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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-a-nomimose |
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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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# whisper-a-nomimose |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0723 |
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- Wer: 15.2655 |
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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: 0.0004 |
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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: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 132 |
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- num_epochs: 15 |
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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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| 1.3968 | 0.9217 | 100 | 0.7677 | 512.9794 | |
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| 0.3388 | 1.8387 | 200 | 0.3331 | 93.3628 | |
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| 0.2711 | 2.7558 | 300 | 0.2512 | 87.0944 | |
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| 0.2383 | 3.6728 | 400 | 0.2198 | 87.9056 | |
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| 0.2096 | 4.5899 | 500 | 0.1971 | 80.3835 | |
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| 0.2131 | 5.5069 | 600 | 0.1680 | 75.5900 | |
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| 0.1498 | 6.4240 | 700 | 0.1433 | 56.1209 | |
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| 0.1152 | 7.3410 | 800 | 0.1094 | 41.0767 | |
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| 0.0833 | 8.2581 | 900 | 0.1193 | 65.9292 | |
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| 0.0653 | 9.1751 | 1000 | 0.0728 | 25.1475 | |
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| 0.0444 | 10.0922 | 1100 | 0.0781 | 24.4100 | |
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| 0.0383 | 11.0092 | 1200 | 0.0537 | 17.6991 | |
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| 0.0269 | 11.9309 | 1300 | 0.0658 | 18.0678 | |
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| 0.0182 | 12.8479 | 1400 | 0.0641 | 19.3215 | |
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| 0.0128 | 13.7650 | 1500 | 0.0679 | 15.8555 | |
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| 0.0068 | 14.6820 | 1600 | 0.0723 | 15.2655 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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