learning_rate: 5e-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: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1579	1.0	113	2.0599	0.49
1.414	2.0	226	1.4245	0.66
1.1784	3.0	339	1.1034	0.65
0.7209	4.0	452	0.7965	0.78
0.5967	5.0	565	0.7356	0.78
0.3644	6.0	678	0.5675	0.82
0.2092	7.0	791	0.5001	0.86
0.0647	8.0	904	0.6535	0.83
0.1354	9.0	1017	0.4772	0.88
0.0525	10.0	1130	0.6393	0.86
0.0127	11.0	1243	0.6587	0.87
0.0059	12.0	1356	0.6669	0.84
0.0052	13.0	1469	0.6354	0.86
0.0044	14.0	1582	0.7918	0.82
0.0035	15.0	1695	0.7577	0.83
0.0035	16.0	1808	0.7344	0.82
0.0033	17.0	1921	0.7079	0.84
0.0031	18.0	2034	0.7367	0.84
0.0032	19.0	2147	0.7150	0.84
0.0034	20.0	2260	0.7144	0.84

ParitKansal/distilhubert-finetuned-gtzan

distilhubert-finetuned-gtzan