wav2vec2bert-bengali-clean-audio-1e5
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9749
- Wer: 0.4271
- Cer: 0.1097
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 100
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 11.3054 | 1.2675 | 100 | 5.1693 | 1.0430 | 0.6356 |
| 3.2001 | 2.5350 | 200 | 1.6331 | 0.6407 | 0.1828 |
| 2.4474 | 3.8025 | 300 | 1.2845 | 0.5187 | 0.1418 |
| 1.8174 | 5.0637 | 400 | 1.1087 | 0.4875 | 0.1327 |
| 1.4476 | 6.3312 | 500 | 1.0288 | 0.4508 | 0.1175 |
| 1.3777 | 7.5987 | 600 | 0.9930 | 0.4278 | 0.1123 |
| 1.1010 | 8.8662 | 700 | 0.9749 | 0.4271 | 0.1097 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2