ndizi-whisper-small-optimized
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7279
- Wer: 0.3118
- Cer: 0.1242
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 200
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.8495 | 1.0 | 268 | 0.6232 | 0.3815 | 0.1517 |
| 0.4653 | 2.0 | 536 | 0.5281 | 0.3612 | 0.1496 |
| 0.3145 | 3.0 | 804 | 0.5185 | 0.3169 | 0.1267 |
| 0.1865 | 4.0 | 1072 | 0.5390 | 0.3227 | 0.1308 |
| 0.1128 | 5.0 | 1340 | 0.5657 | 0.3236 | 0.1284 |
| 0.0654 | 6.0 | 1608 | 0.6066 | 0.3150 | 0.1245 |
| 0.0276 | 7.0 | 1876 | 0.6278 | 0.3210 | 0.1302 |
| 0.0194 | 8.0 | 2144 | 0.6498 | 0.3197 | 0.1253 |
| 0.0078 | 9.0 | 2412 | 0.6749 | 0.3240 | 0.1292 |
| 0.0052 | 10.0 | 2680 | 0.6909 | 0.3154 | 0.1271 |
| 0.0024 | 11.0 | 2948 | 0.7041 | 0.3107 | 0.1232 |
| 0.0028 | 12.0 | 3216 | 0.7126 | 0.3165 | 0.1258 |
| 0.0016 | 13.0 | 3484 | 0.7215 | 0.3142 | 0.1255 |
| 0.0012 | 14.0 | 3752 | 0.7256 | 0.3120 | 0.1241 |
| 0.0011 | 15.0 | 4020 | 0.7279 | 0.3118 | 0.1242 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1