distilhubert-finetuned-gtzan
This model is a fine-tuned version of ORromu/distilhubert-finetuned-gtzan-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.1175
- Accuracy: 0.87
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: 8
- eval_batch_size: 8
- seed: 42
- 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_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0029 | 1.0 | 113 | 1.2308 | 0.81 |
0.0052 | 2.0 | 226 | 1.2370 | 0.82 |
0.0058 | 3.0 | 339 | 1.2694 | 0.82 |
0.0003 | 4.0 | 452 | 1.1034 | 0.86 |
0.0001 | 5.0 | 565 | 1.1175 | 0.87 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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