Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.9968	1.0	32	1.9113	0.2754	0.2518	0.2754	0.2280
1.4178	2.0	64	1.2704	0.5049	0.5149	0.5049	0.4900
1.1751	3.0	96	1.1116	0.5841	0.5891	0.5841	0.5787
1.0127	4.0	128	1.0237	0.6162	0.6335	0.6162	0.6141
0.9969	5.0	160	0.9890	0.6259	0.6294	0.6259	0.6150
0.9376	6.0	192	0.9768	0.6190	0.6335	0.6190	0.6183
0.8299	7.0	224	0.9579	0.6357	0.6339	0.6357	0.6282
0.7645	8.0	256	0.9366	0.6489	0.6559	0.6489	0.6474
0.7944	9.0	288	0.9303	0.6443	0.6494	0.6443	0.6447
0.7334	10.0	320	0.9510	0.6546	0.6634	0.6546	0.6523
0.6596	11.0	352	0.9369	0.6449	0.6528	0.6449	0.6428
0.6781	12.0	384	0.9717	0.6368	0.6513	0.6368	0.6360
0.5688	13.0	416	0.9509	0.6540	0.6531	0.6540	0.6495
0.5766	14.0	448	0.9485	0.6615	0.6655	0.6615	0.6601
0.5529	15.0	480	0.9590	0.6569	0.6561	0.6569	0.6538
0.4998	16.0	512	0.9677	0.6512	0.6514	0.6512	0.6488
0.4908	17.0	544	0.9670	0.6638	0.6645	0.6638	0.6616
0.4682	18.0	576	0.9635	0.6678	0.6707	0.6678	0.6684
0.4761	19.0	608	0.9680	0.6667	0.6674	0.6667	0.6658
0.4161	20.0	640	0.9701	0.6713	0.6719	0.6713	0.6701
0.4295	21.0	672	0.9712	0.6718	0.6698	0.6718	0.6703
0.434	22.0	704	0.9755	0.6707	0.6705	0.6707	0.6690

Mauregato/vit-base-patch16-224-best-finetuned-on-affectnet_short

vit-base-patch16-224-best-finetuned-on-affectnet_short