Training Loss	Epoch	Step	Validation Loss
1.4951	0.01	25	1.5347
1.356	0.02	50	1.3895
1.316	0.03	75	1.3312
1.2512	0.04	100	1.2981
1.2981	0.05	125	1.2738
1.2777	0.06	150	1.2508
1.2913	0.07	175	1.2362
1.2591	0.08	200	1.2201
1.1763	0.09	225	1.2136
1.1835	0.1	250	1.2001
1.1913	0.11	275	1.1864
1.1828	0.12	300	1.1787
1.1523	0.13	325	1.1708
1.2038	0.14	350	1.1653
1.1555	0.15	375	1.1591
1.1235	0.16	400	1.1611
1.1431	0.17	425	1.1484
1.1355	0.18	450	1.1470
1.1464	0.19	475	1.1354
1.146	0.2	500	1.1335
1.1471	0.21	525	1.1241
1.1568	0.22	550	1.1243
1.1565	0.23	575	1.1247
1.1253	0.24	600	1.1160
1.1002	0.25	625	1.1081
1.1356	0.26	650	1.1067
1.0997	0.27	675	1.1074
1.1092	0.28	700	1.1007
1.1016	0.29	725	1.1019
1.0578	0.3	750	1.0897
1.0588	0.31	775	1.0867
1.063	0.32	800	1.0901
1.0559	0.33	825	1.0885
1.1272	0.34	850	1.0841
1.0762	0.35	875	1.0797
1.0842	0.36	900	1.0793
1.0566	0.37	925	1.0744
1.0712	0.38	950	1.0682
1.076	0.39	975	1.0692
1.0624	0.4	1000	1.0670
1.0541	0.41	1025	1.0599
1.0292	0.42	1050	1.0601
1.0788	0.43	1075	1.0536
1.0846	0.44	1100	1.0530
1.0547	0.45	1125	1.0562
0.9978	0.46	1150	1.0483
1.0261	0.47	1175	1.0470
1.0031	0.48	1200	1.0475
1.0141	0.49	1225	1.0442
1.064	0.5	1250	1.0416
1.0154	0.51	1275	1.0408
1.0474	0.52	1300	1.0383
1.0392	0.53	1325	1.0380
1.036	0.54	1350	1.0360
1.0325	0.55	1375	1.0312
1.062	0.56	1400	1.0308
1.0601	0.57	1425	1.0282
1.0287	0.58	1450	1.0274
0.9944	0.59	1475	1.0249
1.0302	0.6	1500	1.0241
1.0188	0.61	1525	1.0210
0.8968	0.62	1550	1.0211
0.9661	0.63	1575	1.0176
1.0741	0.64	1600	1.0182
1.0666	0.65	1625	1.0156
1.0623	0.66	1650	1.0138
1.0435	0.67	1675	1.0117
0.9892	0.68	1700	1.0117
0.9941	0.69	1725	1.0097
0.967	0.7	1750	1.0092
1.0387	0.71	1775	1.0074
0.9718	0.72	1800	1.0056
0.9841	0.73	1825	1.0049
1.0086	0.74	1850	1.0038
0.9855	0.75	1875	1.0025
1.0174	0.76	1900	1.0022
0.9725	0.77	1925	1.0003
0.987	0.78	1950	0.9989
1.0133	0.79	1975	0.9979
0.9978	0.8	2000	0.9974
1.0193	0.81	2025	0.9960
0.9842	0.82	2050	0.9955
0.9316	0.83	2075	0.9952
1.0233	0.84	2100	0.9940
1.0054	0.85	2125	0.9930
0.922	0.86	2150	0.9933
1.0309	0.87	2175	0.9925
0.975	0.88	2200	0.9917
1.0108	0.89	2225	0.9915
0.9418	0.9	2250	0.9911
0.9445	0.91	2275	0.9907
0.9973	0.92	2300	0.9903
1.0052	0.93	2325	0.9900
0.9347	0.94	2350	0.9899
0.954	0.95	2375	0.9897
0.9857	0.96	2400	0.9896
0.958	0.97	2425	0.9895
1.0051	0.98	2450	0.9894
0.9999	0.99	2475	0.9894
0.959	1.0	2500	0.9894

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0

superlazycoder/chesspythia-70m-random_1M

chesspythia-70m-random_1M

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

superlazycoder/
chesspythia-70m-random_1M