NewStock/main/train/catboost_info/learn_error.tsv

1	iter	Precision	CrossEntropy
2	0	0.6421052632	0.6541943716
3	1	0.8571428571	0.6220139285
4	2	0.9473684211	0.5916510322
5	3	0.9142857143	0.5644849167
6	4	0.890625	0.5410338375
7	5	0.8	0.5196276588
8	6	0.8518518519	0.5010221829
9	7	0.8764044944	0.4849534885
10	8	0.8804347826	0.4703366289
11	9	0.8875	0.457428825
12	10	0.9358974359	0.4457376255
13	11	0.8846153846	0.4359375713
14	12	0.8510638298	0.4264152672
15	13	0.8764044944	0.4182715557
16	14	0.9024390244	0.4110272796
17	15	0.8735632184	0.4046110501
18	16	0.8953488372	0.3980741403
19	17	0.8918918919	0.3925273723
20	18	0.8888888889	0.3880111628
21	19	0.8876404494	0.383472642
22	20	0.8850574713	0.3796266965
23	21	0.9	0.3761398694
24	22	0.8941176471	0.3727471701
25	23	0.8795180723	0.3698476705
26	24	0.8791208791	0.366884231
27	25	0.8736842105	0.3639221459
28	26	0.908045977	0.3615422916
29	27	0.8865979381	0.3594712663
30	28	0.9120879121	0.3576372534
31	29	0.9318181818	0.3557858833
32	30	0.9213483146	0.3540102147
33	31	0.9157894737	0.3527535855
34	32	0.9215686275	0.3512465785
35	33	0.9278350515	0.3498231139
36	34	0.9142857143	0.3482837805
37	35	0.9278350515	0.347266124
38	36	0.9304347826	0.3461889827
39	37	0.9333333333	0.3452881929
40	38	0.9327731092	0.3436992116
41	39	0.9268292683	0.3429076257
42	40	0.92	0.3419519488
43	41	0.9206349206	0.3410037922
44	42	0.9236641221	0.3402700516
45	43	0.928057554	0.3396138301
46	44	0.9416058394	0.3387833599
47	45	0.9432624113	0.337743107
48	46	0.9371069182	0.3372271328
49	47	0.935483871	0.3365873061
50	48	0.9320987654	0.33607568
51	49	0.9272727273	0.3350486856
52	50	0.9226190476	0.3345484646
53	51	0.9341317365	0.3338950944
54	52	0.9281437126	0.3327000884
55	53	0.9180327869	0.33217777
56	54	0.9189189189	0.331515846
57	55	0.9206349206	0.3308074105
58	56	0.9214659686	0.3296911354
59	57	0.9162561576	0.3292216726
60	58	0.9099526066	0.3284372505
61	59	0.9107981221	0.3277626383
62	60	0.9128440367	0.3271785541
63	61	0.9132420091	0.3262657177
64	62	0.9144144144	0.3253470717
65	63	0.9196428571	0.3247234974
66	64	0.9203539823	0.3235557567
67	65	0.9166666667	0.3228013444
68	66	0.9181034483	0.3222814496
69	67	0.9166666667	0.321691948
70	68	0.9198312236	0.3209086665
71	69	0.9193548387	0.3202570783
72	70	0.9227642276	0.3199307852
73	71	0.9243027888	0.3194535527
74	72	0.9221789883	0.3188831547
75	73	0.9227799228	0.3182035527
76	74	0.9236641221	0.317120495
77	75	0.9201520913	0.3168538293
78	76	0.9210526316	0.3163409557
79	77	0.921641791	0.3156599994
80	78	0.9239130435	0.3152008368
81	79	0.9241877256	0.3143367929
82	80	0.9222614841	0.3138722842
83	81	0.9219858156	0.3130961665
84	82	0.9195804196	0.3126652315
85	83	0.9206896552	0.3123047231
86	84	0.9238754325	0.3112267621
87	85	0.9233333333	0.31078542
88	86	0.9248366013	0.310220974
89	87	0.9233226837	0.3097435989
90	88	0.9242902208	0.3090203724
91	89	0.9242902208	0.3086560861
92	90	0.9252336449	0.3080292327
93	91	0.9237804878	0.3076218208
94	92	0.9244712991	0.3075668981
95	93	0.9249249249	0.3071175368
96	94	0.9253731343	0.3066006002
97	95	0.9262536873	0.3062844648
98	96	0.9237536657	0.3059603815
99	97	0.9217391304	0.3052842011
100	98	0.9340974212	0.3046106937
101	99	0.9344729345	0.3043589259
102	100	0.9355742297	0.3040324903
103	101	0.9364640884	0.3036740491
104	102	0.9369863014	0.3032366632
105	103	0.935483871	0.3026225693
106	104	0.932642487	0.3020944058
107	105	0.9333333333	0.3018100978
108	106	0.9335038363	0.3012678918
109	107	0.9248120301	0.3006216497
110	108	0.9259259259	0.3002269617
111	109	0.9270072993	0.2997753193
112	110	0.9270072993	0.2989820227
113	111	0.928057554	0.2985569329
114	112	0.9282296651	0.2982289825
115	113	0.9263657957	0.2976258126
116	114	0.9270588235	0.2971854328
117	115	0.9270588235	0.2968307339
118	116	0.9285714286	0.2962460795
119	117	0.9292237443	0.2956911496