Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0053	21.74	500	0.9346	0.6644	0.7315	0.6964	0.8395
0.0026	43.48	1000	0.9918	0.7216	0.7278	0.7247	0.8587
0.0016	65.22	1500	0.9133	0.7098	0.7291	0.7193	0.8603
0.0001	86.96	2000	1.0041	0.7580	0.7328	0.7451	0.8536
0.0002	108.7	2500	1.1795	0.7312	0.7438	0.7375	0.8461
0.0001	130.43	3000	1.1417	0.7169	0.7328	0.7247	0.8642
0.0	152.17	3500	1.1740	0.7336	0.7562	0.7447	0.8453
0.0	173.91	4000	1.0535	0.7350	0.7414	0.7382	0.8635
0.0	195.65	4500	1.2769	0.7443	0.7241	0.7341	0.8502
0.0	217.39	5000	1.2235	0.7148	0.7438	0.7290	0.8363
0.0004	239.13	5500	1.2500	0.7376	0.7685	0.7527	0.8569
0.0	260.87	6000	1.2864	0.7494	0.7734	0.7612	0.8555
0.0	282.61	6500	1.1766	0.7649	0.7451	0.7548	0.8589
0.0	304.35	7000	1.3060	0.7231	0.7365	0.7297	0.8479
0.0	326.09	7500	1.1780	0.7093	0.7451	0.7267	0.8534
0.0	347.83	8000	1.2882	0.7337	0.75	0.7418	0.8614
0.0	369.57	8500	1.2833	0.7436	0.75	0.7468	0.8644
0.0	391.3	9000	1.4372	0.7372	0.7463	0.7417	0.8522
0.0	413.04	9500	1.4223	0.7382	0.75	0.7440	0.8513
0.0	434.78	10000	1.3686	0.7454	0.75	0.7477	0.8554

kavg/LiLT-SER-DE-SIN

LiLT-SER-DE-SIN