Whisper Small - tibetan v1.0.0
This model is a fine-tuned version of openai/whisper-small on the stt-test-v1.0.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1309
- Cer: 38.5374
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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 0.5037 | 0.1249 | 1000 | 48.0593 | 0.2382 |
| 0.3617 | 0.2499 | 2000 | 0.1749 | 41.4889 |
| 0.3172 | 0.3748 | 3000 | 0.1483 | 40.1784 |
| 0.2864 | 0.4998 | 4000 | 0.1374 | 39.0413 |
| 0.2645 | 0.6247 | 5000 | 0.1309 | 38.5374 |
Framework versions
- Transformers 5.6.2
- Pytorch 2.11.0+cu126
- Datasets 4.8.4
- Tokenizers 0.22.2