swinv2-tiny-patch4-window8-256-dmae-humeda-DAV70

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 4e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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: 45
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0983	1.0	15	1.0283	0.5371
0.8777	2.0	30	0.7419	0.7371
0.69	3.0	45	0.4895	0.8
0.4806	4.0	60	0.4128	0.8114
0.436	5.0	75	0.3188	0.8743
0.3499	6.0	90	0.3870	0.8286
0.3754	7.0	105	0.3523	0.8857
0.2954	8.0	120	0.3168	0.8686
0.3075	9.0	135	0.3359	0.8743
0.2405	10.0	150	0.3676	0.8514
0.2716	11.0	165	0.3715	0.8343
0.2414	12.0	180	0.3665	0.8971
0.2116	13.0	195	0.3554	0.88
0.2134	14.0	210	0.4033	0.8686
0.2058	15.0	225	0.4590	0.84
0.1925	16.0	240	0.4088	0.8457
0.2004	17.0	255	0.4399	0.8743
0.1541	18.0	270	0.3550	0.8686
0.2124	19.0	285	0.3603	0.8914
0.1975	20.0	300	0.3655	0.9029
0.15	21.0	315	0.3863	0.8971
0.1796	22.0	330	0.3288	0.9029
0.1307	23.0	345	0.3781	0.8857
0.1721	24.0	360	0.3938	0.9029
0.1161	25.0	375	0.4481	0.88
0.1096	26.0	390	0.4351	0.8686
0.1203	27.0	405	0.4337	0.8686
0.1481	28.0	420	0.5295	0.8457
0.1295	29.0	435	0.4443	0.8857
0.1234	30.0	450	0.4490	0.8914
0.1368	31.0	465	0.5945	0.8629
0.1024	32.0	480	0.5224	0.88
0.1255	33.0	495	0.4385	0.9029
0.1285	34.0	510	0.5272	0.8971
0.1316	35.0	525	0.4936	0.8971
0.1042	36.0	540	0.5399	0.8971
0.1028	37.0	555	0.5199	0.8857
0.0923	38.0	570	0.4813	0.9029
0.1	39.0	585	0.5702	0.8914
0.0943	40.0	600	0.5477	0.8971
0.1135	41.0	615	0.5281	0.8971
0.1021	42.0	630	0.5353	0.8971