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--- |
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library_name: transformers |
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license: mit |
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base_model: distil-whisper/distil-large-v3 |
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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: throatmic_subvocalization_whisper_distil-large-v3 |
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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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# throatmic_subvocalization_whisper_distil-large-v3 |
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This model is a fine-tuned version of [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8634 |
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- Wer: 0.3202 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 50 |
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- training_steps: 800 |
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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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| 4.8931 | 0.4464 | 25 | 3.3920 | 0.7749 | |
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| 2.3126 | 0.8929 | 50 | 1.2760 | 0.4554 | |
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| 0.8156 | 1.3393 | 75 | 0.9349 | 0.3648 | |
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| 0.7011 | 1.7857 | 100 | 0.7822 | 0.3040 | |
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| 0.5483 | 2.2321 | 125 | 0.7531 | 0.2969 | |
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| 0.3743 | 2.6786 | 150 | 0.7529 | 0.3525 | |
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| 0.2984 | 3.125 | 175 | 0.7249 | 0.3402 | |
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| 0.1953 | 3.5714 | 200 | 0.7531 | 0.3182 | |
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| 0.1811 | 4.0179 | 225 | 0.7380 | 0.2788 | |
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| 0.0976 | 4.4643 | 250 | 0.7636 | 0.3234 | |
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| 0.1152 | 4.9107 | 275 | 0.7868 | 0.2962 | |
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| 0.0694 | 5.3571 | 300 | 0.8141 | 0.3072 | |
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| 0.0489 | 5.8036 | 325 | 0.8237 | 0.3279 | |
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| 0.0459 | 6.25 | 350 | 0.8634 | 0.3202 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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