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unit
string
ppl
float64
kld
float64
kld_max
float64
kld_median
float64
dp_rms
float64
same_top
float64
tensors
list
damage
float64
damage_kld
float64
damage_kld_max
float64
damage_kld_median
float64
damage_dp_rms
float64
damage_same_top
float64
BASELINE
21.0553
0.069873
17.620977
0.029143
0.06317
0.88328
null
null
null
null
null
null
null
attn_gate@0+attn_qkv@0
20.6719
0.081139
18.706854
0.030655
0.06703
0.87664
[ "blk.0.attn_gate.weight", "blk.0.attn_qkv.weight" ]
-0.3834
0.011266
1.085877
0.001512
0.00386
-0.00664
attn_output@0
21.0192
0.076174
17.495722
0.030443
0.066
0.87966
[ "blk.0.attn_output.weight" ]
-0.0361
0.006301
-0.125255
0.0013
0.00283
-0.00362
ffn_down@0
21.0304
0.071168
17.06539
0.02939
0.06415
0.88292
[ "blk.0.ffn_down.weight" ]
-0.0249
0.001295
-0.555587
0.000247
0.00098
-0.00036
ffn_gate@0+ffn_up@0
20.9804
0.076562
17.460293
0.029766
0.06461
0.88039
[ "blk.0.ffn_gate.weight", "blk.0.ffn_up.weight" ]
-0.0749
0.006689
-0.160684
0.000623
0.00144
-0.00289
attn_gate@1+attn_qkv@1
21.0024
0.070903
18.379446
0.02928
0.06398
0.88366
[ "blk.1.attn_gate.weight", "blk.1.attn_qkv.weight" ]
-0.0529
0.00103
0.758469
0.000137
0.00081
0.00038
attn_output@1
21.0823
0.071951
17.940834
0.029713
0.06424
0.88229
[ "blk.1.attn_output.weight" ]
0.027
0.002078
0.319857
0.00057
0.00107
-0.00099
ffn_down@1
21.0871
0.071663
18.336733
0.029649
0.06539
0.88325
[ "blk.1.ffn_down.weight" ]
0.0318
0.00179
0.715756
0.000506
0.00222
-0.00003
ffn_gate@1+ffn_up@1
20.9269
0.073522
19.652838
0.030353
0.06449
0.88098
[ "blk.1.ffn_gate.weight", "blk.1.ffn_up.weight" ]
-0.1284
0.003649
2.031861
0.00121
0.00132
-0.0023
attn_gate@10+attn_qkv@10
21.0331
0.070882
18.305182
0.029812
0.06343
0.88173
[ "blk.10.attn_gate.weight", "blk.10.attn_qkv.weight" ]
-0.0222
0.001009
0.684205
0.000669
0.00026
-0.00155
attn_output@10
21.0929
0.071742
17.409397
0.030258
0.06405
0.88253
[ "blk.10.attn_output.weight" ]
0.0376
0.001869
-0.21158
0.001115
0.00088
-0.00075
ffn_down@10
21.0835
0.070605
18.051743
0.029358
0.06351
0.88331
[ "blk.10.ffn_down.weight" ]
0.0282
0.000732
0.430766
0.000215
0.00034
0.00003
ffn_gate@10+ffn_up@10
21.0296
0.072396
18.257988
0.030239
0.06377
0.88127
[ "blk.10.ffn_gate.weight", "blk.10.ffn_up.weight" ]
-0.0257
0.002523
0.637011
0.001096
0.0006
-0.00201
attn_gate@11+attn_qkv@11
21.2184
0.071949
17.881397
0.030271
0.06373
0.88076
[ "blk.11.attn_gate.weight", "blk.11.attn_qkv.weight" ]
0.1631
0.002076
0.26042
0.001128
0.00056
-0.00252
attn_output@11
21.2353
0.073331
16.189793
0.030927
0.06466
0.88063
[ "blk.11.attn_output.weight" ]
0.18
0.003458
-1.431184
0.001784
0.00149
-0.00265
ffn_down@11
20.9783
0.071018
17.641331
0.029483
0.06395
0.88352
[ "blk.11.ffn_down.weight" ]
-0.077
0.001145
0.020354
0.00034
0.00078
0.00024
ffn_gate@11+ffn_up@11
21.1411
0.071179
17.78878
0.029703
0.06408
0.88263
[ "blk.11.ffn_gate.weight", "blk.11.ffn_up.weight" ]
0.0858
0.001306
0.167803
0.00056
0.00091
-0.00065
attn_gate@12+attn_qkv@12
21.0201
0.070734
17.385168
0.029427
0.06385
0.88265
[ "blk.12.attn_gate.weight", "blk.12.attn_qkv.weight" ]
-0.0352
0.000861
-0.235809
0.000284
0.00068
-0.00063
attn_output@12
21.0486
0.070606
18.043449
0.030081
0.06335
0.88301
[ "blk.12.attn_output.weight" ]
-0.0067
0.000733
0.422472
0.000938
0.00018
-0.00027
ffn_down@12
21.0681
0.070381
17.032515
0.029365
0.06324
0.88394
[ "blk.12.ffn_down.weight" ]
0.0128
0.000508
-0.588462
0.000222
0.00007
0.00066
ffn_gate@12+ffn_up@12
20.9955
0.071084
17.496353
0.030071
0.06385
0.88231
[ "blk.12.ffn_gate.weight", "blk.12.ffn_up.weight" ]
-0.0598
0.001211
-0.124624
0.000928
0.00068
-0.00097
attn_gate@13+attn_qkv@13
21.0404
0.070146
17.229485
0.029438
0.06322
0.88313
[ "blk.13.attn_gate.weight", "blk.13.attn_qkv.weight" ]
-0.0149
0.000273
-0.391492
0.000295
0.00005
-0.00015
attn_output@13
20.9843
0.071926
17.791285
0.03048
0.06395
0.88226
[ "blk.13.attn_output.weight" ]
-0.071
0.002053
0.170308
0.001337
0.00078
-0.00102
ffn_down@13
21.0399
0.070555
17.813784
0.029477
0.0636
0.88355
[ "blk.13.ffn_down.weight" ]
-0.0154
0.000682
0.192807
0.000334
0.00043
0.00027
ffn_gate@13+ffn_up@13
21.0414
0.070859
17.939978
0.029567
0.06349
0.88228
[ "blk.13.ffn_gate.weight", "blk.13.ffn_up.weight" ]
-0.0139
0.000986
0.319001
0.000424
0.00032
-0.001
attn_gate@14+attn_qkv@14
21.0986
0.070363
17.620636
0.029326
0.06367
0.88301
[ "blk.14.attn_gate.weight", "blk.14.attn_qkv.weight" ]
0.0433
0.00049
-0.000341
0.000183
0.0005
-0.00027
attn_output@14
21.0632
0.071691
17.754454
0.030411
0.06352
0.88144
[ "blk.14.attn_output.weight" ]
0.0079
0.001818
0.133477
0.001268
0.00035
-0.00184
ffn_down@14
21.1301
0.070651
17.448322
0.02973
0.06378
0.88291
[ "blk.14.ffn_down.weight" ]
0.0748
0.000778
-0.172655
0.000587
0.00061
-0.00037
ffn_gate@14+ffn_up@14
21.0065
0.070629
16.655306
0.029993
0.06342
0.88279
[ "blk.14.ffn_gate.weight", "blk.14.ffn_up.weight" ]
-0.0488
0.000756
-0.965671
0.00085
0.00025
-0.00049
attn_gate@15+attn_qkv@15
21.1234
0.071848
17.687763
0.029996
0.06389
0.88231
[ "blk.15.attn_gate.weight", "blk.15.attn_qkv.weight" ]
0.0681
0.001975
0.066786
0.000853
0.00072
-0.00097
attn_output@15
21.0949
0.071949
18.218407
0.030273
0.06437
0.88214
[ "blk.15.attn_output.weight" ]
0.0396
0.002076
0.59743
0.00113
0.0012
-0.00114
ffn_down@15
21.0566
0.070678
18.125696
0.029487
0.06361
0.88265
[ "blk.15.ffn_down.weight" ]
0.0013
0.000805
0.504719
0.000344
0.00044
-0.00063
ffn_gate@15+ffn_up@15
21.0366
0.070621
17.826267
0.029785
0.0636
0.88183
[ "blk.15.ffn_gate.weight", "blk.15.ffn_up.weight" ]
-0.0187
0.000748
0.20529
0.000642
0.00043
-0.00145
attn_gate@16+attn_qkv@16
20.9833
0.070466
17.426645
0.029499
0.06346
0.88393
[ "blk.16.attn_gate.weight", "blk.16.attn_qkv.weight" ]
-0.072
0.000593
-0.194332
0.000356
0.00029
0.00065
attn_output@16
21.1218
0.071185
17.686026
0.030267
0.06349
0.88325
[ "blk.16.attn_output.weight" ]
0.0665
0.001312
0.065049
0.001124
0.00032
-0.00003
ffn_down@16
21.0374
0.070461
17.561308
0.029405
0.06354
0.88374
[ "blk.16.ffn_down.weight" ]
-0.0179
0.000588
-0.059669
0.000262
0.00037
0.00046
ffn_gate@16+ffn_up@16
21.0471
0.070626
17.38763
0.029517
0.06343
0.88435
[ "blk.16.ffn_gate.weight", "blk.16.ffn_up.weight" ]
-0.0082
0.000753
-0.233347
0.000374
0.00026
0.00107
attn_gate@17+attn_qkv@17
21.1314
0.070334
17.484077
0.029307
0.06344
0.88347
[ "blk.17.attn_gate.weight", "blk.17.attn_qkv.weight" ]
0.0761
0.000461
-0.1369
0.000164
0.00027
0.00019
attn_output@17
21.048
0.070417
17.271139
0.029625
0.06355
0.88214
[ "blk.17.attn_output.weight" ]
-0.0073
0.000544
-0.349838
0.000482
0.00038
-0.00114
ffn_down@17
21.0292
0.070393
17.467249
0.029474
0.06356
0.88314
[ "blk.17.ffn_down.weight" ]
-0.0261
0.00052
-0.153728
0.000331
0.00039
-0.00014
ffn_gate@17+ffn_up@17
21.0666
0.070915
17.6189
0.029664
0.06374
0.88274
[ "blk.17.ffn_gate.weight", "blk.17.ffn_up.weight" ]
0.0113
0.001042
-0.002077
0.000521
0.00057
-0.00054
attn_gate@18+attn_qkv@18
21.1117
0.070381
17.693985
0.029382
0.06346
0.8836
[ "blk.18.attn_gate.weight", "blk.18.attn_qkv.weight" ]
0.0564
0.000508
0.073008
0.000239
0.00029
0.00032
attn_output@18
21.0026
0.070263
16.909418
0.029746
0.06339
0.88223
[ "blk.18.attn_output.weight" ]
-0.0527
0.00039
-0.711559
0.000603
0.00022
-0.00105
ffn_down@18
21.0173
0.070397
17.240646
0.029533
0.0635
0.88369
[ "blk.18.ffn_down.weight" ]
-0.038
0.000524
-0.380331
0.00039
0.00033
0.00041
ffn_gate@18+ffn_up@18
21.1474
0.071065
17.507074
0.030079
0.06405
0.88343
[ "blk.18.ffn_gate.weight", "blk.18.ffn_up.weight" ]
0.0921
0.001192
-0.113903
0.000936
0.00088
0.00015
attn_gate@19+attn_qkv@19
21.0298
0.071226
17.775305
0.02972
0.06352
0.88265
[ "blk.19.attn_gate.weight", "blk.19.attn_qkv.weight" ]
-0.0255
0.001353
0.154328
0.000577
0.00035
-0.00063
attn_output@19
21.1202
0.071201
16.920282
0.029833
0.06369
0.8827
[ "blk.19.attn_output.weight" ]
0.0649
0.001328
-0.700695
0.00069
0.00052
-0.00058
ffn_down@19
21.1128
0.070575
17.764671
0.029438
0.0636
0.88352
[ "blk.19.ffn_down.weight" ]
0.0575
0.000702
0.143694
0.000295
0.00043
0.00024
ffn_gate@19+ffn_up@19
21.0709
0.070512
17.317923
0.029705
0.06343
0.8825
[ "blk.19.ffn_gate.weight", "blk.19.ffn_up.weight" ]
0.0156
0.000639
-0.303054
0.000562
0.00026
-0.00078
attn_gate@2+attn_qkv@2
20.9332
0.075473
17.953886
0.029923
0.06526
0.88095
[ "blk.2.attn_gate.weight", "blk.2.attn_qkv.weight" ]
-0.1221
0.0056
0.332909
0.00078
0.00209
-0.00233
attn_output@2
21.0151
0.070355
18.047815
0.029917
0.06332
0.88233
[ "blk.2.attn_output.weight" ]
-0.0402
0.000482
0.426838
0.000774
0.00015
-0.00095
ffn_down@2
20.9474
0.071821
20.854895
0.029688
0.06446
0.88199
[ "blk.2.ffn_down.weight" ]
-0.1079
0.001948
3.233918
0.000545
0.00129
-0.00129
ffn_gate@2+ffn_up@2
20.9419
0.074145
18.199648
0.029904
0.06476
0.88245
[ "blk.2.ffn_gate.weight", "blk.2.ffn_up.weight" ]
-0.1134
0.004272
0.578671
0.000761
0.00159
-0.00083
attn_gate@20+attn_qkv@20
21.0863
0.070187
17.830053
0.029415
0.06319
0.88311
[ "blk.20.attn_gate.weight", "blk.20.attn_qkv.weight" ]
0.031
0.000314
0.209076
0.000272
0.00002
-0.00017
attn_output@20
21.0502
0.070147
17.428524
0.029432
0.06347
0.88325
[ "blk.20.attn_output.weight" ]
-0.0051
0.000274
-0.192453
0.000289
0.0003
-0.00003
ffn_down@20
21.0705
0.070235
17.596926
0.029416
0.06346
0.88354
[ "blk.20.ffn_down.weight" ]
0.0152
0.000362
-0.024051
0.000273
0.00029
0.00026
ffn_gate@20+ffn_up@20
21.0788
0.07039
17.793222
0.029503
0.06346
0.88468
[ "blk.20.ffn_gate.weight", "blk.20.ffn_up.weight" ]
0.0235
0.000517
0.172245
0.00036
0.00029
0.0014
attn_gate@21+attn_qkv@21
21.0515
0.070027
17.544535
0.029433
0.06326
0.88303
[ "blk.21.attn_gate.weight", "blk.21.attn_qkv.weight" ]
-0.0038
0.000154
-0.076442
0.00029
0.00009
-0.00025
attn_output@21
21.0575
0.069927
17.357851
0.029165
0.06342
0.884
[ "blk.21.attn_output.weight" ]
0.0022
0.000054
-0.263126
0.000022
0.00025
0.00072
ffn_down@21
21.0619
0.070225
17.658344
0.029288
0.06355
0.88369
[ "blk.21.ffn_down.weight" ]
0.0066
0.000352
0.037367
0.000145
0.00038
0.00041
ffn_gate@21+ffn_up@21
21.0608
0.070306
17.707872
0.029615
0.06352
0.8835
[ "blk.21.ffn_gate.weight", "blk.21.ffn_up.weight" ]
0.0055
0.000433
0.086895
0.000472
0.00035
0.00022
attn_gate@22+attn_qkv@22
21.1216
0.070175
17.529819
0.029356
0.06336
0.88376
[ "blk.22.attn_gate.weight", "blk.22.attn_qkv.weight" ]
0.0663
0.000302
-0.091158
0.000213
0.00019
0.00048
attn_output@22
21.0676
0.070121
17.63036
0.029267
0.06324
0.88388
[ "blk.22.attn_output.weight" ]
0.0123
0.000248
0.009383
0.000124
0.00007
0.0006
ffn_down@22
21.0614
0.070068
17.464777
0.029244
0.06338
0.88323
[ "blk.22.ffn_down.weight" ]
0.0061
0.000195
-0.1562
0.000101
0.00021
-0.00005
ffn_gate@22+ffn_up@22
21.0478
0.07031
17.641195
0.029418
0.06344
0.88379
[ "blk.22.ffn_gate.weight", "blk.22.ffn_up.weight" ]
-0.0075
0.000437
0.020218
0.000275
0.00027
0.00051
attn_gate@23+attn_qkv@23
21.0412
0.07043
17.459681
0.029517
0.06341
0.88388
[ "blk.23.attn_gate.weight", "blk.23.attn_qkv.weight" ]
-0.0141
0.000557
-0.161296
0.000374
0.00024
0.0006
attn_output@23
21.0495
0.070492
17.686663
0.029463
0.06331
0.8832
[ "blk.23.attn_output.weight" ]
-0.0058
0.000619
0.065686
0.00032
0.00014
-0.00008
ffn_down@23
21.0446
0.070188
17.579908
0.029331
0.06341
0.88311
[ "blk.23.ffn_down.weight" ]
-0.0107
0.000315
-0.041069
0.000188
0.00024
-0.00017
ffn_gate@23+ffn_up@23
21.0729
0.070436
17.409378
0.02948
0.06344
0.88345
[ "blk.23.ffn_gate.weight", "blk.23.ffn_up.weight" ]
0.0176
0.000563
-0.211599
0.000337
0.00027
0.00017
attn_gate@24+attn_qkv@24
21.0663
0.070022
17.485683
0.029147
0.06334
0.88366
[ "blk.24.attn_gate.weight", "blk.24.attn_qkv.weight" ]
0.011
0.000149
-0.135294
0.000004
0.00017
0.00038
attn_output@24
21.0563
0.070154
17.548342
0.029233
0.06333
0.88342
[ "blk.24.attn_output.weight" ]
0.001
0.000281
-0.072635
0.00009
0.00016
0.00014
ffn_down@24
21.058
0.070094
17.603441
0.029246
0.06334
0.88381
[ "blk.24.ffn_down.weight" ]
0.0027
0.000221
-0.017536
0.000103
0.00017
0.00053
ffn_gate@24+ffn_up@24
21.0384
0.070246
17.433317
0.029496
0.06327
0.88432
[ "blk.24.ffn_gate.weight", "blk.24.ffn_up.weight" ]
-0.0169
0.000373
-0.18766
0.000353
0.0001
0.00104
attn_gate@25+attn_qkv@25
21.0488
0.06996
17.498629
0.029197
0.06331
0.88331
[ "blk.25.attn_gate.weight", "blk.25.attn_qkv.weight" ]
-0.0065
0.000087
-0.122348
0.000054
0.00014
0.00003
attn_output@25
21.0377
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17.485941
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[ "blk.25.attn_output.weight" ]
-0.0176
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ffn_down@25
21.0669
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[ "blk.25.ffn_down.weight" ]
0.0116
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ffn_gate@25+ffn_up@25
21.0516
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17.540106
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[ "blk.25.ffn_gate.weight", "blk.25.ffn_up.weight" ]
-0.0037
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attn_gate@26+attn_qkv@26
21.0386
0.069925
17.537378
0.02923
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[ "blk.26.attn_gate.weight", "blk.26.attn_qkv.weight" ]
-0.0167
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attn_output@26
21.0997
0.07011
17.558487
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[ "blk.26.attn_output.weight" ]
0.0444
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ffn_down@26
21.0669
0.070106
17.515837
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[ "blk.26.ffn_down.weight" ]
0.0116
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0.00011
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ffn_gate@26+ffn_up@26
21.1458
0.070673
17.69623
0.029607
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[ "blk.26.ffn_gate.weight", "blk.26.ffn_up.weight" ]
0.0905
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0.000464
0.00037
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attn_gate@27+attn_qkv@27
21.0858
0.070265
17.357899
0.029306
0.0634
0.88343
[ "blk.27.attn_gate.weight", "blk.27.attn_qkv.weight" ]
0.0305
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attn_output@27
21.0898
0.070174
17.275906
0.029361
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[ "blk.27.attn_output.weight" ]
0.0345
0.000301
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0.000218
0.00005
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ffn_down@27
21.0805
0.070383
17.65424
0.029563
0.06335
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[ "blk.27.ffn_down.weight" ]
0.0252
0.00051
0.033263
0.00042
0.00018
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ffn_gate@27+ffn_up@27
21.0891
0.070515
17.597046
0.029611
0.0634
0.88303
[ "blk.27.ffn_gate.weight", "blk.27.ffn_up.weight" ]
0.0338
0.000642
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0.000468
0.00023
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attn_gate@3+attn_qkv@3
21.0331
0.075593
17.661535
0.030167
0.06563
0.88066
[ "blk.3.attn_gate.weight", "blk.3.attn_qkv.weight" ]
-0.0222
0.00572
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0.001024
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attn_output@3
21.1889
0.074426
17.848194
0.030365
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[ "blk.3.attn_output.weight" ]
0.1336
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0.001222
0.00287
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ffn_down@3
20.9893
0.071797
17.849419
0.029794
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[ "blk.3.ffn_down.weight" ]
-0.066
0.001924
0.228442
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ffn_gate@3+ffn_up@3
21.0104
0.074116
18.660656
0.029799
0.06623
0.88194
[ "blk.3.ffn_gate.weight", "blk.3.ffn_up.weight" ]
-0.0449
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1.039679
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attn_gate@4+attn_qkv@4
21.0807
0.072085
18.158939
0.029688
0.06397
0.88112
[ "blk.4.attn_gate.weight", "blk.4.attn_qkv.weight" ]
0.0254
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attn_output@4
21.0413
0.071294
18.457565
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[ "blk.4.attn_output.weight" ]
-0.014
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ffn_down@4
20.9924
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18.291979
0.029428
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[ "blk.4.ffn_down.weight" ]
-0.0629
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ffn_gate@4+ffn_up@4
21.2242
0.072574
16.185465
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[ "blk.4.ffn_gate.weight", "blk.4.ffn_up.weight" ]
0.1689
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attn_gate@5+attn_qkv@5
21.0432
0.070174
18.635374
0.029438
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[ "blk.5.attn_gate.weight", "blk.5.attn_qkv.weight" ]
-0.0121
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attn_output@5
20.8951
0.072088
17.456945
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[ "blk.5.attn_output.weight" ]
-0.1602
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ffn_down@5
21.116
0.071233
17.780209
0.029682
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[ "blk.5.ffn_down.weight" ]
0.0607
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ffn_gate@5+ffn_up@5
21.3703
0.071871
17.20381
0.030572
0.0643
0.88207
[ "blk.5.ffn_gate.weight", "blk.5.ffn_up.weight" ]
0.315
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0.001429
0.00113
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attn_gate@6+attn_qkv@6
21.034
0.07205
18.219145
0.029658
0.06379
0.8836
[ "blk.6.attn_gate.weight", "blk.6.attn_qkv.weight" ]
-0.0213
0.002177
0.598168
0.000515
0.00062
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attn_output@6
21.019
0.070548
18.440779
0.029627
0.06317
0.88282
[ "blk.6.attn_output.weight" ]
-0.0363
0.000675
0.819802
0.000484
0
-0.00046
ffn_down@6
20.906
0.070905
17.596558
0.029337
0.06393
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[ "blk.6.ffn_down.weight" ]
-0.1493
0.001032
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0.000194
0.00076
-0.00039
End of preview. Expand in Data Studio

MERNIK RL-mini KLD labels (the crown jewels)

Per-tensor damage on reasoning tasks, not wikitext — the label upgrade the whole Gnom program was waiting for. Each row: one unit dropped one tier, damage measured on rl_reasoning_mini (343 prompts, 5 RL-oss subsets, EN+ZH code/reasoning).

Why this file matters. PPL-damage labels saturate: a reasoning-critical layer and a filler layer can show the same wiki damage (the Perplexity Illusion). KLD against the unperturbed model is fidelity-sensitive, and the extra columns below are the first attempt to price how the distribution breaks, not just how much.

Columns (all damage_* = perturbed minus baseline):

Column Meaning
damage PPL damage (legacy anchor)
damage_kld mean token-KLD vs reference (the allocator column)
damage_kld_max worst-token KLD — tail detonations live here (up to 20.85 measured). The mechanism that breaks reasoning: the model generates 95% of a chain-of-thought fine, then on one critical token (say, > vs <) the distribution collapses — one token and the whole answer is garbage. Mean KLD cannot see it; max KLD can
damage_kld_median median token-KLD — robust core damage. mean >> median means rare but catastrophic failures; mean ≈ median means uniform, predictable damage
damage_dp_rms / dp_rms RMS of top-1 probability shift — decisiveness damage (both directions: lost confidence and artificial sharpening)
damage_same_top fraction of positions keeping the argmax — rank before values. same_top = 0.80 means the model rewrites its decisions on every fifth token even when KLD looks fine; for code, one flipped token in if (x > y) breaks the program

Files.

  • damage_17_rlmini.jsonl — Spark-1.7B (Q5_K base, 112 units + baseline), 113 rows, all 9 columns
  • damage_4b_rlmini.jsonl — Spark-X2.5-4B (XHToken/Spark-X2.5-4B, Q5_K base), 145 rows (144 units, zero holes)

Censored units: "damage": null, "retryable": false — never impute.

Known nulls (read before training). The viewer shows null cells and they are honest, each with a reason:

  • BASELINE rows: all kld*/damage_* are null — the baseline is the reference itself, there is nothing to compare it against.
  • 4B rows without KLD columns: the 4B RL-mini leg measured PPL damage only (KLD needs the reference logits beside it; the 17B leg has both). damage is real, damage_kld* is null — absence of measurement, not zero damage.
  • TERMINAL rows: every damage null with "retryable": false — the unit could not be measured at that tier at all. Drop, don't fill.

What's next. More of these: RL-mini-style labels are worth far more per row than wiki labels, so this repo keeps growing while the wiki pool stays frozen. Part of the MERNIK program; the full label archive (pools, legacy sweeps, failure ledgers) is wepiqx/MERNIK-gnom-labels.


If this work saved you a GPU-week: github.com/sponsors/wepiqx

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