Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.4066	0.99	20	1.2430	0.5124	0.5141	0.5124	0.4371
1.0813	1.99	40	0.8244	0.6893	0.6834	0.6893	0.6616
0.8392	2.99	60	0.6334	0.7612	0.7670	0.7612	0.7570
0.7065	3.99	80	0.5819	0.7767	0.7799	0.7767	0.7672
0.5751	4.99	100	0.5365	0.8176	0.8216	0.8176	0.8130
0.4896	5.99	120	0.4943	0.8308	0.8257	0.8308	0.8265
0.4487	6.99	140	0.5399	0.8107	0.8069	0.8107	0.8054
0.4349	7.99	160	0.4892	0.8300	0.8285	0.8300	0.8273
0.43	8.99	180	0.4984	0.8454	0.8465	0.8454	0.8426
0.4372	9.99	200	0.5573	0.8192	0.8221	0.8192	0.8157
0.3994	10.99	220	0.5158	0.8300	0.8284	0.8300	0.8281
0.3883	11.99	240	0.5495	0.8354	0.8317	0.8354	0.8314
0.406	12.99	260	0.5298	0.8284	0.8285	0.8284	0.8246
0.3355	13.99	280	0.5401	0.8393	0.8346	0.8393	0.8357
0.395	14.99	300	0.5915	0.8308	0.8278	0.8308	0.8261
0.3612	15.99	320	0.5852	0.8408	0.8378	0.8408	0.8368
0.3765	16.99	340	0.5509	0.8385	0.8351	0.8385	0.8356
0.3688	17.99	360	0.5668	0.8416	0.8398	0.8416	0.8387
0.3503	18.99	380	0.5626	0.8393	0.8371	0.8393	0.8365
0.3611	19.99	400	0.5595	0.8346	0.8327	0.8346	0.8322

jayanta/cvt-13-384-in22k-FV-finetuned-memes

cvt-13-384-in22k-FV-finetuned-memes