learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.125	1.0	57	2.0967	0.46
1.1862	2.0	114	1.0739	0.73
0.7055	3.0	171	0.7744	0.81
0.445	4.0	228	0.5283	0.86
0.2788	5.0	285	0.4848	0.89
0.0948	6.0	342	0.5192	0.89
0.0709	7.0	399	0.4638	0.9
0.0818	8.0	456	0.4345	0.91
0.0835	9.0	513	0.4638	0.92
0.0063	10.0	570	0.4175	0.94
0.0052	11.0	627	0.4807	0.93
0.0055	12.0	684	0.4814	0.93
0.0235	13.0	741	0.4796	0.93
0.0043	14.0	798	0.4793	0.93
0.0044	15.0	855	0.4795	0.93

dzur658/MERT-v1-330M-finetuned-gtzan

m-a-p/MERT-v1-330M-finetuned-gtzan