Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.5739	0.99	20	1.5427	0.4521	0.3131	0.4521	0.2880
1.4353	1.99	40	1.3786	0.4490	0.3850	0.4490	0.2791
1.3026	2.99	60	1.2734	0.4799	0.3073	0.4799	0.3393
1.1579	3.99	80	1.1378	0.5278	0.4300	0.5278	0.4143
1.0276	4.99	100	1.0231	0.5734	0.4497	0.5734	0.4865
0.8826	5.99	120	0.9228	0.6252	0.5983	0.6252	0.5637
0.766	6.99	140	0.8441	0.6662	0.6474	0.6662	0.6320
0.6732	7.99	160	0.8009	0.6901	0.6759	0.6901	0.6704
0.5653	8.99	180	0.7535	0.7218	0.7141	0.7218	0.7129
0.4957	9.99	200	0.7317	0.7257	0.7248	0.7257	0.7200
0.4534	10.99	220	0.6808	0.7434	0.7405	0.7434	0.7390
0.3792	11.99	240	0.6949	0.7450	0.7454	0.7450	0.7399
0.3489	12.99	260	0.6746	0.7496	0.7511	0.7496	0.7474
0.3113	13.99	280	0.6637	0.7573	0.7638	0.7573	0.7579
0.2947	14.99	300	0.6451	0.7589	0.7667	0.7589	0.7610
0.2776	15.99	320	0.6754	0.7543	0.7565	0.7543	0.7525
0.2611	16.99	340	0.6808	0.7550	0.7607	0.7550	0.7529
0.2428	17.99	360	0.7005	0.7457	0.7497	0.7457	0.7404
0.2346	18.99	380	0.6597	0.7573	0.7642	0.7573	0.7590
0.2367	19.99	400	0.6772	0.7558	0.7557	0.7558	0.7546

jayanta/resnet152-FV-finetuned-memes

resnet152-FV-finetuned-memes