whisper-small-CV_Fleurs_AMMI_ALFFA-sw-200hrs-v1
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: 0.4295
- Wer: 0.1732
- Cer: 0.0731
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.3655 | 1.0 | 8064 | 0.4347 | 0.3461 | 0.1533 |
| 0.4274 | 2.0 | 16128 | 0.3388 | 0.1987 | 0.0715 |
| 0.2724 | 3.0 | 24192 | 0.3215 | 0.1789 | 0.0658 |
| 0.1953 | 4.0 | 32256 | 0.3383 | 0.1737 | 0.0632 |
| 0.1563 | 5.0 | 40320 | 0.3501 | 0.1856 | 0.0728 |
| 0.1368 | 6.0 | 48384 | 0.3699 | 0.1954 | 0.0870 |
| 0.127 | 7.0 | 56448 | 0.3858 | 0.1844 | 0.0711 |
| 0.1236 | 8.0 | 64512 | 0.4001 | 0.1905 | 0.0786 |
| 0.1216 | 9.0 | 72576 | 0.4121 | 0.1982 | 0.0809 |
| 0.1204 | 10.0 | 80640 | 0.4407 | 0.2144 | 0.0916 |
| 0.1123 | 11.0 | 88704 | 0.4334 | 0.1946 | 0.0798 |
| 0.0949 | 12.0 | 96768 | 0.4478 | 0.1869 | 0.0754 |
| 0.0808 | 13.0 | 104832 | 0.4396 | 0.1862 | 0.0762 |
| 0.0702 | 14.0 | 112896 | 0.4295 | 0.1732 | 0.0731 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1