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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: finetuned_wav2vec2.0-base-on-IEMOCAP_1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# finetuned_wav2vec2.0-base-on-IEMOCAP_1 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6629 |
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- Accuracy: 0.6673 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.2016 | 1.0 | 111 | 1.1443 | 0.5 | |
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| 1.0629 | 2.0 | 222 | 0.9839 | 0.5830 | |
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| 0.8111 | 2.99 | 333 | 0.9295 | 0.6233 | |
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| 0.7455 | 4.0 | 445 | 0.9119 | 0.6570 | |
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| 0.4654 | 5.0 | 556 | 0.7440 | 0.7186 | |
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| 0.3648 | 6.0 | 667 | 0.8359 | 0.7007 | |
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| 0.307 | 6.99 | 778 | 0.7964 | 0.7377 | |
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| 0.2823 | 8.0 | 890 | 0.8882 | 0.7321 | |
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| 0.1869 | 9.0 | 1001 | 1.0550 | 0.7186 | |
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| 0.2022 | 10.0 | 1112 | 1.0110 | 0.7231 | |
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| 0.0522 | 10.99 | 1223 | 1.1135 | 0.7265 | |
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| 0.058 | 12.0 | 1335 | 1.1275 | 0.7489 | |
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| 0.0465 | 13.0 | 1446 | 1.1479 | 0.7545 | |
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| 0.0321 | 14.0 | 1557 | 1.1885 | 0.7534 | |
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| 0.0331 | 14.97 | 1665 | 1.2301 | 0.7511 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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