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wav2vec2-base-finetuned-gtzan
This model is a fine-tuned version of facebook/wav2vec2-base on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.8270
- Accuracy: 0.83
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0547 | 0.99 | 56 | 2.0066 | 0.45 |
| 1.7392 | 2.0 | 113 | 1.5974 | 0.57 |
| 1.5689 | 2.99 | 169 | 1.4470 | 0.59 |
| 1.2626 | 4.0 | 226 | 1.2541 | 0.66 |
| 1.1188 | 4.99 | 282 | 1.2458 | 0.65 |
| 0.9776 | 6.0 | 339 | 0.9830 | 0.75 |
| 0.9396 | 6.99 | 395 | 0.8980 | 0.74 |
| 0.8677 | 8.0 | 452 | 0.8398 | 0.8 |
| 0.8194 | 8.99 | 508 | 0.7868 | 0.82 |
| 0.7274 | 9.91 | 560 | 0.8270 | 0.83 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
