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whisper-small-bn-09092023
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: 0.0498
- Wer: 7.7181
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: 32
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2500
- training_steps: 8000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4968 | 0.16 | 400 | 0.3922 | 44.0283 |
| 0.2059 | 0.32 | 800 | 0.1848 | 27.1190 |
| 0.1486 | 0.48 | 1200 | 0.1359 | 20.7105 |
| 0.1203 | 0.64 | 1600 | 0.1094 | 16.8171 |
| 0.1032 | 0.79 | 2000 | 0.0938 | 14.5648 |
| 0.0912 | 0.95 | 2400 | 0.0816 | 12.6067 |
| 0.0778 | 1.11 | 2800 | 0.0749 | 11.5556 |
| 0.0717 | 1.27 | 3200 | 0.0686 | 10.8017 |
| 0.0676 | 1.43 | 3600 | 0.0639 | 9.7786 |
| 0.0641 | 1.59 | 4000 | 0.0607 | 9.4620 |
| 0.0622 | 1.75 | 4400 | 0.0588 | 9.2326 |
| 0.0597 | 1.91 | 4800 | 0.0561 | 8.8085 |
| 0.0498 | 2.07 | 5200 | 0.0546 | 8.3926 |
| 0.0493 | 2.23 | 5600 | 0.0539 | 8.3443 |
| 0.0483 | 2.38 | 6000 | 0.0525 | 8.1459 |
| 0.0478 | 2.54 | 6400 | 0.0518 | 8.0740 |
| 0.0472 | 2.7 | 6800 | 0.0510 | 7.9834 |
| 0.0463 | 2.86 | 7200 | 0.0502 | 7.7784 |
| 0.0439 | 3.02 | 7600 | 0.0499 | 7.7532 |
| 0.0407 | 3.18 | 8000 | 0.0498 | 7.7181 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
