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--- |
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language: |
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- en |
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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: openai/whisper-small |
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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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# openai/whisper-small |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the pphuc25/EngMed dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2775 |
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- Wer: 25.8817 |
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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: 8 |
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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: 100 |
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- num_epochs: 20 |
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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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| 0.8149 | 1.0 | 3491 | 0.8968 | 43.5550 | |
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| 0.5126 | 2.0 | 6982 | 0.8805 | 35.9730 | |
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| 0.3308 | 3.0 | 10473 | 0.9173 | 36.4008 | |
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| 0.2412 | 4.0 | 13964 | 0.9814 | 33.9519 | |
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| 0.1667 | 5.0 | 17455 | 1.0400 | 31.9450 | |
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| 0.1001 | 6.0 | 20946 | 1.0903 | 33.1316 | |
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| 0.079 | 7.0 | 24437 | 1.1191 | 33.2309 | |
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| 0.0751 | 8.0 | 27928 | 1.1580 | 29.3991 | |
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| 0.0515 | 9.0 | 31419 | 1.1723 | 29.8778 | |
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| 0.0395 | 10.0 | 34910 | 1.1876 | 29.4972 | |
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| 0.0313 | 11.0 | 38401 | 1.2305 | 28.8578 | |
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| 0.0129 | 12.0 | 41892 | 1.2344 | 27.5577 | |
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| 0.0207 | 13.0 | 45383 | 1.2527 | 29.9002 | |
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| 0.0169 | 14.0 | 48874 | 1.2498 | 27.3969 | |
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| 0.0055 | 15.0 | 52365 | 1.2604 | 27.4277 | |
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| 0.003 | 16.0 | 55856 | 1.2627 | 26.8923 | |
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| 0.0011 | 17.0 | 59347 | 1.2700 | 26.9135 | |
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| 0.0013 | 18.0 | 62838 | 1.2695 | 27.4785 | |
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| 0.0001 | 19.0 | 66329 | 1.2804 | 26.2836 | |
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| 0.0 | 20.0 | 69820 | 1.2775 | 25.8817 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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