Dataset Viewer
layer_id
int64 0
223
| name
stringlengths 26
32
| D
float64 0.03
0.21
| M
int64 1.02k
4.1k
| N
int64 4.1k
14.3k
| Q
float64 1
4
| alpha
float64 2.55
30.7
| alpha_weighted
float64 -100.7
-4.79
| entropy
float64 1.07
1.57
| has_esd
bool 1
class | lambda_max
float32 0
0.01
| layer_type
stringclasses 1
value | log_alpha_norm
float64 -100.63
-4.73
| log_norm
float32 -1.66
-0.94
| log_spectral_norm
float32 -3.31
-1.88
| matrix_rank
int64 64
64
| norm
float32 0.02
0.11
| num_evals
int64 1.02k
4.1k
| num_pl_spikes
int64 5
64
| rank_loss
int64 960
4.03k
| rf
int64 1
1
| sigma
float64 0.35
9.03
| spectral_norm
float32 0
0.01
| stable_rank
float32 4.91
54.6
| status
stringclasses 1
value | sv_max
float64 0.02
0.11
| sv_min
float64 0
0
| warning
stringclasses 2
values | weak_rank_loss
int64 960
4.03k
| xmax
float64 0
0.01
| xmin
float64 0
0
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0
|
model.layers.0.mlp.down_proj
| 0.078037
| 4,096
| 14,336
| 3.5
| 4.053136
| -8.624209
| 1.546217
| true
| 0.007451
|
dense
| -8.422872
| -0.942671
| -2.127786
| 64
| 0.114112
| 4,096
| 21
| 4,032
| 1
| 0.666249
| 0.007451
| 15.314962
|
success
| 0.086319
| 0.000001
| 4,032
| 0.007451
| 0.001594
|
|
1
|
model.layers.0.mlp.gate_proj
| 0.074845
| 4,096
| 14,336
| 3.5
| 3.074121
| -6.048194
| 1.523045
| true
| 0.010778
|
dense
| -5.992284
| -1.043336
| -1.967455
| 64
| 0.090503
| 4,096
| 13
| 4,032
| 1
| 0.575258
| 0.010778
| 8.39689
|
success
| 0.103818
| 0.000001
| 4,032
| 0.010778
| 0.001346
|
|
2
|
model.layers.0.mlp.up_proj
| 0.073709
| 4,096
| 14,336
| 3.5
| 2.963981
| -5.587149
| 1.50815
| true
| 0.013031
|
dense
| -5.539123
| -1.029696
| -1.885015
| 64
| 0.093391
| 4,096
| 18
| 4,032
| 1
| 0.462915
| 0.013031
| 7.166698
|
success
| 0.114154
| 0.000001
| 4,032
| 0.013031
| 0.001169
|
|
3
|
model.layers.0.self_attn.k_proj
| 0.041871
| 1,024
| 4,096
| 4
| 3.660928
| -8.275696
| 1.091316
| true
| 0.005489
|
dense
| -8.234427
| -1.295308
| -2.260546
| 64
| 0.050663
| 1,024
| 34
| 960
| 1
| 0.456345
| 0.005489
| 9.230771
|
success
| 0.074084
| 0.000001
| 960
| 0.005489
| 0.000629
|
|
4
|
model.layers.0.self_attn.o_proj
| 0.075064
| 4,096
| 4,096
| 1
| 2.545702
| -4.788104
| 1.446955
| true
| 0.013157
|
dense
| -4.725399
| -1.189854
| -1.880858
| 64
| 0.064587
| 4,096
| 19
| 4,032
| 1
| 0.354608
| 0.013157
| 4.90913
|
success
| 0.114702
| 0
| 4,032
| 0.013157
| 0.00069
|
|
5
|
model.layers.0.self_attn.q_proj
| 0.063552
| 4,096
| 4,096
| 1
| 3.702849
| -8.79926
| 1.540747
| true
| 0.004204
|
dense
| -8.706662
| -1.264196
| -2.376349
| 64
| 0.054426
| 4,096
| 41
| 4,032
| 1
| 0.422114
| 0.004204
| 12.9465
|
success
| 0.064837
| 0
| 4,032
| 0.004204
| 0.000649
|
|
6
|
model.layers.0.self_attn.v_proj
| 0.065128
| 1,024
| 4,096
| 4
| 4.518371
| -11.075607
| 1.074268
| true
| 0.003538
|
dense
| -11.073485
| -1.633022
| -2.451239
| 64
| 0.02328
| 1,024
| 64
| 960
| 1
| 0.439796
| 0.003538
| 6.579869
|
success
| 0.059481
| 0.000001
| 960
| 0.003538
| 0.000235
|
|
7
|
model.layers.1.mlp.down_proj
| 0.120789
| 4,096
| 14,336
| 3.5
| 3.760372
| -8.12376
| 1.553696
| true
| 0.006913
|
dense
| -8.030754
| -0.996069
| -2.160361
| 64
| 0.100909
| 4,096
| 7
| 4,032
| 1
| 1.043323
| 0.006913
| 14.59795
|
success
| 0.083142
| 0.000001
| 4,032
| 0.006913
| 0.001736
|
|
8
|
model.layers.1.mlp.gate_proj
| 0.101213
| 4,096
| 14,336
| 3.5
| 3.073197
| -6.50478
| 1.540912
| true
| 0.007645
|
dense
| -6.342643
| -1.041639
| -2.116617
| 64
| 0.090858
| 4,096
| 9
| 4,032
| 1
| 0.691066
| 0.007645
| 11.884425
|
success
| 0.087436
| 0.000001
| 4,032
| 0.007645
| 0.001464
|
|
9
|
model.layers.1.mlp.up_proj
| 0.120154
| 4,096
| 14,336
| 3.5
| 3.501113
| -7.287698
| 1.536073
| true
| 0.008288
|
dense
| -7.149562
| -1.016781
| -2.081537
| 64
| 0.09621
| 4,096
| 15
| 4,032
| 1
| 0.645785
| 0.008288
| 11.607965
|
success
| 0.09104
| 0.000001
| 4,032
| 0.008288
| 0.001366
|
|
10
|
model.layers.1.self_attn.k_proj
| 0.056722
| 1,024
| 4,096
| 4
| 4.463136
| -10.295389
| 1.102708
| true
| 0.004934
|
dense
| -10.254933
| -1.28201
| -2.306761
| 64
| 0.052238
| 1,024
| 62
| 960
| 1
| 0.439819
| 0.004934
| 10.586463
|
success
| 0.070246
| 0.000001
| 960
| 0.004934
| 0.00056
|
|
11
|
model.layers.1.self_attn.o_proj
| 0.082948
| 4,096
| 4,096
| 1
| 2.788825
| -6.187573
| 1.512383
| true
| 0.006044
|
dense
| -5.846718
| -1.19272
| -2.218702
| 64
| 0.064162
| 4,096
| 17
| 4,032
| 1
| 0.433854
| 0.006044
| 10.616527
|
success
| 0.077741
| 0
| 4,032
| 0.006044
| 0.000848
|
|
12
|
model.layers.1.self_attn.q_proj
| 0.051761
| 4,096
| 4,096
| 1
| 4.367304
| -9.032353
| 1.518836
| true
| 0.008547
|
dense
| -9.028883
| -1.188359
| -2.068176
| 64
| 0.06481
| 4,096
| 64
| 4,032
| 1
| 0.420913
| 0.008547
| 7.582582
|
success
| 0.092451
| 0
| 4,032
| 0.008547
| 0.000665
|
|
13
|
model.layers.1.self_attn.v_proj
| 0.084882
| 1,024
| 4,096
| 4
| 6.50357
| -18.628179
| 1.1217
| true
| 0.001367
|
dense
| -18.610157
| -1.656919
| -2.864301
| 64
| 0.022033
| 1,024
| 64
| 960
| 1
| 0.687946
| 0.001367
| 16.120611
|
success
| 0.03697
| 0.000001
|
under-trained
| 960
| 0.001367
| 0.000273
|
14
|
model.layers.2.mlp.down_proj
| 0.141108
| 4,096
| 14,336
| 3.5
| 4.986315
| -11.807773
| 1.561366
| true
| 0.004285
|
dense
| -11.631251
| -1.010099
| -2.368036
| 64
| 0.097701
| 4,096
| 12
| 4,032
| 1
| 1.15075
| 0.004285
| 22.800112
|
success
| 0.065461
| 0.000001
| 4,032
| 0.004285
| 0.001526
|
|
15
|
model.layers.2.mlp.gate_proj
| 0.09412
| 4,096
| 14,336
| 3.5
| 3.715742
| -7.997589
| 1.549306
| true
| 0.007041
|
dense
| -7.919346
| -1.032961
| -2.152353
| 64
| 0.092691
| 4,096
| 10
| 4,032
| 1
| 0.858793
| 0.007041
| 13.164119
|
success
| 0.083912
| 0.000001
| 4,032
| 0.007041
| 0.001451
|
|
16
|
model.layers.2.mlp.up_proj
| 0.088223
| 4,096
| 14,336
| 3.5
| 3.476825
| -7.241272
| 1.543075
| true
| 0.008266
|
dense
| -7.155042
| -1.013239
| -2.082725
| 64
| 0.096998
| 4,096
| 12
| 4,032
| 1
| 0.714998
| 0.008266
| 11.735083
|
success
| 0.090915
| 0.000001
| 4,032
| 0.008266
| 0.001439
|
|
17
|
model.layers.2.self_attn.k_proj
| 0.059055
| 1,024
| 4,096
| 4
| 6.324751
| -16.606587
| 1.124112
| true
| 0.002368
|
dense
| -16.570013
| -1.3895
| -2.625651
| 64
| 0.040785
| 1,024
| 64
| 960
| 1
| 0.665594
| 0.002368
| 17.224663
|
success
| 0.04866
| 0.000001
|
under-trained
| 960
| 0.002368
| 0.000507
|
18
|
model.layers.2.self_attn.o_proj
| 0.054473
| 4,096
| 4,096
| 1
| 3.100158
| -7.058452
| 1.526014
| true
| 0.005287
|
dense
| -6.920864
| -1.264247
| -2.276804
| 64
| 0.054419
| 4,096
| 21
| 4,032
| 1
| 0.458292
| 0.005287
| 10.293361
|
success
| 0.072711
| 0
| 4,032
| 0.005287
| 0.0007
|
|
19
|
model.layers.2.self_attn.q_proj
| 0.085959
| 4,096
| 4,096
| 1
| 8.018122
| -20.184861
| 1.553734
| true
| 0.003038
|
dense
| -20.184489
| -1.360992
| -2.517405
| 64
| 0.043552
| 4,096
| 64
| 4,032
| 1
| 0.877265
| 0.003038
| 14.335519
|
success
| 0.055119
| 0
|
under-trained
| 4,032
| 0.003038
| 0.000566
|
20
|
model.layers.2.self_attn.v_proj
| 0.09117
| 1,024
| 4,096
| 4
| 7.027676
| -20.602752
| 1.12715
| true
| 0.00117
|
dense
| -20.565834
| -1.62459
| -2.931659
| 64
| 0.023736
| 1,024
| 64
| 960
| 1
| 0.753459
| 0.00117
| 20.280077
|
success
| 0.034211
| 0.000001
|
under-trained
| 960
| 0.00117
| 0.000304
|
21
|
model.layers.3.mlp.down_proj
| 0.08119
| 4,096
| 14,336
| 3.5
| 5.102273
| -12.319074
| 1.563152
| true
| 0.003851
|
dense
| -12.153177
| -1.034317
| -2.414429
| 64
| 0.092402
| 4,096
| 10
| 4,032
| 1
| 1.297253
| 0.003851
| 23.994524
|
success
| 0.062056
| 0.000001
| 4,032
| 0.003851
| 0.001462
|
|
22
|
model.layers.3.mlp.gate_proj
| 0.10023
| 4,096
| 14,336
| 3.5
| 3.712471
| -8.48617
| 1.556851
| true
| 0.005178
|
dense
| -8.305467
| -1.050676
| -2.285855
| 64
| 0.088987
| 4,096
| 8
| 4,032
| 1
| 0.959003
| 0.005178
| 17.186176
|
success
| 0.071957
| 0.000001
| 4,032
| 0.005178
| 0.001423
|
|
23
|
model.layers.3.mlp.up_proj
| 0.11905
| 4,096
| 14,336
| 3.5
| 3.594004
| -8.02471
| 1.553261
| true
| 0.005851
|
dense
| -7.847661
| -1.035492
| -2.232805
| 64
| 0.092153
| 4,096
| 9
| 4,032
| 1
| 0.864668
| 0.005851
| 15.75117
|
success
| 0.076489
| 0.000001
| 4,032
| 0.005851
| 0.001451
|
|
24
|
model.layers.3.self_attn.k_proj
| 0.104859
| 1,024
| 4,096
| 4
| 5.604087
| -12.085917
| 1.085087
| true
| 0.006972
|
dense
| -12.084052
| -1.287998
| -2.156626
| 64
| 0.051523
| 1,024
| 64
| 960
| 1
| 0.575511
| 0.006972
| 7.389718
|
success
| 0.0835
| 0.000001
| 960
| 0.006972
| 0.000571
|
|
25
|
model.layers.3.self_attn.o_proj
| 0.063017
| 4,096
| 4,096
| 1
| 4.106814
| -10.249573
| 1.550359
| true
| 0.003193
|
dense
| -10.072092
| -1.276134
| -2.495748
| 64
| 0.05295
| 4,096
| 22
| 4,032
| 1
| 0.662375
| 0.003193
| 16.581116
|
success
| 0.05651
| 0
| 4,032
| 0.003193
| 0.000741
|
|
26
|
model.layers.3.self_attn.q_proj
| 0.067876
| 4,096
| 4,096
| 1
| 3.348291
| -7.814138
| 1.538209
| true
| 0.004637
|
dense
| -7.730213
| -1.295588
| -2.333769
| 64
| 0.05063
| 4,096
| 12
| 4,032
| 1
| 0.677893
| 0.004637
| 10.918955
|
success
| 0.068095
| 0
| 4,032
| 0.004637
| 0.000785
|
|
27
|
model.layers.3.self_attn.v_proj
| 0.070333
| 1,024
| 4,096
| 4
| 5.224446
| -15.4996
| 1.13189
| true
| 0.00108
|
dense
| -15.310787
| -1.573987
| -2.966745
| 64
| 0.026669
| 1,024
| 11
| 960
| 1
| 1.273718
| 0.00108
| 24.70347
|
success
| 0.032857
| 0.000001
| 960
| 0.00108
| 0.000431
|
|
28
|
model.layers.4.mlp.down_proj
| 0.103412
| 4,096
| 14,336
| 3.5
| 6.499501
| -16.271618
| 1.564917
| true
| 0.003137
|
dense
| -16.07889
| -1.03764
| -2.503518
| 64
| 0.091698
| 4,096
| 13
| 4,032
| 1
| 1.525287
| 0.003137
| 29.233288
|
success
| 0.056007
| 0.000001
|
under-trained
| 4,032
| 0.003137
| 0.001422
|
29
|
model.layers.4.mlp.gate_proj
| 0.116253
| 4,096
| 14,336
| 3.5
| 3.795076
| -8.701769
| 1.557888
| true
| 0.005094
|
dense
| -8.544298
| -1.054941
| -2.29291
| 64
| 0.088117
| 4,096
| 7
| 4,032
| 1
| 1.056439
| 0.005094
| 17.296932
|
success
| 0.071375
| 0.000001
| 4,032
| 0.005094
| 0.001453
|
|
30
|
model.layers.4.mlp.up_proj
| 0.12004
| 4,096
| 14,336
| 3.5
| 4.187209
| -9.434501
| 1.55538
| true
| 0.005582
|
dense
| -9.328923
| -1.033906
| -2.253172
| 64
| 0.09249
| 4,096
| 12
| 4,032
| 1
| 0.920068
| 0.005582
| 16.567825
|
success
| 0.074716
| 0.000001
| 4,032
| 0.005582
| 0.001405
|
|
31
|
model.layers.4.self_attn.k_proj
| 0.06627
| 1,024
| 4,096
| 4
| 6.227436
| -16.95982
| 1.127202
| true
| 0.001891
|
dense
| -16.916808
| -1.442925
| -2.723403
| 64
| 0.036064
| 1,024
| 64
| 960
| 1
| 0.653429
| 0.001891
| 19.075619
|
success
| 0.043481
| 0.000001
|
under-trained
| 960
| 0.001891
| 0.00045
|
32
|
model.layers.4.self_attn.o_proj
| 0.051627
| 4,096
| 4,096
| 1
| 4.323554
| -10.8611
| 1.552673
| true
| 0.003076
|
dense
| -10.770511
| -1.30265
| -2.512077
| 64
| 0.049814
| 4,096
| 22
| 4,032
| 1
| 0.708584
| 0.003076
| 16.196711
|
success
| 0.055458
| 0
| 4,032
| 0.003076
| 0.000711
|
|
33
|
model.layers.4.self_attn.q_proj
| 0.079045
| 4,096
| 4,096
| 1
| 7.006285
| -18.277367
| 1.554457
| true
| 0.002462
|
dense
| -18.263869
| -1.388304
| -2.60871
| 64
| 0.040897
| 4,096
| 64
| 4,032
| 1
| 0.750786
| 0.002462
| 16.611397
|
success
| 0.049619
| 0
|
under-trained
| 4,032
| 0.002462
| 0.000519
|
34
|
model.layers.4.self_attn.v_proj
| 0.064339
| 1,024
| 4,096
| 4
| 8.255926
| -25.286125
| 1.132694
| true
| 0.000865
|
dense
| -25.089855
| -1.590087
| -3.062785
| 64
| 0.025699
| 1,024
| 64
| 960
| 1
| 0.906991
| 0.000865
| 29.696016
|
success
| 0.029418
| 0.000001
|
under-trained
| 960
| 0.000865
| 0.000344
|
35
|
model.layers.5.mlp.down_proj
| 0.102415
| 4,096
| 14,336
| 3.5
| 6.801178
| -17.267207
| 1.565843
| true
| 0.002892
|
dense
| -17.055313
| -1.040575
| -2.538856
| 64
| 0.09108
| 4,096
| 11
| 4,032
| 1
| 1.749121
| 0.002892
| 31.497822
|
success
| 0.053774
| 0.000001
|
under-trained
| 4,032
| 0.002892
| 0.001433
|
36
|
model.layers.5.mlp.gate_proj
| 0.101403
| 4,096
| 14,336
| 3.5
| 4.828013
| -11.53821
| 1.561887
| true
| 0.004075
|
dense
| -11.414749
| -1.061174
| -2.389846
| 64
| 0.086861
| 4,096
| 9
| 4,032
| 1
| 1.276004
| 0.004075
| 21.314381
|
success
| 0.063838
| 0.000001
| 4,032
| 0.004075
| 0.00138
|
|
37
|
model.layers.5.mlp.up_proj
| 0.122957
| 4,096
| 14,336
| 3.5
| 4.840966
| -11.489038
| 1.560318
| true
| 0.004234
|
dense
| -11.329233
| -1.041366
| -2.373294
| 64
| 0.090915
| 4,096
| 13
| 4,032
| 1
| 1.065292
| 0.004234
| 21.474775
|
success
| 0.065066
| 0.000001
| 4,032
| 0.004234
| 0.001391
|
|
38
|
model.layers.5.self_attn.k_proj
| 0.058986
| 1,024
| 4,096
| 4
| 6.511588
| -17.164931
| 1.124793
| true
| 0.002312
|
dense
| -17.146604
| -1.41215
| -2.636059
| 64
| 0.038712
| 1,024
| 64
| 960
| 1
| 0.688948
| 0.002312
| 16.745928
|
success
| 0.048081
| 0.000001
|
under-trained
| 960
| 0.002312
| 0.000485
|
39
|
model.layers.5.self_attn.o_proj
| 0.102708
| 4,096
| 4,096
| 1
| 6.50579
| -18.101157
| 1.563011
| true
| 0.001651
|
dense
| -17.909787
| -1.336704
| -2.782315
| 64
| 0.046057
| 4,096
| 25
| 4,032
| 1
| 1.101158
| 0.001651
| 27.900465
|
success
| 0.04063
| 0
|
under-trained
| 4,032
| 0.001651
| 0.000678
|
40
|
model.layers.5.self_attn.q_proj
| 0.075607
| 4,096
| 4,096
| 1
| 8.9117
| -24.09903
| 1.560718
| true
| 0.001976
|
dense
| -24.090758
| -1.387967
| -2.704201
| 64
| 0.040929
| 4,096
| 64
| 4,032
| 1
| 0.988963
| 0.001976
| 20.712568
|
success
| 0.044453
| 0
|
under-trained
| 4,032
| 0.001976
| 0.00055
|
41
|
model.layers.5.self_attn.v_proj
| 0.05698
| 1,024
| 4,096
| 4
| 10.334181
| -32.260235
| 1.135119
| true
| 0.000756
|
dense
| -32.222351
| -1.613308
| -3.121702
| 64
| 0.024361
| 1,024
| 64
| 960
| 1
| 1.166773
| 0.000756
| 32.239906
|
success
| 0.027488
| 0.000001
|
under-trained
| 960
| 0.000756
| 0.000339
|
42
|
model.layers.6.mlp.down_proj
| 0.106362
| 4,096
| 14,336
| 3.5
| 6.931822
| -17.470068
| 1.565562
| true
| 0.003018
|
dense
| -17.290337
| -1.030035
| -2.520271
| 64
| 0.093318
| 4,096
| 14
| 4,032
| 1
| 1.585346
| 0.003018
| 30.919691
|
success
| 0.054937
| 0.000001
|
under-trained
| 4,032
| 0.003018
| 0.001441
|
43
|
model.layers.6.mlp.gate_proj
| 0.089191
| 4,096
| 14,336
| 3.5
| 4.654741
| -10.97667
| 1.560834
| true
| 0.004384
|
dense
| -10.851597
| -1.049342
| -2.35817
| 64
| 0.08926
| 4,096
| 11
| 4,032
| 1
| 1.101946
| 0.004384
| 20.362329
|
success
| 0.066209
| 0.000001
| 4,032
| 0.004384
| 0.001363
|
|
44
|
model.layers.6.mlp.up_proj
| 0.105811
| 4,096
| 14,336
| 3.5
| 4.32534
| -10.156714
| 1.559256
| true
| 0.004486
|
dense
| -9.939353
| -1.027995
| -2.348189
| 64
| 0.093757
| 4,096
| 13
| 4,032
| 1
| 0.922283
| 0.004486
| 20.902269
|
success
| 0.066974
| 0.000001
| 4,032
| 0.004486
| 0.001421
|
|
45
|
model.layers.6.self_attn.k_proj
| 0.056873
| 1,024
| 4,096
| 4
| 6.693871
| -17.802754
| 1.12456
| true
| 0.00219
|
dense
| -17.785555
| -1.437849
| -2.65956
| 64
| 0.036488
| 1,024
| 63
| 960
| 1
| 0.71736
| 0.00219
| 16.661371
|
success
| 0.046797
| 0.000001
|
under-trained
| 960
| 0.00219
| 0.000461
|
46
|
model.layers.6.self_attn.o_proj
| 0.103141
| 4,096
| 4,096
| 1
| 5.320054
| -14.340628
| 1.559961
| true
| 0.002016
|
dense
| -14.170697
| -1.334167
| -2.69558
| 64
| 0.046327
| 4,096
| 20
| 4,032
| 1
| 0.965993
| 0.002016
| 22.983286
|
success
| 0.044896
| 0
| 4,032
| 0.002016
| 0.000693
|
|
47
|
model.layers.6.self_attn.q_proj
| 0.075063
| 4,096
| 4,096
| 1
| 8.53185
| -22.660099
| 1.559597
| true
| 0.002208
|
dense
| -22.658375
| -1.38822
| -2.655942
| 64
| 0.040905
| 4,096
| 64
| 4,032
| 1
| 0.941481
| 0.002208
| 18.523449
|
success
| 0.046993
| 0
|
under-trained
| 4,032
| 0.002208
| 0.000545
|
48
|
model.layers.6.self_attn.v_proj
| 0.053575
| 1,024
| 4,096
| 4
| 10.10451
| -32.271476
| 1.135456
| true
| 0.00064
|
dense
| -31.934859
| -1.60524
| -3.193769
| 64
| 0.024818
| 1,024
| 57
| 960
| 1
| 1.205922
| 0.00064
| 38.773029
|
success
| 0.0253
| 0.000001
|
under-trained
| 960
| 0.00064
| 0.000349
|
49
|
model.layers.7.mlp.down_proj
| 0.131502
| 4,096
| 14,336
| 3.5
| 6.106007
| -15.723402
| 1.566253
| true
| 0.00266
|
dense
| -15.247479
| -1.027381
| -2.575071
| 64
| 0.09389
| 4,096
| 7
| 4,032
| 1
| 1.929889
| 0.00266
| 35.293121
|
success
| 0.051578
| 0.000001
|
under-trained
| 4,032
| 0.00266
| 0.001575
|
50
|
model.layers.7.mlp.gate_proj
| 0.092991
| 4,096
| 14,336
| 3.5
| 4.66407
| -11.037661
| 1.561423
| true
| 0.0043
|
dense
| -10.888869
| -1.039225
| -2.36653
| 64
| 0.091364
| 4,096
| 9
| 4,032
| 1
| 1.221357
| 0.0043
| 21.247375
|
success
| 0.065575
| 0.000001
| 4,032
| 0.0043
| 0.001464
|
|
51
|
model.layers.7.mlp.up_proj
| 0.083526
| 4,096
| 14,336
| 3.5
| 4.418851
| -10.374051
| 1.559826
| true
| 0.004491
|
dense
| -10.158229
| -1.018919
| -2.347681
| 64
| 0.095737
| 4,096
| 12
| 4,032
| 1
| 0.986937
| 0.004491
| 21.318748
|
success
| 0.067013
| 0.000001
| 4,032
| 0.004491
| 0.001482
|
|
52
|
model.layers.7.self_attn.k_proj
| 0.092425
| 1,024
| 4,096
| 4
| 6.301261
| -18.606098
| 1.133596
| true
| 0.001115
|
dense
| -18.203055
| -1.425027
| -2.952758
| 64
| 0.037581
| 1,024
| 47
| 960
| 1
| 0.773268
| 0.001115
| 33.707863
|
success
| 0.03339
| 0.000001
|
under-trained
| 960
| 0.001115
| 0.00051
|
53
|
model.layers.7.self_attn.o_proj
| 0.075342
| 4,096
| 4,096
| 1
| 9.002145
| -25.429427
| 1.564116
| true
| 0.001497
|
dense
| -25.246398
| -1.327605
| -2.824819
| 64
| 0.047032
| 4,096
| 64
| 4,032
| 1
| 1.000268
| 0.001497
| 31.42049
|
success
| 0.038689
| 0
|
under-trained
| 4,032
| 0.001497
| 0.000639
|
54
|
model.layers.7.self_attn.q_proj
| 0.067324
| 4,096
| 4,096
| 1
| 8.272918
| -22.371443
| 1.560991
| true
| 0.001976
|
dense
| -22.349378
| -1.366129
| -2.704178
| 64
| 0.04304
| 4,096
| 64
| 4,032
| 1
| 0.909115
| 0.001976
| 21.779566
|
success
| 0.044454
| 0
|
under-trained
| 4,032
| 0.001976
| 0.000572
|
55
|
model.layers.7.self_attn.v_proj
| 0.035828
| 1,024
| 4,096
| 4
| 11.606042
| -36.820088
| 1.135943
| true
| 0.000672
|
dense
| -36.715384
| -1.592729
| -3.172493
| 64
| 0.025543
| 1,024
| 52
| 960
| 1
| 1.470793
| 0.000672
| 37.998268
|
success
| 0.025927
| 0.000001
|
under-trained
| 960
| 0.000672
| 0.000369
|
56
|
model.layers.8.mlp.down_proj
| 0.143326
| 4,096
| 14,336
| 3.5
| 7.349975
| -18.750527
| 1.565933
| true
| 0.002811
|
dense
| -18.478513
| -1.021602
| -2.551101
| 64
| 0.095148
| 4,096
| 14
| 4,032
| 1
| 1.697102
| 0.002811
| 33.845333
|
success
| 0.053021
| 0.000001
|
under-trained
| 4,032
| 0.002811
| 0.001474
|
57
|
model.layers.8.mlp.gate_proj
| 0.096562
| 4,096
| 14,336
| 3.5
| 4.282198
| -9.903676
| 1.559676
| true
| 0.004867
|
dense
| -9.748083
| -1.023318
| -2.312756
| 64
| 0.094772
| 4,096
| 9
| 4,032
| 1
| 1.094066
| 0.004867
| 19.473211
|
success
| 0.069763
| 0.000001
| 4,032
| 0.004867
| 0.00151
|
|
58
|
model.layers.8.mlp.up_proj
| 0.101449
| 4,096
| 14,336
| 3.5
| 4.470252
| -10.296513
| 1.558773
| true
| 0.004973
|
dense
| -10.135558
| -1.003884
| -2.30334
| 64
| 0.09911
| 4,096
| 13
| 4,032
| 1
| 0.962475
| 0.004973
| 19.927673
|
success
| 0.070523
| 0.000001
| 4,032
| 0.004973
| 0.001524
|
|
59
|
model.layers.8.self_attn.k_proj
| 0.08686
| 1,024
| 4,096
| 4
| 6.646015
| -16.279518
| 1.114718
| true
| 0.003552
|
dense
| -16.2774
| -1.380645
| -2.449516
| 64
| 0.041625
| 1,024
| 64
| 960
| 1
| 0.705752
| 0.003552
| 11.718461
|
success
| 0.059599
| 0.000001
|
under-trained
| 960
| 0.003552
| 0.000513
|
60
|
model.layers.8.self_attn.o_proj
| 0.068692
| 4,096
| 4,096
| 1
| 5.494895
| -14.968555
| 1.562716
| true
| 0.001888
|
dense
| -14.748427
| -1.30508
| -2.724084
| 64
| 0.049536
| 4,096
| 13
| 4,032
| 1
| 1.24666
| 0.001888
| 26.242395
|
success
| 0.043447
| 0
| 4,032
| 0.001888
| 0.000804
|
|
61
|
model.layers.8.self_attn.q_proj
| 0.089713
| 4,096
| 4,096
| 1
| 7.238111
| -17.969642
| 1.553421
| true
| 0.003291
|
dense
| -17.967233
| -1.307936
| -2.482643
| 64
| 0.049211
| 4,096
| 64
| 4,032
| 1
| 0.779764
| 0.003291
| 14.952259
|
success
| 0.057369
| 0
|
under-trained
| 4,032
| 0.003291
| 0.000627
|
62
|
model.layers.8.self_attn.v_proj
| 0.039211
| 1,024
| 4,096
| 4
| 10.635006
| -33.443697
| 1.135642
| true
| 0.000717
|
dense
| -33.337394
| -1.584424
| -3.144681
| 64
| 0.026036
| 1,024
| 53
| 960
| 1
| 1.32347
| 0.000717
| 36.329201
|
success
| 0.026771
| 0.000001
|
under-trained
| 960
| 0.000717
| 0.000372
|
63
|
model.layers.9.mlp.down_proj
| 0.128309
| 4,096
| 14,336
| 3.5
| 8.653824
| -22.723533
| 1.566809
| true
| 0.002367
|
dense
| -22.262528
| -1.019453
| -2.625837
| 64
| 0.09562
| 4,096
| 15
| 4,032
| 1
| 1.976209
| 0.002367
| 40.400311
|
success
| 0.04865
| 0.000001
|
under-trained
| 4,032
| 0.002367
| 0.001492
|
64
|
model.layers.9.mlp.gate_proj
| 0.08722
| 4,096
| 14,336
| 3.5
| 4.630853
| -10.738622
| 1.560123
| true
| 0.004798
|
dense
| -10.615177
| -1.01836
| -2.318929
| 64
| 0.095861
| 4,096
| 10
| 4,032
| 1
| 1.148177
| 0.004798
| 19.978786
|
success
| 0.069268
| 0.000001
| 4,032
| 0.004798
| 0.001535
|
|
65
|
model.layers.9.mlp.up_proj
| 0.095441
| 4,096
| 14,336
| 3.5
| 4.509581
| -10.436652
| 1.559562
| true
| 0.004849
|
dense
| -10.254104
| -0.994814
| -2.314328
| 64
| 0.101201
| 4,096
| 11
| 4,032
| 1
| 1.058179
| 0.004849
| 20.869593
|
success
| 0.069636
| 0.000001
| 4,032
| 0.004849
| 0.001637
|
|
66
|
model.layers.9.self_attn.k_proj
| 0.083743
| 1,024
| 4,096
| 4
| 11.978332
| -36.619759
| 1.136268
| true
| 0.000877
|
dense
| -36.102986
| -1.390942
| -3.057167
| 64
| 0.04065
| 1,024
| 31
| 960
| 1
| 1.971767
| 0.000877
| 46.368629
|
success
| 0.029609
| 0.000001
|
under-trained
| 960
| 0.000877
| 0.000628
|
67
|
model.layers.9.self_attn.o_proj
| 0.063917
| 4,096
| 4,096
| 1
| 9.052659
| -25.969677
| 1.56488
| true
| 0.001353
|
dense
| -25.562036
| -1.315855
| -2.868735
| 64
| 0.048322
| 4,096
| 64
| 4,032
| 1
| 1.006582
| 0.001353
| 35.717358
|
success
| 0.036782
| 0
|
under-trained
| 4,032
| 0.001353
| 0.000658
|
68
|
model.layers.9.self_attn.q_proj
| 0.068104
| 4,096
| 4,096
| 1
| 11.947367
| -34.271361
| 1.566557
| true
| 0.001354
|
dense
| -34.250902
| -1.33759
| -2.868528
| 64
| 0.045963
| 4,096
| 48
| 4,032
| 1
| 1.580116
| 0.001354
| 33.957748
|
success
| 0.036791
| 0
|
under-trained
| 4,032
| 0.001354
| 0.00067
|
69
|
model.layers.9.self_attn.v_proj
| 0.036851
| 1,024
| 4,096
| 4
| 11.726856
| -37.617797
| 1.136089
| true
| 0.00062
|
dense
| -37.503763
| -1.617514
| -3.207833
| 64
| 0.024126
| 1,024
| 43
| 960
| 1
| 1.63583
| 0.00062
| 38.933083
|
success
| 0.024893
| 0.000001
|
under-trained
| 960
| 0.00062
| 0.000355
|
70
|
model.layers.10.mlp.down_proj
| 0.13738
| 4,096
| 14,336
| 3.5
| 6.860931
| -17.709316
| 1.565695
| true
| 0.002623
|
dense
| -17.151487
| -1.01245
| -2.581182
| 64
| 0.097174
| 4,096
| 15
| 4,032
| 1
| 1.513286
| 0.002623
| 37.04528
|
success
| 0.051216
| 0.000001
|
under-trained
| 4,032
| 0.002623
| 0.0015
|
71
|
model.layers.10.mlp.gate_proj
| 0.083743
| 4,096
| 14,336
| 3.5
| 3.814121
| -8.29112
| 1.553266
| true
| 0.006702
|
dense
| -8.192316
| -1.002268
| -2.173796
| 64
| 0.099479
| 4,096
| 10
| 4,032
| 1
| 0.889903
| 0.006702
| 14.843208
|
success
| 0.081866
| 0.000001
| 4,032
| 0.006702
| 0.001555
|
|
72
|
model.layers.10.mlp.up_proj
| 0.083849
| 4,096
| 14,336
| 3.5
| 4.076868
| -8.950159
| 1.554181
| true
| 0.006377
|
dense
| -8.837687
| -0.985078
| -2.195352
| 64
| 0.103496
| 4,096
| 13
| 4,032
| 1
| 0.85337
| 0.006377
| 16.228313
|
success
| 0.079859
| 0.000001
| 4,032
| 0.006377
| 0.001591
|
|
73
|
model.layers.10.self_attn.k_proj
| 0.056769
| 1,024
| 4,096
| 4
| 7.818972
| -21.698837
| 1.132445
| true
| 0.001678
|
dense
| -21.653366
| -1.368847
| -2.775152
| 64
| 0.042771
| 1,024
| 58
| 960
| 1
| 0.895375
| 0.001678
| 25.486191
|
success
| 0.040966
| 0.000001
|
under-trained
| 960
| 0.001678
| 0.000576
|
74
|
model.layers.10.self_attn.o_proj
| 0.070628
| 4,096
| 4,096
| 1
| 8.901525
| -24.73618
| 1.56414
| true
| 0.001664
|
dense
| -24.647737
| -1.30816
| -2.77887
| 64
| 0.049186
| 4,096
| 64
| 4,032
| 1
| 0.987691
| 0.001664
| 29.560369
|
success
| 0.040791
| 0
|
under-trained
| 4,032
| 0.001664
| 0.000667
|
75
|
model.layers.10.self_attn.q_proj
| 0.091471
| 4,096
| 4,096
| 1
| 9.544777
| -25.029251
| 1.561299
| true
| 0.002386
|
dense
| -25.027851
| -1.31183
| -2.622298
| 64
| 0.048772
| 4,096
| 64
| 4,032
| 1
| 1.068097
| 0.002386
| 20.439404
|
success
| 0.048848
| 0
|
under-trained
| 4,032
| 0.002386
| 0.000663
|
76
|
model.layers.10.self_attn.v_proj
| 0.039781
| 1,024
| 4,096
| 4
| 13.460733
| -43.727946
| 1.136434
| true
| 0.000564
|
dense
| -43.467368
| -1.606999
| -3.248556
| 64
| 0.024717
| 1,024
| 34
| 960
| 1
| 2.136998
| 0.000564
| 43.808399
|
success
| 0.023753
| 0.000001
|
under-trained
| 960
| 0.000564
| 0.000377
|
77
|
model.layers.11.mlp.down_proj
| 0.084076
| 4,096
| 14,336
| 3.5
| 8.331583
| -21.69929
| 1.566558
| true
| 0.002486
|
dense
| -21.266779
| -1.013571
| -2.604462
| 64
| 0.096923
| 4,096
| 16
| 4,032
| 1
| 1.832896
| 0.002486
| 38.984375
|
success
| 0.049862
| 0.000001
|
under-trained
| 4,032
| 0.002486
| 0.00151
|
78
|
model.layers.11.mlp.gate_proj
| 0.124518
| 4,096
| 14,336
| 3.5
| 3.566869
| -7.808087
| 1.554186
| true
| 0.006471
|
dense
| -7.641942
| -0.990355
| -2.189059
| 64
| 0.102246
| 4,096
| 8
| 4,032
| 1
| 0.907525
| 0.006471
| 15.801709
|
success
| 0.08044
| 0.000001
| 4,032
| 0.006471
| 0.001697
|
|
79
|
model.layers.11.mlp.up_proj
| 0.105866
| 4,096
| 14,336
| 3.5
| 4.111511
| -9.150791
| 1.555739
| true
| 0.005948
|
dense
| -9.000263
| -0.978656
| -2.225652
| 64
| 0.105037
| 4,096
| 12
| 4,032
| 1
| 0.898216
| 0.005948
| 17.660204
|
success
| 0.077121
| 0.000001
| 4,032
| 0.005948
| 0.001658
|
|
80
|
model.layers.11.self_attn.k_proj
| 0.076034
| 1,024
| 4,096
| 4
| 6.886649
| -17.54321
| 1.125219
| true
| 0.002835
|
dense
| -17.53927
| -1.338794
| -2.547423
| 64
| 0.045836
| 1,024
| 64
| 960
| 1
| 0.735831
| 0.002835
| 16.166996
|
success
| 0.053246
| 0.000001
|
under-trained
| 960
| 0.002835
| 0.000583
|
81
|
model.layers.11.self_attn.o_proj
| 0.082475
| 4,096
| 4,096
| 1
| 9.621523
| -27.295947
| 1.564701
| true
| 0.001456
|
dense
| -27.014932
| -1.307915
| -2.836967
| 64
| 0.049214
| 4,096
| 64
| 4,032
| 1
| 1.07769
| 0.001456
| 33.810543
|
success
| 0.038152
| 0
|
under-trained
| 4,032
| 0.001456
| 0.000676
|
82
|
model.layers.11.self_attn.q_proj
| 0.092576
| 4,096
| 4,096
| 1
| 3.737231
| -9.223967
| 1.553536
| true
| 0.003403
|
dense
| -9.073385
| -1.267686
| -2.468129
| 64
| 0.05399
| 4,096
| 10
| 4,032
| 1
| 0.865588
| 0.003403
| 15.865086
|
success
| 0.058336
| 0
| 4,032
| 0.003403
| 0.00086
|
|
83
|
model.layers.11.self_attn.v_proj
| 0.045068
| 1,024
| 4,096
| 4
| 12.227346
| -39.194857
| 1.136222
| true
| 0.000623
|
dense
| -38.929056
| -1.581387
| -3.205508
| 64
| 0.026219
| 1,024
| 40
| 960
| 1
| 1.775199
| 0.000623
| 42.08437
|
success
| 0.02496
| 0.000001
|
under-trained
| 960
| 0.000623
| 0.00039
|
84
|
model.layers.12.mlp.down_proj
| 0.071737
| 4,096
| 14,336
| 3.5
| 10.463299
| -27.652009
| 1.567254
| true
| 0.002276
|
dense
| -27.278975
| -1.01537
| -2.642762
| 64
| 0.096523
| 4,096
| 17
| 4,032
| 1
| 2.295187
| 0.002276
| 42.402534
|
success
| 0.047711
| 0.000001
|
under-trained
| 4,032
| 0.002276
| 0.001505
|
85
|
model.layers.12.mlp.gate_proj
| 0.093378
| 4,096
| 14,336
| 3.5
| 3.726353
| -8.2903
| 1.556028
| true
| 0.00596
|
dense
| -8.120935
| -0.997856
| -2.224776
| 64
| 0.100495
| 4,096
| 8
| 4,032
| 1
| 0.963911
| 0.00596
| 16.8624
|
success
| 0.077199
| 0.000001
| 4,032
| 0.00596
| 0.001679
|
|
86
|
model.layers.12.mlp.up_proj
| 0.084262
| 4,096
| 14,336
| 3.5
| 4.286353
| -9.666749
| 1.557471
| true
| 0.005556
|
dense
| -9.516003
| -0.984565
| -2.255239
| 64
| 0.103618
| 4,096
| 11
| 4,032
| 1
| 0.990873
| 0.005556
| 18.64978
|
success
| 0.074538
| 0.000001
| 4,032
| 0.005556
| 0.001669
|
|
87
|
model.layers.12.self_attn.k_proj
| 0.048592
| 1,024
| 4,096
| 4
| 5.293701
| -15.09437
| 1.131777
| true
| 0.001408
|
dense
| -14.339401
| -1.297373
| -2.851383
| 64
| 0.050423
| 1,024
| 64
| 960
| 1
| 0.536713
| 0.001408
| 35.810429
|
success
| 0.037524
| 0.000001
| 960
| 0.001408
| 0.00061
|
|
88
|
model.layers.12.self_attn.o_proj
| 0.036461
| 4,096
| 4,096
| 1
| 10.498903
| -30.738891
| 1.566372
| true
| 0.001181
|
dense
| -30.349195
| -1.325973
| -2.927819
| 64
| 0.047209
| 4,096
| 64
| 4,032
| 1
| 1.187363
| 0.001181
| 39.980358
|
success
| 0.034363
| 0
|
under-trained
| 4,032
| 0.001181
| 0.000659
|
89
|
model.layers.12.self_attn.q_proj
| 0.059794
| 4,096
| 4,096
| 1
| 10.446452
| -27.443894
| 1.562977
| true
| 0.00236
|
dense
| -27.443376
| -1.285311
| -2.627102
| 64
| 0.051843
| 4,096
| 62
| 4,032
| 1
| 1.199701
| 0.00236
| 21.968027
|
success
| 0.048579
| 0
|
under-trained
| 4,032
| 0.00236
| 0.000719
|
90
|
model.layers.12.self_attn.v_proj
| 0.056912
| 1,024
| 4,096
| 4
| 14.830225
| -48.769316
| 1.136817
| true
| 0.000515
|
dense
| -48.376759
| -1.608922
| -3.288508
| 64
| 0.024608
| 1,024
| 40
| 960
| 1
| 2.186751
| 0.000515
| 47.817432
|
success
| 0.022685
| 0.000001
|
under-trained
| 960
| 0.000515
| 0.000371
|
91
|
model.layers.13.mlp.down_proj
| 0.101172
| 4,096
| 14,336
| 3.5
| 9.722754
| -25.602905
| 1.566878
| true
| 0.002326
|
dense
| -25.09933
| -1.007937
| -2.633298
| 64
| 0.098189
| 4,096
| 21
| 4,032
| 1
| 1.903461
| 0.002326
| 42.204708
|
success
| 0.048234
| 0.000001
|
under-trained
| 4,032
| 0.002326
| 0.001502
|
92
|
model.layers.13.mlp.gate_proj
| 0.076844
| 4,096
| 14,336
| 3.5
| 4.195623
| -9.25822
| 1.555494
| true
| 0.006214
|
dense
| -9.17138
| -0.996401
| -2.206638
| 64
| 0.100832
| 4,096
| 12
| 4,032
| 1
| 0.922497
| 0.006214
| 16.226952
|
success
| 0.078828
| 0.000001
| 4,032
| 0.006214
| 0.001561
|
|
93
|
model.layers.13.mlp.up_proj
| 0.072975
| 4,096
| 14,336
| 3.5
| 4.54178
| -10.238768
| 1.558146
| true
| 0.005567
|
dense
| -10.13164
| -0.983272
| -2.254352
| 64
| 0.103927
| 4,096
| 12
| 4,032
| 1
| 1.022424
| 0.005567
| 18.667231
|
success
| 0.074615
| 0.000001
| 4,032
| 0.005567
| 0.001665
|
|
94
|
model.layers.13.self_attn.k_proj
| 0.074733
| 1,024
| 4,096
| 4
| 8.151952
| -22.214526
| 1.131022
| true
| 0.001883
|
dense
| -22.195854
| -1.377887
| -2.725056
| 64
| 0.04189
| 1,024
| 63
| 960
| 1
| 0.901061
| 0.001883
| 22.241776
|
success
| 0.043398
| 0.000001
|
under-trained
| 960
| 0.001883
| 0.000559
|
95
|
model.layers.13.self_attn.o_proj
| 0.030219
| 4,096
| 4,096
| 1
| 10.243985
| -29.651683
| 1.566539
| true
| 0.001275
|
dense
| -29.323853
| -1.290212
| -2.894546
| 64
| 0.051261
| 4,096
| 64
| 4,032
| 1
| 1.155498
| 0.001275
| 40.209957
|
success
| 0.035705
| 0
|
under-trained
| 4,032
| 0.001275
| 0.000714
|
96
|
model.layers.13.self_attn.q_proj
| 0.089999
| 4,096
| 4,096
| 1
| 9.241785
| -23.352984
| 1.559237
| true
| 0.002972
|
dense
| -23.352611
| -1.2781
| -2.526891
| 64
| 0.052711
| 4,096
| 64
| 4,032
| 1
| 1.030223
| 0.002972
| 17.733349
|
success
| 0.05452
| 0
|
under-trained
| 4,032
| 0.002972
| 0.00071
|
97
|
model.layers.13.self_attn.v_proj
| 0.06204
| 1,024
| 4,096
| 4
| 17.463952
| -57.035094
| 1.136875
| true
| 0.000542
|
dense
| -56.694075
| -1.577319
| -3.265876
| 64
| 0.026466
| 1,024
| 24
| 960
| 1
| 3.36069
| 0.000542
| 48.815338
|
success
| 0.023284
| 0.000001
|
under-trained
| 960
| 0.000542
| 0.000418
|
98
|
model.layers.14.mlp.down_proj
| 0.082979
| 4,096
| 14,336
| 3.5
| 11.637098
| -31.044017
| 1.567351
| true
| 0.002149
|
dense
| -30.417835
| -0.998153
| -2.667677
| 64
| 0.100426
| 4,096
| 24
| 4,032
| 1
| 2.171288
| 0.002149
| 46.722298
|
success
| 0.046362
| 0.000001
|
under-trained
| 4,032
| 0.002149
| 0.001538
|
99
|
model.layers.14.mlp.gate_proj
| 0.106847
| 4,096
| 14,336
| 3.5
| 4.425835
| -9.716215
| 1.556191
| true
| 0.006378
|
dense
| -9.659478
| -0.990614
| -2.19534
| 64
| 0.102185
| 4,096
| 9
| 4,032
| 1
| 1.141945
| 0.006378
| 16.022362
|
success
| 0.07986
| 0.000001
| 4,032
| 0.006378
| 0.001713
|
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