distilhubert-finetuned-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: 1.1599
- eval_accuracy: 0.8
- eval_runtime: 2.7351
- eval_samples_per_second: 36.562
- eval_steps_per_second: 4.753
- epoch: 5.0
- step: 565
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for J001/distilhubert-finetuned-gtzan
Base model
ntu-spml/distilhubert