wav2vec2-ASR-google-colab
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: 2.8244
- Wer: 0.9468
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 |
|---|---|---|---|---|
| 8.2357 | 2.9940 | 500 | 3.2836 | 0.9993 |
| 2.8848 | 5.9880 | 1000 | 2.3607 | 1.0030 |
| 1.8264 | 8.9820 | 1500 | 2.2085 | 0.9963 |
| 1.2993 | 11.9760 | 2000 | 2.1122 | 0.9700 |
| 0.9819 | 14.9701 | 2500 | 2.4227 | 0.9700 |
| 0.8020 | 17.9641 | 3000 | 2.4763 | 0.9446 |
| 0.6464 | 20.9581 | 3500 | 2.6294 | 0.9618 |
| 0.5507 | 23.9521 | 4000 | 2.7564 | 0.9483 |
| 0.4691 | 26.9461 | 4500 | 2.8887 | 0.9461 |
| 0.4202 | 29.9401 | 5000 | 2.8239 | 0.9468 |
| 0.4202 | 30.0 | 5010 | 2.8244 | 0.9468 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2