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openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2790
- Wer: 8.3986
- Cer: 5.2582
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: 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1691 | 1.01 | 1000 | 0.1871 | 10.1740 | 6.3509 |
| 0.0916 | 2.02 | 2000 | 0.1691 | 8.9797 | 5.5499 |
| 0.0452 | 3.03 | 3000 | 0.1902 | 8.9814 | 5.5867 |
| 0.0213 | 4.04 | 4000 | 0.2062 | 8.9375 | 5.6531 |
| 0.0096 | 5.05 | 5000 | 0.2284 | 8.7331 | 5.6202 |
| 0.0041 | 6.05 | 6000 | 0.2395 | 8.5051 | 5.3009 |
| 0.0022 | 7.06 | 7000 | 0.2535 | 8.5507 | 5.3640 |
| 0.001 | 8.07 | 8000 | 0.2656 | 8.5557 | 5.3791 |
| 0.0006 | 9.08 | 9000 | 0.2721 | 8.4037 | 5.2739 |
| 0.0004 | 10.09 | 10000 | 0.2790 | 8.3986 | 5.2582 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
