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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-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- medical_data |
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- Na0s/Primock_med |
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model-index: |
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- name: Final_Medical_whisper |
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results: [] |
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metrics: |
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- cer |
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- wer |
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pipeline_tag: automatic-speech-recognition |
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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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<a href="https://ibb.co/4YRxh82"><img src="https://i.ibb.co/wwh15S7/DALL-E-2024-10-05-20-47-54-A-doctor-in-a-modern-clinical-setting-carefully-listening-to-a-patient-s.webp" alt="DALL-E-2024-10-05-20-47-54-A-doctor-in-a-modern-clinical-setting-carefully-listening-to-a-patient-s" border="0"></a> |
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# med-whisper-large-final |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the primock_data dataset. |
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## Model description |
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Fine tuned version of whisper-large-v3 through transfer learning on Doctor/Patient consultations |
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## Intended uses & limitations |
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Medical transcription |
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## Training and evaluation data |
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Na0s/Medical_Augmented_data |
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## Training procedure |
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Exhaustive transfer learning |
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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: 6 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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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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### Performance Overview: |
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\| Model Name | WER | CER | Number of Parameters | |
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|--------------------|------|------|----------------------| |
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| Whisper Tiny | 0.46 | 0.27 | 39M | |
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| Whisper Base | 0.42 | 0.26 | 74M | |
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| Whisper Small | 0.39 | 0.26 | 244M | |
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| Whisper Medium | 0.37 | 0.23 | 769M | |
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| Whisper Large v3 | 0.33 | 0.18 | 1.55B | |
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| **Whisper Medical**| **0.19** | **0.10** | **1.55B** | |
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**Performance of foundation Whispers vs Medical Whisper on the Validation set.** |
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| Model Name | WER | CER | Number of Parameters | |
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|--------------------|------|------|----------------------| |
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| **Whisper Medical**| **0.24** | **0.13** | **1.55B** | |
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**Table: Performance of Whisper Medical on the Test set.** |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
