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0050 results: [] ---  # whisper_charsplit_new_0050 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: 10.0022 - Validation Loss: 0.5166 - Validation Accuracy: 0.0764 - Validation Wermet: 8.4855 - Epoch: 49 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

fp16-guy/Cetus-Mix_v4_fp16_cleaned

fp16-guy

2023-08-13T12:51:38Z

0

1

null

[ "text-to-image", "region:us" ]

text-to-image

2023-07-31T14:37:04Z

--- pipeline_tag: text-to-image --- Cetus-Mix v4, but fp16/cleaned - smaller size, same result. ======== /// **[**original checkpoint link**](https://civitai.com/models/6755?modelVersionId=126564)** *(all rights to the model belong to Eagelaxis)* --- *[*grid 01*](https://huggingface.co/datasets/fp16-guy/grids/blob/main/cetusmixv4%2001%2020230807110113-111-cetusMix_v4-Euler%20a-6.png) *(1.99gb version)* *[*grid 02*](https://huggingface.co/datasets/fp16-guy/grids/blob/main/cetusmixv4%2002%2020230807110204-111-cetusMix_v4-Euler%20a-6.png) *(1.83gb version - no vae)* *[*grid 03*](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/cetusMix_v4%20inp%2001%2020230813151521-111-cetusMix_v4_fp16-Euler%20a-5.5.png) *(1.99gb inpainting version)* *[*grid 04*](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/cetusMix_v4%20inp%2002%2020230813151628-111-cetusMix_v4_fp16_no_vae-Euler%20a-5.5.png) *(1.83gb inpainting version - no vae)*

bigmorning/whisper_charsplit_new_0048

bigmorning

2023-08-13T12:43:50Z

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

2023-08-13T12:43:42Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0048 results: [] ---  # whisper_charsplit_new_0048 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: 10.0455 - Validation Loss: 0.5174 - Validation Accuracy: 0.0762 - Validation Wermet: 8.2514 - Epoch: 47 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

Ding-Qiang/Reinfore-MLP-Cartpole

Ding-Qiang

2023-08-13T12:36:09Z

0

null

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

reinforcement-learning

2023-08-13T12:35:59Z

--- tags: - CartPole-v1 - reinforce - reinforcement-learning - custom-implementation - deep-rl-class model-index: - name: Reinfore-MLP results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 457.00 +/- 87.33 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

bigmorning/whisper_charsplit_new_0045

bigmorning

2023-08-13T12:30:32Z

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

2023-08-13T12:30:23Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0045 results: [] ---  # whisper_charsplit_new_0045 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: 0.0024 - Train Accuracy: 0.0795 - Train Wermet: 10.3731 - Validation Loss: 0.5055 - Validation Accuracy: 0.0762 - Validation Wermet: 8.6347 - Epoch: 44 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

hafidzmrizky/stress-detection-500

hafidzmrizky

2023-08-13T12:30:30Z

0

peft

[ "peft", "doi:10.57967/hf/0976", "region:us" ]

null

2023-08-13T11:30:51Z

--- library_name: peft --- ## Training procedure failed model, cant delete. 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: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.5.0.dev0

bigmorning/whisper_charsplit_new_0044

bigmorning

2023-08-13T12:26:06Z

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

2023-08-13T12:25:59Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0044 results: [] ---  # whisper_charsplit_new_0044 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: 0.0023 - Train Accuracy: 0.0795 - Train Wermet: 10.4871 - Validation Loss: 0.5027 - Validation Accuracy: 0.0762 - Validation Wermet: 8.6712 - Epoch: 43 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0043

bigmorning

2023-08-13T12:21:48Z

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

2023-08-13T12:21:41Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0043 results: [] ---  # whisper_charsplit_new_0043 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: 0.0028 - Train Accuracy: 0.0795 - Train Wermet: 10.3174 - Validation Loss: 0.4968 - Validation Accuracy: 0.0762 - Validation Wermet: 8.8525 - Epoch: 42 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0042

bigmorning

2023-08-13T12:17:26Z

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

2023-08-13T12:17:18Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0042 results: [] ---  # whisper_charsplit_new_0042 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: 0.0045 - Train Accuracy: 0.0795 - Train Wermet: 10.2251 - Validation Loss: 0.5014 - Validation Accuracy: 0.0761 - Validation Wermet: 8.5737 - Epoch: 41 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

mosama/Llama-2-LoRA-Weights

mosama

2023-08-13T12:17:09Z

6

1

peft

[ "peft", "safetensors", "region:us" ]

null

2023-07-27T20:50:46Z

--- 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: True - bnb_4bit_compute_dtype: float16 ### Framework versions - PEFT 0.4.0

Pierre-Arthur/T5_small_eurlexsum

Pierre-Arthur

2023-08-13T12:16:31Z

106

0

transformers

[ "transformers", "pytorch", "tensorboard", "safetensors", "t5", "text2text-generation", "generated_from_trainer", "dataset:eur-lex-sum", "base_model:google-t5/t5-small", "base_model:finetune:google-t5/t5-small", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text2text-generation

2023-07-24T20:26:43Z

--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - eur-lex-sum metrics: - rouge model-index: - name: T5_small_eurlexsum results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: eur-lex-sum type: eur-lex-sum config: french split: test args: french metrics: - name: Rouge1 type: rouge value: 0.2 ---  # T5_small_eurlexsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eur-lex-sum dataset. It achieves the following results on the evaluation set: - Loss: 1.1159 - Rouge1: 0.2 - Rouge2: 0.1394 - Rougel: 0.1833 - Rougelsum: 0.1829 - Gen Len: 19.0 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 71 | 1.4740 | 0.1718 | 0.0935 | 0.1476 | 0.1476 | 19.0 | | No log | 2.0 | 142 | 1.2138 | 0.1915 | 0.1207 | 0.1719 | 0.1719 | 19.0 | | No log | 3.0 | 213 | 1.1368 | 0.1953 | 0.1306 | 0.1759 | 0.1759 | 19.0 | | No log | 4.0 | 284 | 1.1159 | 0.2 | 0.1394 | 0.1833 | 0.1829 | 19.0 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.0 - Tokenizers 0.13.3

lizsergeeva/vit-base-patch16-224-finetuned-vit

lizsergeeva

2023-08-13T12:13:49Z

193

0

transformers

[ "transformers", "pytorch", "tensorboard", "vit", "image-classification", "generated_from_trainer", "dataset:imagefolder", "base_model:google/vit-base-patch16-224", "base_model:finetune:google/vit-base-patch16-224", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]

image-classification

2023-08-13T08:28:07Z

--- license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-base-patch16-224-finetuned-vit 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: 0.9160530191458026 ---  # vit-base-patch16-224-finetuned-vit This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2549 - Accuracy: 0.9161 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6065 | 0.99 | 47 | 0.4006 | 0.8748 | | 0.335 | 2.0 | 95 | 0.2745 | 0.9175 | | 0.2707 | 2.97 | 141 | 0.2549 | 0.9161 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0041

bigmorning

2023-08-13T12:12:58Z

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

2023-08-13T12:12:51Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0041 results: [] ---  # whisper_charsplit_new_0041 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: 0.0120 - Train Accuracy: 0.0793 - Train Wermet: 10.4810 - Validation Loss: 0.4963 - Validation Accuracy: 0.0760 - Validation Wermet: 8.9194 - Epoch: 40 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

Evan-Lin/Bart-large-abs-amazon-allure

Evan-Lin

2023-08-13T12:06:06Z

47

0

transformers

[ "transformers", "pytorch", "bart", "text2text-generation", "trl", "reinforcement-learning", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

reinforcement-learning

2023-08-13T11:59:19Z

--- license: apache-2.0 tags: - trl - transformers - reinforcement-learning --- # TRL Model This is a [TRL language model](https://github.com/lvwerra/trl) that has been fine-tuned with reinforcement learning to guide the model outputs according to a value, function, or human feedback. The model can be used for text generation. ## Usage To use this model for inference, first install the TRL library: ```bash python -m pip install trl ``` You can then generate text as follows: ```python from transformers import pipeline generator = pipeline("text-generation", model="Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") outputs = generator("Hello, my llama is cute") ``` If you want to use the model for training or to obtain the outputs from the value head, load the model as follows: ```python from transformers import AutoTokenizer from trl import AutoModelForCausalLMWithValueHead tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpyq66vaeu/Evan-Lin/Bart-large-abs-amazon-allure") inputs = tokenizer("Hello, my llama is cute", return_tensors="pt") outputs = model(**inputs, labels=inputs["input_ids"]) ```

bigmorning/whisper_charsplit_new_0038

bigmorning

2023-08-13T11:59:47Z

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

2023-08-13T11:59:40Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0038 results: [] ---  # whisper_charsplit_new_0038 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: 0.0020 - Train Accuracy: 0.0795 - Train Wermet: 10.7428 - Validation Loss: 0.4835 - Validation Accuracy: 0.0762 - Validation Wermet: 9.0566 - Epoch: 37 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

fathyshalab/mdcsi-unternehmen-verbaende-setfit

fathyshalab

2023-08-13T11:51:49Z

5

0

sentence-transformers

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

text-classification

2023-08-13T11:50:59Z

--- license: apache-2.0 tags: - setfit - sentence-transformers - text-classification pipeline_tag: text-classification --- # C:\Users\F896D~1.SHA\AppData\Local\Temp\tmp8z_73twb\fathyshalab\mdcsi-unternehmen-verbaende-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\tmp8z_73twb\fathyshalab\mdcsi-unternehmen-verbaende-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} } ```

manvik28/FinBERT_Tuned

manvik28

2023-08-13T11:47:14Z

106

0

transformers

[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "base_model:ProsusAI/finbert", "base_model:finetune:ProsusAI/finbert", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2023-08-13T11:15:40Z

--- base_model: ProsusAI/finbert tags: - generated_from_trainer model-index: - name: FinBERT_Tuned results: [] ---  # FinBERT_Tuned This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 148 | 0.4307 | 0.7776 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0035

bigmorning

2023-08-13T11:46:46Z

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

2023-08-13T11:46:39Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0035 results: [] ---  # whisper_charsplit_new_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: 0.0130 - Train Accuracy: 0.0793 - Train Wermet: 11.1022 - Validation Loss: 0.4748 - Validation Accuracy: 0.0760 - Validation Wermet: 9.4521 - 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 | |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:| | 0.8733 | 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0034

bigmorning

2023-08-13T11:42:29Z

61

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

2023-08-13T11:42:22Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0034 results: [] ---  # whisper_charsplit_new_0034 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: 0.0047 - Train Accuracy: 0.0795 - Train Wermet: 10.7613 - Validation Loss: 0.4788 - Validation Accuracy: 0.0759 - Validation Wermet: 9.4065 - Epoch: 33 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0029

bigmorning

2023-08-13T11:20:47Z

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

2023-08-13T11:20:40Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0029 results: [] ---  # whisper_charsplit_new_0029 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: 0.0114 - Train Accuracy: 0.0794 - Train Wermet: 11.3093 - Validation Loss: 0.4431 - Validation Accuracy: 0.0758 - Validation Wermet: 9.5545 - Epoch: 28 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

bigmorning/whisper_charsplit_new_0026

bigmorning

2023-08-13T11:07:34Z

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

2023-08-13T11:07:26Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0026 results: [] ---  # whisper_charsplit_new_0026 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: 0.0142 - Train Accuracy: 0.0794 - Train Wermet: 11.3562 - Validation Loss: 0.4057 - Validation Accuracy: 0.0760 - Validation Wermet: 9.6831 - Epoch: 25 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

morell23/3dmm

morell23

2023-08-13T11:04:37Z

0

null

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

null

2023-08-13T11:03:45Z

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

Falah/Iyad_Radi_SDXL1.0_Lora

Falah

2023-08-13T11:01:53Z

3

2

diffusers

[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]

text-to-image

2023-08-13T08:27:32Z

--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a Iyad Radi tags: - text-to-image - diffusers - autotrain inference: true --- # ART Text-to-Image Generation using stabilityai/stable-diffusion-xl-base-1.0 This repository contains code and instructions for using the `stabilityai/stable-diffusion-xl-base-1.0` model from Hugging Face's Transformers library to generate images from textual descriptions. The model utilizes diffusion models for high-quality image synthesis based on the provided text prompts. ![1](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/12.png) ![2](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/2.png) ![3](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/3.png) ![4](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/4.png) ![5](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/6.png) ![6](https://huggingface.co/Falah/Iyad_Radi_SDXL1.0_Lora/resolve/main/8.png) ## Model Information - Base Model: stabilityai/stable-diffusion-xl-base-1.0 - Instance Prompt: "photo of Iyad Radi" - Tags: - text-to-image - diffusers - autotrain ## Inference To use this model for generating images from text prompts, follow these steps: 1. **Environment Setup:** Make sure you have Python installed on your system. You can also use a virtual environment for isolation. 2. **Install Dependencies:** Install the required Python packages by running the following command: ```bash pip install -r requirements.txt ``` 3.## Usage Here is an example of how you can use the `stabilityai/stable-diffusion-xl-base-1.0` model for text-to-image generation in Python using the `diffusers` library. ```python from diffusers import DiffusionPipeline import torch # Load LoRA weights lora_weights = torch.load("/path/to/lora_weights/pytorch_lora_weights.safetensors") # Initialize the DiffusionPipeline pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16) pipe.to("cuda") # Load LoRA weights into the pipeline pipe.load_lora_weights(lora_weights) # Text prompt for image generation prompt = "photo of Iyad Radi with cat in the pool" # Generate Images image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images ``` 4. **Generated Images:** The generated images will be saved in the `output_images` directory by default. ## Application in Art and Cinema Industry This model can be incredibly useful in the art and cinema movie production industry, especially for creating visuals based on textual descriptions. In the case of Aiyad Radi, an Iraqi actor and comedian, this tool can aid in visualizing character designs, scenes, and concepts before actual production. Directors, artists, and producers can utilize the generated images as a reference to plan and visualize their projects effectively. ## Credits - Model developed by [stabilityai](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) - This repository is created and maintained by [Falah.G.Saleih] ## Disclaimer Please note that the model's outputs might vary, and the generated images are based on the input text prompts. The model's behavior is influenced by its training data and might not always produce accurate or desired results. Feel free to experiment, provide feedback, and contribute to this repository if you'd like to enhance its functionality! ---

bigmorning/whisper_charsplit_new_0022

bigmorning

2023-08-13T10:50:13Z

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

2023-08-13T10:50:05Z

--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_keras_callback model-index: - name: whisper_charsplit_new_0022 results: [] ---  # whisper_charsplit_new_0022 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: 0.0318 - Train Accuracy: 0.0790 - Train Wermet: 11.6314 - Validation Loss: 0.3628 - Validation Accuracy: 0.0760 - Validation Wermet: 9.6652 - Epoch: 21 ## 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 | ### Framework versions - Transformers 4.32.0.dev0 - TensorFlow 2.12.0 - Tokenizers 0.13.3

steve-tong/opus-mt-en-zh-tw

steve-tong

2023-08-13T10:39:43Z

107

2

transformers

[ "transformers", "pytorch", "tensorboard", "marian", "text2text-generation", "generated_from_trainer", "base_model:Helsinki-NLP/opus-mt-en-zh", "base_model:finetune:Helsinki-NLP/opus-mt-en-zh", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2023-08-13T10:36:48Z

--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-zh tags: - generated_from_trainer model-index: - name: opus-mt-en-zh-tw results: [] ---  # opus-mt-en-zh-tw This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) on the None 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.0 - Tokenizers 0.13.3

snob/HeungEol-KoAlpaca-12.8B-v1.0_LoRA

snob

2023-08-13T10:38:31Z

0

peft

[ "peft", "HeungEol", "ko", "region:us" ]

null

2023-08-10T12:38:00Z

--- library_name: peft language: - ko tags: - HeungEol --- ## Training procedure ### Framework versions - PEFT 0.4.0.dev0

snob/HeungEol-KoAlpaca-12.8B-v1.0

snob

2023-08-13T10:38:08Z

13

0

transformers

[ "transformers", "pytorch", "gpt_neox", "text-generation", "HeungEol", "ko", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2023-08-10T13:56:44Z

--- tags: - HeungEol language: - ko ---