OpenBMB/BitCPM-CANN-1B-unquantized
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: openbmb/BitCPM-CANN-1B-unquantized
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-06-04 14:32:59 +08:00
commit a94919dde4
28 changed files with 181544 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

51
example/npu_pretrain.csv Normal file
View File

@@ -0,0 +1,51 @@
step,train/loss,train/grad_norm,train/learning_rate,train/epoch,train/train_runtime,train/train_samples_per_second,train/train_steps_per_second,train/total_flos,train/train_loss
2,2.7920000553131104,0.035306449979543686,7.999999979801942e-06,0.010457516647875309,,,,,
4,2.8011999130249023,0.03491510450839996,1.5999999959603883e-05,0.020915033295750618,,,,,
6,2.7964000701904297,0.032717395573854446,2.4000000848900527e-05,0.0313725508749485,,,,,
8,2.763700008392334,0.024953875690698624,3.199999991920777e-05,0.041830066591501236,,,,,
10,3.2811999320983887,0.3170815408229828,3.9999998989515007e-05,0.05228758230805397,,,,,
12,2.9409000873565674,0.04423849284648895,3.995128281530924e-05,0.062745101749897,,,,,
14,2.851900100708008,0.03667925298213959,3.9805359847377986e-05,0.07320261746644974,,,,,
16,2.7869999408721924,0.022814607247710228,3.9562950405525044e-05,0.08366013318300247,,,,,
18,2.782599925994873,0.021528413519263268,3.922523319488391e-05,0.0941176488995552,,,,,
20,2.785599946975708,0.017014438286423683,3.87938525818754e-05,0.10457516461610794,,,,,
22,2.7571001052856445,0.015719758346676826,3.827090768027119e-05,0.11503268033266068,,,,,
24,2.762399911880493,0.016948623582720757,3.7658952351193875e-05,0.125490203499794,,,,,
26,2.7411000728607178,0.015535997226834297,3.6960962461307645e-05,0.13594771921634674,,,,,
28,2.7330000400543213,0.012748735956847668,3.6180339520797133e-05,0.14640523493289948,,,,,
30,2.723299980163574,0.014809778891503811,3.532088885549456e-05,0.1568627506494522,,,,,
32,2.7342000007629395,0.01219236571341753,3.4386797779006884e-05,0.16732026636600494,,,,,
34,2.7321999073028564,0.012785322032868862,3.338261376484297e-05,0.17777778208255768,,,,,
36,2.7314000129699707,0.012986919842660427,3.231322989449836e-05,0.1882352977991104,,,,,
38,2.7065999507904053,0.01096824835985899,3.118385939160362e-05,0.19869281351566315,,,,,
40,2.6958999633789062,0.012387535534799099,2.9999999242136255e-05,0.20915032923221588,,,,,
42,2.751499891281128,0.011586200445890427,2.8767422918463126e-05,0.21960784494876862,,,,,
44,2.713099956512451,0.011821281164884567,2.749213126662653e-05,0.23006536066532135,,,,,
46,2.7102999687194824,0.01147585827857256,2.6180339773418382e-05,0.24052287638187408,,,,,
48,2.7019999027252197,0.011368263512849808,2.483843854861334e-05,0.250980406999588,,,,,
50,2.680500030517578,0.009935515932738781,2.3472963221138343e-05,0.26143792271614075,,,,,
52,2.6993000507354736,0.0109846917912364,2.2090569473220967e-05,0.2718954384326935,,,,,
54,2.6940999031066895,0.010465175844728947,2.0697989384643734e-05,0.2823529541492462,,,,,
56,2.7091000080108643,0.01009758748114109,1.9302009604871273e-05,0.29281046986579895,,,,,
58,2.69950008392334,0.01249368954449892,1.7909431335283443e-05,0.3032679855823517,,,,,
60,2.7216999530792236,0.01051376760005951,1.6527035768376663e-05,0.3137255012989044,,,,,
62,2.7158000469207764,0.01054943073540926,1.516156225989107e-05,0.32418301701545715,,,,,
64,2.7214999198913574,0.01076149195432663,1.3819660125591327e-05,0.3346405327320099,,,,,
66,2.7116000652313232,0.010380392894148827,1.2507867722888477e-05,0.3450980484485626,,,,,
68,2.6923000812530518,0.010425001382827759,1.1232576980546582e-05,0.35555556416511536,,,,,
70,2.683199882507324,0.00925016961991787,9.999999747378752e-06,0.3660130798816681,,,,,
72,2.7093000411987305,0.01072422880679369,8.816142326395493e-06,0.3764705955982208,,,,,
74,2.6988000869750977,0.011063243262469769,7.686770914006047e-06,0.38692811131477356,,,,,
76,2.7125000953674316,0.01013101264834404,6.61738795315614e-06,0.3973856270313263,,,,,
78,2.6993000507354736,0.009940676391124725,5.613203938992228e-06,0.40784314274787903,,,,,
80,2.6861000061035156,0.01050259917974472,4.6791110435151495e-06,0.41830065846443176,,,,,
82,2.6828999519348145,0.009912634268403053,3.819659923465224e-06,0.4287581741809845,,,,,
84,2.699199914932251,0.010668900795280933,3.03903811982309e-06,0.43921568989753723,,,,,
86,2.698899984359741,0.009650414809584618,2.3410482299368596e-06,0.44967320561408997,,,,,
88,2.6884000301361084,0.01006452739238739,1.7290908544964623e-06,0.4601307213306427,,,,,
90,2.6928999423980713,0.010409764014184475,1.206147544507985e-06,0.47058823704719543,,,,,
92,2.714200019836426,0.009937116876244545,7.74766078848188e-07,0.48104575276374817,,,,,
94,2.672300100326538,0.009728306904435158,4.370479871340649e-07,0.4915032684803009,,,,,
96,2.7018001079559326,0.010098566301167011,1.9463863054625108e-07,0.501960813999176,,,,,
98,2.7123000621795654,0.009524320252239704,4.8718995060426096e-08,0.5124183297157288,,,,,
100,2.7028000354766846,0.009290286339819431,0.0,0.5228758454322815,788.0635986328125,64.96900177001953,0.12700000405311584,4.629706395531346e+17,2.739542245864868
1 step train/loss train/grad_norm train/learning_rate train/epoch train/train_runtime train/train_samples_per_second train/train_steps_per_second train/total_flos train/train_loss
2 2 2.7920000553131104 0.035306449979543686 7.999999979801942e-06 0.010457516647875309
3 4 2.8011999130249023 0.03491510450839996 1.5999999959603883e-05 0.020915033295750618
4 6 2.7964000701904297 0.032717395573854446 2.4000000848900527e-05 0.0313725508749485
5 8 2.763700008392334 0.024953875690698624 3.199999991920777e-05 0.041830066591501236
6 10 3.2811999320983887 0.3170815408229828 3.9999998989515007e-05 0.05228758230805397
7 12 2.9409000873565674 0.04423849284648895 3.995128281530924e-05 0.062745101749897
8 14 2.851900100708008 0.03667925298213959 3.9805359847377986e-05 0.07320261746644974
9 16 2.7869999408721924 0.022814607247710228 3.9562950405525044e-05 0.08366013318300247
10 18 2.782599925994873 0.021528413519263268 3.922523319488391e-05 0.0941176488995552
11 20 2.785599946975708 0.017014438286423683 3.87938525818754e-05 0.10457516461610794
12 22 2.7571001052856445 0.015719758346676826 3.827090768027119e-05 0.11503268033266068
13 24 2.762399911880493 0.016948623582720757 3.7658952351193875e-05 0.125490203499794
14 26 2.7411000728607178 0.015535997226834297 3.6960962461307645e-05 0.13594771921634674
15 28 2.7330000400543213 0.012748735956847668 3.6180339520797133e-05 0.14640523493289948
16 30 2.723299980163574 0.014809778891503811 3.532088885549456e-05 0.1568627506494522
17 32 2.7342000007629395 0.01219236571341753 3.4386797779006884e-05 0.16732026636600494
18 34 2.7321999073028564 0.012785322032868862 3.338261376484297e-05 0.17777778208255768
19 36 2.7314000129699707 0.012986919842660427 3.231322989449836e-05 0.1882352977991104
20 38 2.7065999507904053 0.01096824835985899 3.118385939160362e-05 0.19869281351566315
21 40 2.6958999633789062 0.012387535534799099 2.9999999242136255e-05 0.20915032923221588
22 42 2.751499891281128 0.011586200445890427 2.8767422918463126e-05 0.21960784494876862
23 44 2.713099956512451 0.011821281164884567 2.749213126662653e-05 0.23006536066532135
24 46 2.7102999687194824 0.01147585827857256 2.6180339773418382e-05 0.24052287638187408
25 48 2.7019999027252197 0.011368263512849808 2.483843854861334e-05 0.250980406999588
26 50 2.680500030517578 0.009935515932738781 2.3472963221138343e-05 0.26143792271614075
27 52 2.6993000507354736 0.0109846917912364 2.2090569473220967e-05 0.2718954384326935
28 54 2.6940999031066895 0.010465175844728947 2.0697989384643734e-05 0.2823529541492462
29 56 2.7091000080108643 0.01009758748114109 1.9302009604871273e-05 0.29281046986579895
30 58 2.69950008392334 0.01249368954449892 1.7909431335283443e-05 0.3032679855823517
31 60 2.7216999530792236 0.01051376760005951 1.6527035768376663e-05 0.3137255012989044
32 62 2.7158000469207764 0.01054943073540926 1.516156225989107e-05 0.32418301701545715
33 64 2.7214999198913574 0.01076149195432663 1.3819660125591327e-05 0.3346405327320099
34 66 2.7116000652313232 0.010380392894148827 1.2507867722888477e-05 0.3450980484485626
35 68 2.6923000812530518 0.010425001382827759 1.1232576980546582e-05 0.35555556416511536
36 70 2.683199882507324 0.00925016961991787 9.999999747378752e-06 0.3660130798816681
37 72 2.7093000411987305 0.01072422880679369 8.816142326395493e-06 0.3764705955982208
38 74 2.6988000869750977 0.011063243262469769 7.686770914006047e-06 0.38692811131477356
39 76 2.7125000953674316 0.01013101264834404 6.61738795315614e-06 0.3973856270313263
40 78 2.6993000507354736 0.009940676391124725 5.613203938992228e-06 0.40784314274787903
41 80 2.6861000061035156 0.01050259917974472 4.6791110435151495e-06 0.41830065846443176
42 82 2.6828999519348145 0.009912634268403053 3.819659923465224e-06 0.4287581741809845
43 84 2.699199914932251 0.010668900795280933 3.03903811982309e-06 0.43921568989753723
44 86 2.698899984359741 0.009650414809584618 2.3410482299368596e-06 0.44967320561408997
45 88 2.6884000301361084 0.01006452739238739 1.7290908544964623e-06 0.4601307213306427
46 90 2.6928999423980713 0.010409764014184475 1.206147544507985e-06 0.47058823704719543
47 92 2.714200019836426 0.009937116876244545 7.74766078848188e-07 0.48104575276374817
48 94 2.672300100326538 0.009728306904435158 4.370479871340649e-07 0.4915032684803009
49 96 2.7018001079559326 0.010098566301167011 1.9463863054625108e-07 0.501960813999176
50 98 2.7123000621795654 0.009524320252239704 4.8718995060426096e-08 0.5124183297157288
51 100 2.7028000354766846 0.009290286339819431 0.0 0.5228758454322815 788.0635986328125 64.96900177001953 0.12700000405311584 4.629706395531346e+17 2.739542245864868