mask-ddpm/example/results/train_log.csv

1	epoch	step	loss	loss_cont	loss_disc
2	0	0	1.337395	1.021482	1.653308
3	0	10	1.038067	1.000154	1.075980
4	0	20	0.826958	1.003188	0.650727
5	0	30	0.716293	1.000017	0.432568
6	0	40	0.642435	0.996074	0.288796
7	0	50	0.645388	0.996218	0.294559
8	1	0	0.637520	0.993191	0.281849
9	1	10	0.713771	0.991469	0.436074
10	1	20	0.650629	0.992278	0.308979
11	1	30	0.629345	0.985191	0.273500
12	1	40	0.609776	0.981005	0.238547
13	1	50	0.617772	0.969507	0.266037
14	2	0	0.585185	0.967395	0.202975
15	2	10	0.680145	0.959188	0.401103
16	2	20	0.642215	0.958451	0.325979
17	2	30	0.608462	0.944497	0.272428
18	2	40	0.591900	0.935138	0.248661
19	2	50	0.595101	0.924723	0.265478
20	3	0	0.558750	0.922984	0.194516
21	3	10	0.660143	0.914986	0.405301
22	3	20	0.627620	0.921503	0.333737
23	3	30	0.588966	0.904150	0.273781
24	3	40	0.564722	0.894733	0.234712
25	3	50	0.570761	0.885211	0.256310
26	4	0	0.540599	0.890481	0.190716
27	4	10	0.641783	0.867125	0.416441
28	4	20	0.602556	0.877150	0.327963
29	4	30	0.565765	0.864500	0.267031
30	4	40	0.549726	0.865462	0.233990
31	4	50	0.557315	0.841800	0.272829
32	5	0	0.519324	0.852145	0.186504
33	5	10	0.620299	0.834153	0.406445
34	5	20	0.575242	0.824914	0.325570
35	5	30	0.552362	0.823336	0.281388
36	5	40	0.522278	0.819058	0.225498
37	5	50	0.532715	0.803952	0.261479
38	6	0	0.497478	0.812609	0.182347
39	6	10	0.604873	0.796479	0.413267
40	6	20	0.561931	0.810630	0.313232
41	6	30	0.529465	0.781080	0.277850
42	6	40	0.497049	0.760593	0.233505
43	6	50	0.508375	0.755011	0.261740
44	7	0	0.468464	0.767502	0.169426
45	7	10	0.581364	0.750101	0.412627
46	7	20	0.527510	0.744724	0.310295
47	7	30	0.502973	0.751034	0.254912
48	7	40	0.488204	0.747923	0.228486
49	7	50	0.490762	0.720018	0.261506