wav2vec2-base-yo-big-dataset-demo-colab-1
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: nan
- Wer: 0.9926
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 194.8586 | 3.8627 | 100 | nan | 0.9926 |
| 0.0 | 7.7059 | 200 | nan | 0.9926 |
| 0.0 | 11.5490 | 300 | nan | 0.9926 |
| 0.0 | 15.3922 | 400 | nan | 0.9926 |
| 0.0 | 19.2353 | 500 | nan | 0.9926 |
| 0.0 | 23.0784 | 600 | nan | 0.9926 |
| 0.0 | 26.9412 | 700 | nan | 0.9926 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2