Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0089	21.74	500	0.8362	0.6606	0.7118	0.6852	0.8545
0.0013	43.48	1000	1.3605	0.7269	0.7081	0.7174	0.8230
0.0051	65.22	1500	0.9220	0.7113	0.7525	0.7313	0.8725
0.0054	86.96	2000	1.2086	0.6965	0.7291	0.7124	0.8467
0.0001	108.7	2500	1.1308	0.6843	0.7315	0.7071	0.8449
0.0001	130.43	3000	1.0934	0.7362	0.7044	0.7199	0.8606
0.0	152.17	3500	1.0390	0.7297	0.7512	0.7403	0.8590
0.0001	173.91	4000	1.1448	0.7128	0.7672	0.7390	0.8599
0.0	195.65	4500	1.1902	0.7393	0.7229	0.7310	0.8551
0.0001	217.39	5000	1.1164	0.7141	0.7783	0.7448	0.8555
0.0001	239.13	5500	1.4359	0.7197	0.7241	0.7219	0.8313
0.0	260.87	6000	1.4027	0.7256	0.7426	0.7340	0.8376
0.0	282.61	6500	1.4112	0.7085	0.7574	0.7321	0.8524
0.0	304.35	7000	1.5045	0.7627	0.7599	0.7613	0.8432
0.0	326.09	7500	1.4482	0.7390	0.7672	0.7529	0.8398
0.0	347.83	8000	1.5717	0.7155	0.7525	0.7335	0.8360
0.0	369.57	8500	1.3845	0.7348	0.7746	0.7542	0.8422
0.0	391.3	9000	1.3238	0.7283	0.7660	0.7467	0.8499
0.0	413.04	9500	1.3677	0.7321	0.7672	0.7492	0.8492
0.0001	434.78	10000	1.3790	0.7420	0.7759	0.7586	0.8474

kavg/LiLT-SER-EN-SIN

LiLT-SER-EN-SIN