Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
1.0317	0.05	400	0.5734	0.7771	0.7803
0.544	0.09	800	0.3994	0.8548	0.8555
0.4604	0.14	1200	0.3492	0.8681	0.8687
0.4235	0.19	1600	0.3323	0.8764	0.8777
0.3934	0.23	2000	0.3225	0.8831	0.8841
0.3863	0.28	2400	0.3086	0.8875	0.8872
0.3767	0.33	2800	0.2972	0.8892	0.8898
0.3726	0.37	3200	0.2910	0.8932	0.8936
0.3624	0.42	3600	0.2934	0.8934	0.8937
0.361	0.47	4000	0.2831	0.8989	0.8989
0.3553	0.51	4400	0.2905	0.8985	0.8993
0.3451	0.56	4800	0.2725	0.9019	0.9024
0.3475	0.61	5200	0.2712	0.9046	0.9051
0.3398	0.65	5600	0.2787	0.9024	0.9028
0.3322	0.7	6000	0.2697	0.9043	0.9046
0.3288	0.75	6400	0.2722	0.9006	0.9013
0.324	0.79	6800	0.2677	0.9066	0.9066
0.3335	0.84	7200	0.2629	0.9075	0.9077
0.3309	0.89	7600	0.2577	0.9058	0.9061
0.3236	0.93	8000	0.2561	0.9121	0.9121
0.3183	0.98	8400	0.2556	0.9084	0.9088
0.3022	1.03	8800	0.2668	0.9056	0.9064
0.2974	1.07	9200	0.2519	0.9087	0.9092
0.29	1.12	9600	0.2554	0.9103	0.9109
0.2855	1.16	10000	0.2611	0.9108	0.9110

k4black/roberta-base-e-snli-classification-nli-base

roberta-base-e-snli-classification-nli-base