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

Loss: 0.1733
Accuracy: 0.9667

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: 0.0001
train_batch_size: 6
eval_batch_size: 6
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: 7
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.026	1.0	135	0.2289	0.9444
0.1351	2.0	270	0.1379	0.9778
0.01	3.0	405	0.2310	0.9667
0.0053	4.0	540	0.1727	0.9667
0.0002	5.0	675	0.1703	0.9667
0.0002	6.0	810	0.1722	0.9667
0.0002	7.0	945	0.1733	0.9667

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2