wav2vec2-base-balti-bft
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8899
- Wer: 0.8106
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.5551 | 6.0241 | 500 | 3.1767 | 1.0 |
| 2.0285 | 12.0482 | 1000 | 1.7825 | 0.9161 |
| 0.7834 | 18.0723 | 1500 | 1.7636 | 0.8580 |
| 0.4583 | 24.0964 | 2000 | 1.9707 | 0.8225 |
| 0.4583 | 30.0 | 2490 | 1.8899 | 0.8106 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2