Whisper Small EN-BN ASR
This model is a fine-tuned version of openai/whisper-small on the Indic Bengali dataset. It achieves the following results on the evaluation set:
- Loss: 0.0514
- Wer: 17.3903
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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_ratio: 0.03
- training_steps: 8000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1073 | 0.3811 | 1000 | 0.0995 | 31.1461 |
| 0.0831 | 0.7622 | 2000 | 0.0781 | 26.3300 |
| 0.0525 | 1.1433 | 3000 | 0.0689 | 24.3359 |
| 0.0435 | 1.5244 | 4000 | 0.0605 | 21.2507 |
| 0.0391 | 1.9055 | 5000 | 0.0543 | 19.3544 |
| 0.018 | 2.2866 | 6000 | 0.0564 | 18.5793 |
| 0.0175 | 2.6677 | 7000 | 0.0519 | 18.1804 |
| 0.0063 | 3.0488 | 8000 | 0.0514 | 17.3903 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.4.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1