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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-tiny |
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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_tiny |
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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_tiny |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3807 |
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- Wer: 0.6449 |
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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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| 7.2094 | 0.4464 | 25 | 5.9584 | 1.7658 | |
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| 4.7209 | 0.8929 | 50 | 3.3913 | 1.1397 | |
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| 2.5229 | 1.3393 | 75 | 2.1995 | 0.9069 | |
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| 1.8454 | 1.7857 | 100 | 1.8676 | 0.8454 | |
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| 1.6015 | 2.2321 | 125 | 1.7199 | 0.7794 | |
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| 1.3786 | 2.6786 | 150 | 1.6296 | 0.7574 | |
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| 1.2147 | 3.125 | 175 | 1.5654 | 0.7432 | |
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| 1.0976 | 3.5714 | 200 | 1.5200 | 0.7135 | |
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| 1.0156 | 4.0179 | 225 | 1.4829 | 0.6759 | |
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| 0.8611 | 4.4643 | 250 | 1.4689 | 0.7050 | |
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| 0.8818 | 4.9107 | 275 | 1.4394 | 0.6585 | |
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| 0.7822 | 5.3571 | 300 | 1.4273 | 0.6669 | |
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| 0.6969 | 5.8036 | 325 | 1.4159 | 0.6481 | |
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| 0.7037 | 6.25 | 350 | 1.4057 | 0.6533 | |
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| 0.6555 | 6.6964 | 375 | 1.3991 | 0.6475 | |
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| 0.5759 | 7.1429 | 400 | 1.3927 | 0.6546 | |
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| 0.5217 | 7.5893 | 425 | 1.3936 | 0.6397 | |
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| 0.5731 | 8.0357 | 450 | 1.3849 | 0.6436 | |
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| 0.4753 | 8.4821 | 475 | 1.3839 | 0.6345 | |
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| 0.4799 | 8.9286 | 500 | 1.3816 | 0.6546 | |
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| 0.4369 | 9.375 | 525 | 1.3824 | 0.6429 | |
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| 0.4424 | 9.8214 | 550 | 1.3828 | 0.6404 | |
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| 0.4206 | 10.2679 | 575 | 1.3888 | 0.6371 | |
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| 0.3735 | 10.7143 | 600 | 1.3807 | 0.6449 | |
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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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