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whisper-small
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1540
- Wer: 13.8083
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 2.3889 | 0.0 | 1 | 3.1044 | 49.3314 |
| 0.174 | 0.29 | 1000 | 0.2346 | 20.9796 |
| 0.1521 | 0.58 | 2000 | 0.1945 | 17.9616 |
| 0.1301 | 0.88 | 3000 | 0.1747 | 16.2713 |
| 0.0951 | 1.17 | 4000 | 0.1684 | 15.3962 |
| 0.0955 | 1.46 | 5000 | 0.1606 | 14.7689 |
| 0.096 | 1.75 | 6000 | 0.1561 | 14.3492 |
| 0.0668 | 2.04 | 7000 | 0.1554 | 14.0853 |
| 0.062 | 2.34 | 8000 | 0.1555 | 14.0599 |
| 0.0664 | 2.63 | 9000 | 0.1548 | 13.9191 |
| 0.0678 | 2.92 | 10000 | 0.1540 | 13.8083 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3
