distilhubert-finetuned-gtzan-v3-finetuned-gtzan

This model is a fine-tuned version of MariaK/distilhubert-finetuned-gtzan-v3 on the GTZAN dataset. It achieves the following results on the evaluation set:

• Loss: 0.4764
• Accuracy: 0.88

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0791	0.99	56	0.5451	0.82
0.0677	2.0	113	0.4793	0.88
0.0329	2.97	168	0.4764	0.88

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3