distilhubert-finetuned-gtzan-lora-dropout0.25-split3-full

• Loss: 1.1294
• Accuracy: 0.8433

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 0.001
• 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: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Framework versions

• PEFT 0.15.2
• Transformers 4.51.3
• Pytorch 2.6.0
• Datasets 3.3.2
• Tokenizers 0.21.0