Whisper Base Bengali
This model is a fine-tuned version of arun100/whisper-base-bn on the google/fleurs bn_in dataset. It achieves the following results on the evaluation set:
- Loss: 0.2509
- Wer: 43.6760
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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2889 | 79.0 | 1000 | 0.2730 | 45.0242 |
| 0.2527 | 159.0 | 2000 | 0.2593 | 44.4617 |
| 0.2306 | 239.0 | 3000 | 0.2539 | 44.0616 |
| 0.2191 | 319.0 | 4000 | 0.2515 | 43.7367 |
| 0.2164 | 399.0 | 5000 | 0.2509 | 43.6760 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0