distilhubert-finetuned-gtzan-v2-finetuned-gtzan
This model is a fine-tuned version of MariaK/distilhubert-finetuned-gtzan-v2 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.1561
- Accuracy: 0.9556
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1145 | 1.0 | 51 | 0.1565 | 0.9556 |
| 0.0774 | 2.0 | 102 | 0.1561 | 0.9556 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for HaythamB/distilhubert-finetuned-gtzan-v2-finetuned-gtzan
Base model
MariaK/distilhubert-finetuned-gtzan-v2