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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-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- yashtiwari/PaulMooney-Medical-ASR-Data |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Medical |
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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: Medical ASR |
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type: yashtiwari/PaulMooney-Medical-ASR-Data |
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metrics: |
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- name: Wer |
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type: wer |
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value: 19.526912865073616 |
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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 Medium Medical |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Medical ASR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0829 |
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- Wer: 19.5269 |
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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: 32 |
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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: 50 |
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- training_steps: 500 |
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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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| 0.3456 | 0.5405 | 100 | 0.2379 | 17.6684 | |
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| 0.1514 | 1.0811 | 200 | 0.1298 | 15.7615 | |
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| 0.0846 | 1.6216 | 300 | 0.0976 | 19.7924 | |
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| 0.0479 | 2.1622 | 400 | 0.0881 | 19.3338 | |
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| 0.0272 | 2.7027 | 500 | 0.0829 | 19.5269 | |
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### Framework versions |
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- Transformers 4.45.1 |
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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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