Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.3821	0.99	20	1.2780	0.4969	0.5083	0.4969	0.4458
1.0785	1.99	40	0.8633	0.6669	0.6658	0.6669	0.6500
0.8862	2.99	60	0.7110	0.7218	0.7258	0.7218	0.7013
0.665	3.99	80	0.5515	0.8045	0.8137	0.8045	0.8050
0.6056	4.99	100	0.5956	0.7960	0.8041	0.7960	0.7846
0.4779	5.99	120	0.6229	0.7937	0.7945	0.7937	0.7857
0.4554	6.99	140	0.5355	0.8099	0.8126	0.8099	0.8086
0.4249	7.99	160	0.5447	0.8269	0.8275	0.8269	0.8236
0.4313	8.99	180	0.5530	0.8153	0.8140	0.8153	0.8132
0.423	9.99	200	0.5346	0.8238	0.8230	0.8238	0.8223
0.3997	10.99	220	0.5413	0.8338	0.8347	0.8338	0.8338
0.4095	11.99	240	0.5999	0.8207	0.8231	0.8207	0.8177
0.3979	12.99	260	0.5632	0.8284	0.8255	0.8284	0.8250
0.3408	13.99	280	0.5725	0.8207	0.8198	0.8207	0.8196
0.3828	14.99	300	0.5631	0.8277	0.8258	0.8277	0.8260
0.3595	15.99	320	0.6005	0.8308	0.8297	0.8308	0.8275
0.3789	16.99	340	0.5840	0.8300	0.8271	0.8300	0.8273
0.3545	17.99	360	0.5983	0.8246	0.8226	0.8246	0.8222
0.3472	18.99	380	0.5795	0.8416	0.8382	0.8416	0.8390
0.355	19.99	400	0.5761	0.8315	0.8302	0.8315	0.8292

jayanta/cvt-13-384-22k-fv-finetuned-memes

cvt-13-384-22k-fv-finetuned-memes