distilhubert-finetuned-hyperparam-gtzan
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6969
- eval_model_preparation_time: 0.0031
- eval_accuracy: 0.86
- eval_runtime: 69.8954
- eval_samples_per_second: 1.431
- eval_steps_per_second: 0.186
- step: 0
Model description
More information needed
Intended uses & limitations
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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: 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: 0.2
- num_epochs: 30
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
ntu-spml/distilhubert