dynann/whisper-small-kh-final
This model is a fine-tuned version of openai/whisper-small on the KHM ASR Cultural dataset. It achieves the following results on the evaluation set:
- Loss: 0.3025
- Wer: 102.0349
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: 4
- 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
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3845 | 7.6923 | 500 | 0.4710 | 103.3430 |
| 0.2341 | 15.3846 | 1000 | 0.3025 | 102.0349 |
Framework versions
- Transformers 5.7.0
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2