Whisper Tajik
This model is a fine-tuned version of openai/whisper-small on the CUSTOM dataset. It achieves the following results on the evaluation set:
- Loss: 0.4538
- Wer: 18.9518
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0245 | 6.2893 | 1000 | 0.3726 | 20.9634 |
| 0.0043 | 12.5786 | 2000 | 0.4167 | 20.5318 |
| 0.0003 | 18.8679 | 3000 | 0.4431 | 19.2062 |
| 0.0002 | 25.1572 | 4000 | 0.4538 | 18.9518 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0