whisper_fine_tune_Nataraj
This model is a fine-tuned version of openai/whisper-small on the Medical Speech, Transcription, and Intent dataset. It achieves the following results on the evaluation set:
- Loss: 0.1107
- Wer: 7.1807
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 600
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.6938 | 0.28 | 100 | 0.6197 | 45.9080 |
0.1912 | 0.56 | 200 | 0.2053 | 12.1040 |
0.1152 | 0.85 | 300 | 0.1555 | 9.5495 |
0.0519 | 1.13 | 400 | 0.1268 | 8.3883 |
0.0557 | 1.41 | 500 | 0.1156 | 7.6173 |
0.0536 | 1.69 | 600 | 0.1107 | 7.1807 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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Evaluation results
- Wer on Medical Speech, Transcription, and Intentself-reported7.181