Whisper Small Medical
This model is a fine-tuned version of openai/whisper-large-v3 on the OUTCOMESAI/medical_speech_corpus zh-en dataset. It achieves the following results on the evaluation set:
- Loss: 0.6201
- Wer: 44.2553
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.4337 | 25.0 | 50 | 0.6201 | 44.2553 |
| 5.7447 | 50.0 | 100 | 0.6113 | 51.2340 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 3.1.1.dev0
- Tokenizers 0.21.0
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Model tree for saurabhy27-outcomes/whisper-small-medical
Base model
openai/whisper-large-v3Dataset used to train saurabhy27-outcomes/whisper-small-medical
Evaluation results
- Wer on OUTCOMESAI/medical_speech_corpus zh-enself-reported44.255