learning_rate: 5e-05
train_batch_size: 64
eval_batch_size: 64
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: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0639	1.0	125	2.0235	0.3393
1.9838	2.0	250	1.9041	0.4911
1.8621	3.0	375	1.7795	0.5238
1.7579	4.0	500	1.6965	0.5446
1.6945	5.0	625	1.6616	0.5625
1.6741	6.0	750	1.6497	0.5565
1.6042	7.0	875	1.5223	0.5685
1.4807	8.0	1000	1.4272	0.5893
1.3988	9.0	1125	1.3771	0.6101
1.3575	10.0	1250	1.3642	0.6071
1.3377	11.0	1375	1.3011	0.6220
1.2331	12.0	1500	1.2030	0.6548
1.1439	13.0	1625	1.1507	0.6577
1.0902	14.0	1750	1.1259	0.6548
1.0735	15.0	1875	1.1313	0.6726

cvmil/resnet-50_augmented-v2_fft

resnet-50_rice-leaf-disease-augmented-v2_fft