Training Loss	Epoch	Step	Validation Loss	Mse
0.0209	0.05	50	0.0135	0.0135
0.0179	0.11	100	0.0118	0.0118
0.0153	0.16	150	0.0116	0.0116
0.0159	0.22	200	0.0131	0.0131
0.0169	0.27	250	0.0163	0.0163
0.0116	0.32	300	0.0116	0.0116
0.0094	0.38	350	0.0123	0.0123
0.0168	0.43	400	0.0115	0.0115
0.0224	0.48	450	0.0135	0.0135
0.0144	0.54	500	0.0116	0.0116
0.0147	0.59	550	0.0115	0.0115
0.0117	0.65	600	0.0121	0.0121
0.0198	0.7	650	0.0120	0.0120
0.0119	0.75	700	0.0121	0.0121
0.0166	0.81	750	0.0118	0.0118
0.0096	0.86	800	0.0123	0.0123
0.0166	0.92	850	0.0115	0.0115
0.0181	0.97	900	0.0114	0.0114
0.0128	1.02	950	0.0114	0.0114
0.0174	1.08	1000	0.0113	0.0113
0.0161	1.13	1050	0.0126	0.0126
0.0174	1.19	1100	0.0141	0.0141
0.016	1.24	1150	0.0114	0.0114
0.0098	1.29	1200	0.0114	0.0114
0.0179	1.35	1250	0.0126	0.0126
0.0141	1.4	1300	0.0115	0.0115
0.0118	1.45	1350	0.0116	0.0116
0.0115	1.51	1400	0.0113	0.0113
0.0118	1.56	1450	0.0113	0.0113
0.0165	1.62	1500	0.0118	0.0118
0.0129	1.67	1550	0.0113	0.0113
0.011	1.72	1600	0.0118	0.0118
0.0128	1.78	1650	0.0120	0.0120
0.0145	1.83	1700	0.0124	0.0124
0.014	1.89	1750	0.0114	0.0114
0.0155	1.94	1800	0.0114	0.0114
0.0144	1.99	1850	0.0114	0.0114
0.0141	2.05	1900	0.0114	0.0114
0.0108	2.1	1950	0.0117	0.0117
0.0109	2.16	2000	0.0113	0.0113
0.0124	2.21	2050	0.0132	0.0132
0.0169	2.26	2100	0.0123	0.0123
0.0115	2.32	2150	0.0120	0.0120
0.0102	2.37	2200	0.0117	0.0117
0.0189	2.42	2250	0.0116	0.0116
0.0136	2.48	2300	0.0115	0.0115
0.0116	2.53	2350	0.0119	0.0119
0.0141	2.59	2400	0.0119	0.0119
0.0098	2.64	2450	0.0120	0.0120
0.0081	2.69	2500	0.0117	0.0117
0.009	2.75	2550	0.0119	0.0119
0.0121	2.8	2600	0.0118	0.0118
0.0128	2.86	2650	0.0123	0.0123
0.0131	2.91	2700	0.0117	0.0117
0.009	2.96	2750	0.0117	0.0117

vtiyyal1/quality_model_apr3

quality_model_apr3