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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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model-index: |
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- name: wsj0-full-supervised |
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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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# wsj0-full-supervised |
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This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0623 |
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- Wer: 0.0343 |
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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: 0.0001 |
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- train_batch_size: 12 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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_steps: 1000 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 5.517 | 0.86 | 500 | 2.9475 | 1.0 | |
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| 2.2387 | 1.72 | 1000 | 0.4004 | 0.3498 | |
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| 0.3081 | 2.57 | 1500 | 0.1362 | 0.1159 | |
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| 0.1744 | 3.43 | 2000 | 0.1125 | 0.0929 | |
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| 0.1285 | 4.29 | 2500 | 0.0894 | 0.0727 | |
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| 0.1015 | 5.15 | 3000 | 0.0852 | 0.0642 | |
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| 0.0811 | 6.0 | 3500 | 0.0789 | 0.0614 | |
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| 0.0748 | 6.86 | 4000 | 0.0746 | 0.0529 | |
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| 0.0639 | 7.72 | 4500 | 0.0714 | 0.0481 | |
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| 0.0606 | 8.58 | 5000 | 0.0698 | 0.0489 | |
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| 0.0525 | 9.43 | 5500 | 0.0747 | 0.0464 | |
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| 0.0489 | 10.29 | 6000 | 0.0594 | 0.0396 | |
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| 0.0419 | 11.15 | 6500 | 0.0600 | 0.0359 | |
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| 0.0414 | 12.01 | 7000 | 0.0612 | 0.0412 | |
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| 0.0383 | 12.86 | 7500 | 0.0676 | 0.0392 | |
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| 0.0352 | 13.72 | 8000 | 0.0626 | 0.0388 | |
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| 0.034 | 14.58 | 8500 | 0.0699 | 0.0372 | |
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| 0.0309 | 15.44 | 9000 | 0.0807 | 0.0420 | |
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| 0.0295 | 16.3 | 9500 | 0.0796 | 0.0396 | |
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| 0.0273 | 17.15 | 10000 | 0.0716 | 0.0376 | |
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| 0.0271 | 18.01 | 10500 | 0.0657 | 0.0384 | |
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| 0.0251 | 18.87 | 11000 | 0.0585 | 0.0351 | |
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| 0.024 | 19.73 | 11500 | 0.0557 | 0.0347 | |
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| 0.0252 | 20.58 | 12000 | 0.0609 | 0.0327 | |
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| 0.0231 | 21.44 | 12500 | 0.0720 | 0.0368 | |
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| 0.0202 | 22.3 | 13000 | 0.0625 | 0.0343 | |
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| 0.0195 | 23.16 | 13500 | 0.0635 | 0.0372 | |
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| 0.0201 | 24.01 | 14000 | 0.0582 | 0.0335 | |
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| 0.0183 | 24.87 | 14500 | 0.0562 | 0.0343 | |
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| 0.0183 | 25.73 | 15000 | 0.0629 | 0.0335 | |
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| 0.0175 | 26.59 | 15500 | 0.0593 | 0.0323 | |
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| 0.017 | 27.44 | 16000 | 0.0631 | 0.0339 | |
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| 0.0162 | 28.3 | 16500 | 0.0597 | 0.0335 | |
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| 0.0169 | 29.16 | 17000 | 0.0623 | 0.0343 | |
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### Framework versions |
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- Transformers 4.14.1 |
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- Pytorch 1.10.2 |
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- Datasets 1.18.2 |
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- Tokenizers 0.10.3 |
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