Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall
0.6582	0.05	454	0.6970	0.5695	0.5660	0.5964
0.6712	1.05	908	0.6281	0.6390	0.6202	0.7175
0.5664	2.05	1362	0.6718	0.6457	0.6555	0.6143
0.5645	3.05	1816	0.5835	0.7018	0.6974	0.7130
0.4259	4.05	2270	0.5497	0.7197	0.7402	0.6771
0.3542	5.05	2724	0.5509	0.7466	0.7434	0.7534
0.3676	6.05	3178	0.4956	0.7623	0.7532	0.7803
0.2656	7.05	3632	0.5263	0.7534	0.7811	0.7040
0.4675	8.05	4086	0.5216	0.7915	0.8009	0.7758
0.1434	9.05	4540	0.4744	0.8094	0.8136	0.8027
0.1389	10.05	4994	0.5389	0.8318	0.8274	0.8386
0.3228	11.05	5448	0.5345	0.8341	0.8599	0.7982
0.1044	12.05	5902	0.5729	0.8341	0.8465	0.8161
0.0305	13.05	6356	0.5812	0.8363	0.8378	0.8341
0.1256	14.05	6810	0.5806	0.8520	0.8489	0.8565
0.2735	15.05	7264	0.5713	0.8520	0.8618	0.8386
0.2376	16.05	7718	0.6030	0.8498	0.8578	0.8386
0.2978	17.05	8172	0.6263	0.8565	0.8502	0.8655
0.3872	18.05	8626	0.6099	0.8520	0.8489	0.8565
0.6629	19.05	9080	0.6142	0.8543	0.8496	0.8610

onarganogun/videomae-large-fight_22-01-2024

videomae-large-fight_22-01-2024