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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-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- physician_dictation_gpt_4_turbo |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large v3 Physician Dictation GPT 4 turbo |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Physician Dictation GPT 4 Turbo |
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type: physician_dictation_gpt_4_turbo |
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config: default |
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split: None |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.349683331087454 |
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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 Large v3 Physician Dictation GPT 4 turbo |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Physician Dictation GPT 4 Turbo dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1660 |
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- Wer: 5.3497 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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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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- training_steps: 8500 |
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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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| 0.0143 | 3.9683 | 500 | 0.1068 | 4.9948 | |
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| 0.0023 | 7.9365 | 1000 | 0.1287 | 5.0757 | |
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| 0.0026 | 11.9048 | 1500 | 0.1254 | 4.9409 | |
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| 0.0003 | 15.8730 | 2000 | 0.1298 | 4.7298 | |
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| 0.001 | 19.8413 | 2500 | 0.1312 | 5.0173 | |
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| 0.0001 | 23.8095 | 3000 | 0.1405 | 5.2374 | |
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| 0.0001 | 27.7778 | 3500 | 0.1454 | 4.9903 | |
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| 0.0001 | 31.7460 | 4000 | 0.1497 | 5.2104 | |
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| 0.0 | 35.7143 | 4500 | 0.1531 | 5.1835 | |
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| 0.0 | 39.6825 | 5000 | 0.1558 | 5.1431 | |
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| 0.0 | 43.6508 | 5500 | 0.1581 | 5.1296 | |
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| 0.0 | 47.6190 | 6000 | 0.1601 | 5.1700 | |
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| 0.0 | 51.5873 | 6500 | 0.1619 | 5.1925 | |
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| 0.0 | 55.5556 | 7000 | 0.1635 | 5.2329 | |
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| 0.0 | 59.5238 | 7500 | 0.1648 | 5.2733 | |
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| 0.0 | 63.4921 | 8000 | 0.1656 | 5.3362 | |
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| 0.0 | 67.4603 | 8500 | 0.1660 | 5.3497 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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