jazzhong1_medical_whisper_cut_small_2
This model is a fine-tuned version of openai/whisper-small on the voice_medical dataset. It achieves the following results on the evaluation set:
- Loss: 0.3032
- Cer: 8.2941
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-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.3147 | 0.9381 | 1000 | 0.3346 | 13.2283 |
| 0.2144 | 1.8762 | 2000 | 0.2960 | 9.8543 |
| 0.1068 | 2.8143 | 3000 | 0.2950 | 9.7808 |
| 0.0379 | 3.7523 | 4000 | 0.2990 | 8.5810 |
| 0.0097 | 4.6904 | 5000 | 0.3032 | 8.2941 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-small