learning_rate: 0.0001
train_batch_size: 16
eval_batch_size: 16
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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training Loss	Epoch	Step	Accuracy	Validation Loss
1.9904	1.0	113	0.32	1.8002
1.4272	2.0	226	0.42	1.4586
1.2049	3.0	339	0.57	1.1404
0.863	4.0	452	0.59	1.1260
0.8745	5.0	565	0.66	0.9967
1.0163	6.0	678	0.71	0.9480
0.7964	7.0	791	0.72	1.1457
0.4728	8.0	904	0.75	0.8339
0.4715	9.0	1017	0.75	0.8824
0.398	10.0	1130	0.75	0.9532
0.5508	11.0	1243	0.7917	0.73
0.4541	12.0	1356	0.8301	0.76
0.4138	13.0	1469	0.8934	0.77
0.7154	14.0	1582	1.0575	0.76
0.1853	15.0	1695	1.2034	0.76
0.4277	16.0	1808	1.0570	0.78
0.2253	17.0	1921	1.1249	0.77
0.154	18.0	2034	0.9172	0.82
0.1654	19.0	2147	1.0680	0.78
0.0696	20.0	2260	1.0638	0.78

MaxLinggg/distilhubert-gtzan-dropout0.5

distilhubert-finetuned-gtzan-dropout