wav2vec2-base-timit-phoneme-demo-google-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the timit_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4174
- Per: 0.1346
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 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: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|---|---|---|---|---|
| 3.2638 | 1.0040 | 500 | 2.8755 | 0.7958 |
| 1.0067 | 2.0080 | 1000 | 0.6757 | 0.1643 |
| 0.6595 | 3.0120 | 1500 | 0.5000 | 0.1494 |
| 0.6451 | 4.0161 | 2000 | 0.4453 | 0.1398 |
| 0.3795 | 5.0201 | 2500 | 0.4174 | 0.1346 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0