whisper-small-alif
This model is a fine-tuned version of openai/whisper-small on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2298
- Wer: 0.0
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 4 | 3.3199 | 100.0 |
| 6.3947 | 2.0 | 8 | 3.2238 | 100.0 |
| 6.3570 | 3.0 | 12 | 1.7064 | 100.0 |
| 3.6043 | 4.0 | 16 | 0.8654 | 75.0 |
| 1.3034 | 5.0 | 20 | 0.1943 | 0.0 |
| 1.3034 | 6.0 | 24 | 0.0241 | 0.0 |
| 0.1757 | 7.0 | 28 | 0.0071 | 0.0 |
| 0.0055 | 8.0 | 32 | 0.0000 | 0.0 |
| 0.0002 | 9.0 | 36 | 0.0000 | 0.0 |
| 0.0000 | 10.0 | 40 | 0.0000 | 0.0 |
| 0.0000 | 11.0 | 44 | 0.0000 | 0.0 |
| 0.0000 | 12.0 | 48 | 0.0000 | 0.0 |
| 0.0000 | 13.0 | 52 | 0.0000 | 0.0 |
| 0.0000 | 14.0 | 56 | 0.0000 | 0.0 |
| 0.0000 | 15.0 | 60 | 0.0000 | 0.0 |
| 0.0000 | 16.0 | 64 | 0.0000 | 0.0 |
| 0.0000 | 17.0 | 68 | 0.0000 | 0.0 |
| 0.0000 | 18.0 | 72 | 0.0000 | 0.0 |
| 0.0000 | 19.0 | 76 | 0.0000 | 0.0 |
| 0.0000 | 20.0 | 80 | 0.0000 | 0.0 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2