wav2vec2-base_music_speech_both_classification
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0586
- Accuracy: 0.9847
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9458 | 1.0 | 66 | 0.8468 | 0.7405 |
| 0.3785 | 2.0 | 132 | 0.2951 | 0.9771 |
| 0.1762 | 3.0 | 198 | 0.2639 | 0.9313 |
| 0.134 | 4.0 | 264 | 0.1084 | 0.9771 |
| 0.0782 | 5.0 | 330 | 0.0877 | 0.9771 |
| 0.0568 | 6.0 | 396 | 0.0912 | 0.9771 |
| 0.0122 | 7.0 | 462 | 0.4056 | 0.9198 |
| 0.059 | 8.0 | 528 | 0.0586 | 0.9847 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3