whisper-small-bangla-asr-dlsprint
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1195
- Wer: 0.3900
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1821 | 0.16 | 500 | 0.1695 | 0.5006 |
| 0.1401 | 0.31 | 1000 | 0.1313 | 0.4109 |
| 0.1257 | 0.47 | 1500 | 0.1195 | 0.3900 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.10.0+cu128
- Datasets 2.18.0
- Tokenizers 0.15.2