Wav2Vec2_Finetuned
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: 0.9886
- Accuracy: 0.7247
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use 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_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1066 | 0.9863 | 54 | 2.0550 | 0.3211 |
| 1.7945 | 1.9817 | 108 | 1.8463 | 0.3858 |
| 1.5042 | 2.9772 | 162 | 1.6106 | 0.4911 |
| 1.3307 | 3.9909 | 217 | 1.3656 | 0.6199 |
| 1.1295 | 4.9863 | 271 | 1.2506 | 0.6417 |
| 1.0127 | 5.9817 | 325 | 1.2754 | 0.6211 |
| 0.949 | 6.9772 | 379 | 1.0925 | 0.7041 |
| 0.8618 | 7.9909 | 434 | 1.0693 | 0.7052 |
| 0.7838 | 8.9863 | 488 | 1.0308 | 0.7138 |
| 0.7813 | 9.9452 | 540 | 0.9886 | 0.7247 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3