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distilhubert-finetuned-gtzan_2
This model is a fine-tuned version of avojarot/distilhubert-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.4655
- Accuracy: 0.91
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
- 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 |
|---|---|---|---|---|
| 0.1362 | 1.0 | 113 | 0.3293 | 0.94 |
| 0.0329 | 2.0 | 226 | 0.7029 | 0.84 |
| 0.144 | 3.0 | 339 | 0.4230 | 0.9 |
| 0.0056 | 4.0 | 452 | 0.4720 | 0.89 |
| 0.003 | 5.0 | 565 | 0.4619 | 0.91 |
| 0.0092 | 6.0 | 678 | 0.4495 | 0.92 |
| 0.0023 | 7.0 | 791 | 0.4328 | 0.93 |
| 0.0017 | 8.0 | 904 | 0.4514 | 0.91 |
| 0.0016 | 9.0 | 1017 | 0.4479 | 0.93 |
| 0.0015 | 10.0 | 1130 | 0.4655 | 0.91 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
