Dataset Viewer
layer_id
int64 0
223
| name
stringlengths 26
32
| D
float64 0.03
0.12
| M
int64 1.02k
4.1k
| N
int64 4.1k
14.3k
| Q
float64 1
4
| alpha
float64 2.98
23.9
| alpha_weighted
float64 -65.71
-6.41
| entropy
float64 1.11
1.57
| has_esd
bool 1
class | lambda_max
float32 0
0.02
| layer_type
stringclasses 1
value | log_alpha_norm
float64 -64.96
-5.95
| log_norm
float32 -1.43
-0.48
| log_spectral_norm
float32 -2.81
-1.77
| matrix_rank
int64 64
64
| norm
float32 0.04
0.33
| num_evals
int64 1.02k
4.1k
| num_pl_spikes
int64 10
64
| rank_loss
int64 960
4.03k
| rf
int64 1
1
| sigma
float64 0.25
5.88
| spectral_norm
float32 0
0.02
| stable_rank
float32 7.52
56.2
| status
stringclasses 1
value | sv_max
float64 0.04
0.13
| sv_min
float64 0
0
| warning
stringclasses 2
values | weak_rank_loss
int64 960
4.03k
| xmax
float64 0
0.02
| xmin
float64 0
0
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0
|
model.layers.0.mlp.down_proj
| 0.044372
| 4,096
| 14,336
| 3.5
| 8.365172
| -19.331526
| 1.565136
| true
| 0.004887
|
dense
| -18.927617
| -0.749923
| -2.310954
| 64
| 0.17786
| 4,096
| 64
| 4,032
| 1
| 0.920646
| 0.004887
| 36.394131
|
success
| 0.069907
| 0.000001
|
under-trained
| 4,032
| 0.004887
| 0.002397
|
1
|
model.layers.0.mlp.gate_proj
| 0.044792
| 4,096
| 14,336
| 3.5
| 4.921705
| -11.727318
| 1.558989
| true
| 0.004142
|
dense
| -11.388952
| -0.983228
| -2.382775
| 64
| 0.103937
| 4,096
| 27
| 4,032
| 1
| 0.754733
| 0.004142
| 25.092697
|
success
| 0.064359
| 0.000001
| 4,032
| 0.004142
| 0.001486
|
|
2
|
model.layers.0.mlp.up_proj
| 0.05879
| 4,096
| 14,336
| 3.5
| 5.270882
| -12.216789
| 1.559112
| true
| 0.004811
|
dense
| -12.024244
| -0.950149
| -2.317788
| 64
| 0.112163
| 4,096
| 32
| 4,032
| 1
| 0.754992
| 0.004811
| 23.315189
|
success
| 0.069359
| 0.000001
| 4,032
| 0.004811
| 0.001558
|
|
3
|
model.layers.0.self_attn.k_proj
| 0.044862
| 1,024
| 4,096
| 4
| 3.967196
| -10.618157
| 1.116284
| true
| 0.002106
|
dense
| -10.36955
| -1.432019
| -2.676489
| 64
| 0.036981
| 1,024
| 40
| 960
| 1
| 0.469155
| 0.002106
| 17.557785
|
success
| 0.045894
| 0.000001
| 960
| 0.002106
| 0.000457
|
|
4
|
model.layers.0.self_attn.o_proj
| 0.071946
| 4,096
| 4,096
| 1
| 3.15045
| -6.414638
| 1.531436
| true
| 0.009202
|
dense
| -5.951533
| -0.820385
| -2.036102
| 64
| 0.151222
| 4,096
| 45
| 4,032
| 1
| 0.32057
| 0.009202
| 16.43302
|
success
| 0.095929
| 0
| 4,032
| 0.009202
| 0.001521
|
|
5
|
model.layers.0.self_attn.q_proj
| 0.035535
| 4,096
| 4,096
| 1
| 2.977482
| -6.897628
| 1.521928
| true
| 0.004824
|
dense
| -6.518055
| -1.191919
| -2.316598
| 64
| 0.064281
| 4,096
| 64
| 4,032
| 1
| 0.247185
| 0.004824
| 13.325367
|
success
| 0.069455
| 0
| 4,032
| 0.004824
| 0.000518
|
|
6
|
model.layers.0.self_attn.v_proj
| 0.045686
| 1,024
| 4,096
| 4
| 3.300158
| -8.03369
| 1.105158
| true
| 0.003678
|
dense
| -7.724496
| -1.274459
| -2.434335
| 64
| 0.053155
| 1,024
| 24
| 960
| 1
| 0.469518
| 0.003678
| 14.450284
|
success
| 0.06065
| 0.000001
| 960
| 0.003678
| 0.000702
|
|
7
|
model.layers.1.mlp.down_proj
| 0.075648
| 4,096
| 14,336
| 3.5
| 7.65575
| -16.933677
| 1.565563
| true
| 0.006139
|
dense
| -16.84096
| -0.733272
| -2.21189
| 64
| 0.184811
| 4,096
| 13
| 4,032
| 1
| 1.845973
| 0.006139
| 30.103548
|
success
| 0.078353
| 0.000001
|
under-trained
| 4,032
| 0.006139
| 0.002963
|
8
|
model.layers.1.mlp.gate_proj
| 0.112535
| 4,096
| 14,336
| 3.5
| 3.981704
| -8.683508
| 1.556923
| true
| 0.006594
|
dense
| -8.361143
| -0.866137
| -2.180852
| 64
| 0.136102
| 4,096
| 11
| 4,032
| 1
| 0.899018
| 0.006594
| 20.640265
|
success
| 0.081203
| 0.000001
| 4,032
| 0.006594
| 0.002157
|
|
9
|
model.layers.1.mlp.up_proj
| 0.058219
| 4,096
| 14,336
| 3.5
| 5.127727
| -11.404952
| 1.561835
| true
| 0.005968
|
dense
| -11.187414
| -0.83321
| -2.224173
| 64
| 0.146822
| 4,096
| 13
| 4,032
| 1
| 1.144825
| 0.005968
| 24.601585
|
success
| 0.077253
| 0.000001
| 4,032
| 0.005968
| 0.002357
|
|
10
|
model.layers.1.self_attn.k_proj
| 0.043356
| 1,024
| 4,096
| 4
| 4.768239
| -12.602271
| 1.124037
| true
| 0.002275
|
dense
| -12.498928
| -1.378174
| -2.642962
| 64
| 0.041863
| 1,024
| 56
| 960
| 1
| 0.503552
| 0.002275
| 18.398703
|
success
| 0.0477
| 0.000001
| 960
| 0.002275
| 0.000498
|
|
11
|
model.layers.1.self_attn.o_proj
| 0.053403
| 4,096
| 4,096
| 1
| 3.869334
| -7.790337
| 1.546909
| true
| 0.009697
|
dense
| -7.571464
| -0.793234
| -2.013354
| 64
| 0.160978
| 4,096
| 32
| 4,032
| 1
| 0.507231
| 0.009697
| 16.600451
|
success
| 0.098474
| 0
| 4,032
| 0.009697
| 0.00206
|
|
12
|
model.layers.1.self_attn.q_proj
| 0.040165
| 4,096
| 4,096
| 1
| 4.360187
| -10.607257
| 1.54881
| true
| 0.003692
|
dense
| -10.532897
| -1.257076
| -2.432753
| 64
| 0.055325
| 4,096
| 62
| 4,032
| 1
| 0.426744
| 0.003692
| 14.985688
|
success
| 0.060761
| 0
| 4,032
| 0.003692
| 0.000609
|
|
13
|
model.layers.1.self_attn.v_proj
| 0.029854
| 1,024
| 4,096
| 4
| 5.583189
| -15.041438
| 1.130228
| true
| 0.002023
|
dense
| -14.569543
| -1.219971
| -2.694058
| 64
| 0.06026
| 1,024
| 53
| 960
| 1
| 0.629549
| 0.002023
| 29.791128
|
success
| 0.044975
| 0.000001
| 960
| 0.002023
| 0.000769
|
|
14
|
model.layers.2.mlp.down_proj
| 0.055346
| 4,096
| 14,336
| 3.5
| 15.095443
| -34.764815
| 1.567153
| true
| 0.004977
|
dense
| -34.647397
| -0.697174
| -2.303001
| 64
| 0.200829
| 4,096
| 64
| 4,032
| 1
| 1.76193
| 0.004977
| 40.348392
|
success
| 0.07055
| 0.000001
|
under-trained
| 4,032
| 0.004977
| 0.002909
|
15
|
model.layers.2.mlp.gate_proj
| 0.069836
| 4,096
| 14,336
| 3.5
| 7.014292
| -15.802
| 1.564927
| true
| 0.005587
|
dense
| -15.72346
| -0.811401
| -2.252829
| 64
| 0.154383
| 4,096
| 13
| 4,032
| 1
| 1.668065
| 0.005587
| 27.63302
|
success
| 0.074746
| 0.000001
|
under-trained
| 4,032
| 0.005587
| 0.002453
|
16
|
model.layers.2.mlp.up_proj
| 0.058174
| 4,096
| 14,336
| 3.5
| 6.622721
| -14.627589
| 1.564325
| true
| 0.006184
|
dense
| -14.520681
| -0.773311
| -2.208698
| 64
| 0.168535
| 4,096
| 15
| 4,032
| 1
| 1.45178
| 0.006184
| 27.251282
|
success
| 0.078641
| 0.000001
|
under-trained
| 4,032
| 0.006184
| 0.002648
|
17
|
model.layers.2.self_attn.k_proj
| 0.059239
| 1,024
| 4,096
| 4
| 8.314302
| -22.293065
| 1.133351
| true
| 0.002083
|
dense
| -22.094893
| -1.15985
| -2.681291
| 64
| 0.069207
| 1,024
| 15
| 960
| 1
| 1.888545
| 0.002083
| 33.223221
|
success
| 0.045641
| 0.000001
|
under-trained
| 960
| 0.002083
| 0.001193
|
18
|
model.layers.2.self_attn.o_proj
| 0.043211
| 4,096
| 4,096
| 1
| 4.301974
| -9.517501
| 1.553272
| true
| 0.006133
|
dense
| -9.028854
| -0.828736
| -2.212357
| 64
| 0.148342
| 4,096
| 58
| 4,032
| 1
| 0.43357
| 0.006133
| 24.189142
|
success
| 0.078311
| 0
| 4,032
| 0.006133
| 0.001669
|
|
19
|
model.layers.2.self_attn.q_proj
| 0.036099
| 4,096
| 4,096
| 1
| 7.774757
| -19.31455
| 1.563217
| true
| 0.003279
|
dense
| -19.277754
| -1.073739
| -2.484264
| 64
| 0.084384
| 4,096
| 43
| 4,032
| 1
| 1.033141
| 0.003279
| 25.735031
|
success
| 0.057262
| 0
|
under-trained
| 4,032
| 0.003279
| 0.001195
|
20
|
model.layers.2.self_attn.v_proj
| 0.039486
| 1,024
| 4,096
| 4
| 5.728909
| -15.094938
| 1.131631
| true
| 0.002318
|
dense
| -14.438458
| -1.097779
| -2.634871
| 64
| 0.07984
| 1,024
| 62
| 960
| 1
| 0.600572
| 0.002318
| 34.442307
|
success
| 0.048146
| 0.000001
| 960
| 0.002318
| 0.000994
|
|
21
|
model.layers.3.mlp.down_proj
| 0.079373
| 4,096
| 14,336
| 3.5
| 15.131404
| -33.785049
| 1.566826
| true
| 0.005851
|
dense
| -33.759555
| -0.672238
| -2.232777
| 64
| 0.212697
| 4,096
| 64
| 4,032
| 1
| 1.766426
| 0.005851
| 36.352871
|
success
| 0.076491
| 0.000001
|
under-trained
| 4,032
| 0.005851
| 0.003079
|
22
|
model.layers.3.mlp.gate_proj
| 0.089666
| 4,096
| 14,336
| 3.5
| 6.122937
| -13.159611
| 1.563872
| true
| 0.007092
|
dense
| -13.073512
| -0.752022
| -2.149232
| 64
| 0.177002
| 4,096
| 10
| 4,032
| 1
| 1.620015
| 0.007092
| 24.958031
|
success
| 0.084214
| 0.000001
|
under-trained
| 4,032
| 0.007092
| 0.002905
|
23
|
model.layers.3.mlp.up_proj
| 0.097207
| 4,096
| 14,336
| 3.5
| 7.223045
| -15.33708
| 1.56381
| true
| 0.007527
|
dense
| -15.292052
| -0.716858
| -2.123354
| 64
| 0.191929
| 4,096
| 19
| 4,032
| 1
| 1.427664
| 0.007527
| 25.497366
|
success
| 0.086761
| 0.000001
|
under-trained
| 4,032
| 0.007527
| 0.002949
|
24
|
model.layers.3.self_attn.k_proj
| 0.053499
| 1,024
| 4,096
| 4
| 6.338608
| -17.415424
| 1.130776
| true
| 0.001788
|
dense
| -17.103588
| -1.292547
| -2.747516
| 64
| 0.050986
| 1,024
| 64
| 960
| 1
| 0.667326
| 0.001788
| 28.508137
|
success
| 0.04229
| 0.000001
|
under-trained
| 960
| 0.001788
| 0.000645
|
25
|
model.layers.3.self_attn.o_proj
| 0.031086
| 4,096
| 4,096
| 1
| 5.812814
| -13.425333
| 1.561421
| true
| 0.004902
|
dense
| -13.015641
| -0.83379
| -2.30961
| 64
| 0.146626
| 4,096
| 62
| 4,032
| 1
| 0.611228
| 0.004902
| 29.910252
|
success
| 0.070016
| 0
| 4,032
| 0.004902
| 0.001826
|
|
26
|
model.layers.3.self_attn.q_proj
| 0.033947
| 4,096
| 4,096
| 1
| 5.52264
| -13.971607
| 1.559661
| true
| 0.002952
|
dense
| -13.88557
| -1.195202
| -2.529878
| 64
| 0.063797
| 4,096
| 62
| 4,032
| 1
| 0.574376
| 0.002952
| 21.61108
|
success
| 0.054333
| 0
| 4,032
| 0.002952
| 0.000781
|
|
27
|
model.layers.3.self_attn.v_proj
| 0.031332
| 1,024
| 4,096
| 4
| 8.437461
| -21.783879
| 1.1343
| true
| 0.002619
|
dense
| -21.660868
| -1.074053
| -2.581805
| 64
| 0.084323
| 1,024
| 43
| 960
| 1
| 1.134202
| 0.002619
| 32.192299
|
success
| 0.05118
| 0.000001
|
under-trained
| 960
| 0.002619
| 0.001206
|
28
|
model.layers.4.mlp.down_proj
| 0.076604
| 4,096
| 14,336
| 3.5
| 14.993147
| -33.140575
| 1.566824
| true
| 0.006161
|
dense
| -33.082934
| -0.636412
| -2.210382
| 64
| 0.230987
| 4,096
| 64
| 4,032
| 1
| 1.749143
| 0.006161
| 37.494659
|
success
| 0.078489
| 0.000001
|
under-trained
| 4,032
| 0.006161
| 0.003341
|
29
|
model.layers.4.mlp.gate_proj
| 0.071158
| 4,096
| 14,336
| 3.5
| 5.423075
| -11.23735
| 1.562094
| true
| 0.00847
|
dense
| -11.120026
| -0.70997
| -2.072136
| 64
| 0.194998
| 4,096
| 12
| 4,032
| 1
| 1.276832
| 0.00847
| 23.02322
|
success
| 0.092031
| 0.000001
| 4,032
| 0.00847
| 0.003126
|
|
30
|
model.layers.4.mlp.up_proj
| 0.058521
| 4,096
| 14,336
| 3.5
| 6.87642
| -14.190751
| 1.562732
| true
| 0.008636
|
dense
| -14.10596
| -0.656931
| -2.063683
| 64
| 0.220328
| 4,096
| 29
| 4,032
| 1
| 1.091224
| 0.008636
| 25.512463
|
success
| 0.092931
| 0.000001
|
under-trained
| 4,032
| 0.008636
| 0.003203
|
31
|
model.layers.4.self_attn.k_proj
| 0.07151
| 1,024
| 4,096
| 4
| 8.27638
| -22.574322
| 1.132434
| true
| 0.001873
|
dense
| -22.013693
| -1.143497
| -2.72756
| 64
| 0.071863
| 1,024
| 22
| 960
| 1
| 1.55133
| 0.001873
| 38.37632
|
success
| 0.043273
| 0.000001
|
under-trained
| 960
| 0.001873
| 0.001211
|
32
|
model.layers.4.self_attn.o_proj
| 0.039916
| 4,096
| 4,096
| 1
| 5.481292
| -12.934991
| 1.561933
| true
| 0.004367
|
dense
| -12.256102
| -0.825011
| -2.359844
| 64
| 0.14962
| 4,096
| 62
| 4,032
| 1
| 0.569125
| 0.004367
| 34.263561
|
success
| 0.066081
| 0
| 4,032
| 0.004367
| 0.001837
|
|
33
|
model.layers.4.self_attn.q_proj
| 0.043186
| 4,096
| 4,096
| 1
| 7.05384
| -17.32022
| 1.56158
| true
| 0.003504
|
dense
| -17.280596
| -1.078193
| -2.455431
| 64
| 0.083523
| 4,096
| 22
| 4,032
| 1
| 1.290683
| 0.003504
| 23.83625
|
success
| 0.059195
| 0
|
under-trained
| 4,032
| 0.003504
| 0.001334
|
34
|
model.layers.4.self_attn.v_proj
| 0.051123
| 1,024
| 4,096
| 4
| 8.01902
| -21.363418
| 1.13487
| true
| 0.002167
|
dense
| -20.8389
| -1.065824
| -2.664093
| 64
| 0.085936
| 1,024
| 41
| 960
| 1
| 1.096187
| 0.002167
| 39.652363
|
success
| 0.046554
| 0.000001
|
under-trained
| 960
| 0.002167
| 0.001234
|
35
|
model.layers.5.mlp.down_proj
| 0.064079
| 4,096
| 14,336
| 3.5
| 15.944951
| -34.872978
| 1.567136
| true
| 0.0065
|
dense
| -34.853326
| -0.608785
| -2.187086
| 64
| 0.246158
| 4,096
| 64
| 4,032
| 1
| 1.868119
| 0.0065
| 37.870461
|
success
| 0.080623
| 0.000001
|
under-trained
| 4,032
| 0.0065
| 0.003581
|
36
|
model.layers.5.mlp.gate_proj
| 0.096163
| 4,096
| 14,336
| 3.5
| 5.903078
| -12.108724
| 1.562384
| true
| 0.008887
|
dense
| -12.002394
| -0.671732
| -2.051256
| 64
| 0.212945
| 4,096
| 16
| 4,032
| 1
| 1.225769
| 0.008887
| 23.96207
|
success
| 0.09427
| 0.000001
| 4,032
| 0.008887
| 0.003285
|
|
37
|
model.layers.5.mlp.up_proj
| 0.060143
| 4,096
| 14,336
| 3.5
| 6.366293
| -12.982274
| 1.56298
| true
| 0.009136
|
dense
| -12.837507
| -0.616751
| -2.03922
| 64
| 0.241685
| 4,096
| 20
| 4,032
| 1
| 1.19994
| 0.009136
| 26.452679
|
success
| 0.095585
| 0.000001
|
under-trained
| 4,032
| 0.009136
| 0.003693
|
38
|
model.layers.5.self_attn.k_proj
| 0.042857
| 1,024
| 4,096
| 4
| 6.45947
| -17.316833
| 1.133314
| true
| 0.002085
|
dense
| -16.710907
| -1.118405
| -2.680844
| 64
| 0.076137
| 1,024
| 59
| 960
| 1
| 0.710762
| 0.002085
| 36.512318
|
success
| 0.045664
| 0.000001
|
under-trained
| 960
| 0.002085
| 0.00099
|
39
|
model.layers.5.self_attn.o_proj
| 0.03663
| 4,096
| 4,096
| 1
| 7.81447
| -19.20972
| 1.565988
| true
| 0.003482
|
dense
| -18.370583
| -0.812658
| -2.458224
| 64
| 0.153937
| 4,096
| 51
| 4,032
| 1
| 0.954217
| 0.003482
| 44.214661
|
success
| 0.059005
| 0
|
under-trained
| 4,032
| 0.003482
| 0.00213
|
40
|
model.layers.5.self_attn.q_proj
| 0.039347
| 4,096
| 4,096
| 1
| 7.181912
| -17.746361
| 1.563375
| true
| 0.003381
|
dense
| -17.677551
| -1.044679
| -2.47098
| 64
| 0.090224
| 4,096
| 38
| 4,032
| 1
| 1.002839
| 0.003381
| 26.687077
|
success
| 0.058145
| 0
|
under-trained
| 4,032
| 0.003381
| 0.001293
|
41
|
model.layers.5.self_attn.v_proj
| 0.074037
| 1,024
| 4,096
| 4
| 9.685775
| -26.449586
| 1.13634
| true
| 0.001859
|
dense
| -25.600858
| -1.046485
| -2.730766
| 64
| 0.089849
| 1,024
| 56
| 960
| 1
| 1.160686
| 0.001859
| 48.337158
|
success
| 0.043114
| 0.000001
|
under-trained
| 960
| 0.001859
| 0.001266
|
42
|
model.layers.6.mlp.down_proj
| 0.095639
| 4,096
| 14,336
| 3.5
| 14.635101
| -31.146394
| 1.566578
| true
| 0.007444
|
dense
| -31.129475
| -0.582811
| -2.128198
| 64
| 0.26133
| 4,096
| 64
| 4,032
| 1
| 1.704388
| 0.007444
| 35.10651
|
success
| 0.086278
| 0.000001
|
under-trained
| 4,032
| 0.007444
| 0.00377
|
43
|
model.layers.6.mlp.gate_proj
| 0.069643
| 4,096
| 14,336
| 3.5
| 5.839907
| -11.692018
| 1.561022
| true
| 0.009952
|
dense
| -11.543849
| -0.621106
| -2.00209
| 64
| 0.239273
| 4,096
| 26
| 4,032
| 1
| 0.949184
| 0.009952
| 24.042736
|
success
| 0.09976
| 0.000001
| 4,032
| 0.009952
| 0.003457
|
|
44
|
model.layers.6.mlp.up_proj
| 0.071441
| 4,096
| 14,336
| 3.5
| 5.83869
| -11.695706
| 1.56181
| true
| 0.009928
|
dense
| -11.448427
| -0.575978
| -2.003139
| 64
| 0.265474
| 4,096
| 23
| 4,032
| 1
| 1.008937
| 0.009928
| 26.739985
|
success
| 0.099639
| 0.000001
| 4,032
| 0.009928
| 0.003958
|
|
45
|
model.layers.6.self_attn.k_proj
| 0.053588
| 1,024
| 4,096
| 4
| 6.589289
| -17.636502
| 1.133221
| true
| 0.002106
|
dense
| -17.076734
| -1.121298
| -2.676541
| 64
| 0.075631
| 1,024
| 64
| 960
| 1
| 0.698661
| 0.002106
| 35.912281
|
success
| 0.045891
| 0.000001
|
under-trained
| 960
| 0.002106
| 0.000972
|
46
|
model.layers.6.self_attn.o_proj
| 0.028815
| 4,096
| 4,096
| 1
| 6.851371
| -16.127938
| 1.564554
| true
| 0.004426
|
dense
| -15.613682
| -0.798362
| -2.353972
| 64
| 0.159088
| 4,096
| 64
| 4,032
| 1
| 0.731421
| 0.004426
| 35.942707
|
success
| 0.066529
| 0
|
under-trained
| 4,032
| 0.004426
| 0.002065
|
47
|
model.layers.6.self_attn.q_proj
| 0.045633
| 4,096
| 4,096
| 1
| 6.070915
| -14.817944
| 1.562566
| true
| 0.003624
|
dense
| -14.683584
| -1.024928
| -2.440809
| 64
| 0.094422
| 4,096
| 64
| 4,032
| 1
| 0.633864
| 0.003624
| 26.054392
|
success
| 0.0602
| 0
|
under-trained
| 4,032
| 0.003624
| 0.001186
|
48
|
model.layers.6.self_attn.v_proj
| 0.04742
| 1,024
| 4,096
| 4
| 10.374022
| -27.161139
| 1.135434
| true
| 0.002409
|
dense
| -26.936849
| -1.031026
| -2.618188
| 64
| 0.093105
| 1,024
| 20
| 960
| 1
| 2.096095
| 0.002409
| 38.65107
|
success
| 0.04908
| 0.000001
|
under-trained
| 960
| 0.002409
| 0.001501
|
49
|
model.layers.7.mlp.down_proj
| 0.063456
| 4,096
| 14,336
| 3.5
| 15.614345
| -33.627184
| 1.567221
| true
| 0.007021
|
dense
| -33.590977
| -0.559208
| -2.153608
| 64
| 0.275926
| 4,096
| 64
| 4,032
| 1
| 1.826793
| 0.007021
| 39.300701
|
success
| 0.083791
| 0.000001
|
under-trained
| 4,032
| 0.007021
| 0.004009
|
50
|
model.layers.7.mlp.gate_proj
| 0.054805
| 4,096
| 14,336
| 3.5
| 5.579458
| -11.013746
| 1.561041
| true
| 0.010617
|
dense
| -10.847327
| -0.592793
| -1.973981
| 64
| 0.255392
| 4,096
| 21
| 4,032
| 1
| 0.99932
| 0.010617
| 24.05406
|
success
| 0.103041
| 0.000001
| 4,032
| 0.010617
| 0.003834
|
|
51
|
model.layers.7.mlp.up_proj
| 0.063687
| 4,096
| 14,336
| 3.5
| 5.60456
| -11.151875
| 1.562231
| true
| 0.010238
|
dense
| -10.824994
| -0.543541
| -1.989786
| 64
| 0.286062
| 4,096
| 19
| 4,032
| 1
| 1.056359
| 0.010238
| 27.941221
|
success
| 0.101183
| 0.000001
| 4,032
| 0.010238
| 0.004375
|
|
52
|
model.layers.7.self_attn.k_proj
| 0.095712
| 1,024
| 4,096
| 4
| 10.705249
| -27.8816
| 1.133918
| true
| 0.002486
|
dense
| -27.546094
| -1.011718
| -2.604479
| 64
| 0.097338
| 1,024
| 18
| 960
| 1
| 2.287549
| 0.002486
| 39.152649
|
success
| 0.049861
| 0.000001
|
under-trained
| 960
| 0.002486
| 0.001678
|
53
|
model.layers.7.self_attn.o_proj
| 0.065757
| 4,096
| 4,096
| 1
| 11.30707
| -27.335589
| 1.566889
| true
| 0.003823
|
dense
| -26.685796
| -0.751225
| -2.417566
| 64
| 0.177327
| 4,096
| 25
| 4,032
| 1
| 2.061414
| 0.003823
| 46.381084
|
success
| 0.061833
| 0
|
under-trained
| 4,032
| 0.003823
| 0.002786
|
54
|
model.layers.7.self_attn.q_proj
| 0.025897
| 4,096
| 4,096
| 1
| 7.524983
| -17.814964
| 1.563334
| true
| 0.004291
|
dense
| -17.77534
| -0.956906
| -2.367442
| 64
| 0.110432
| 4,096
| 39
| 4,032
| 1
| 1.044834
| 0.004291
| 25.73575
|
success
| 0.065506
| 0
|
under-trained
| 4,032
| 0.004291
| 0.001579
|
55
|
model.layers.7.self_attn.v_proj
| 0.073396
| 1,024
| 4,096
| 4
| 15.267755
| -41.123873
| 1.13667
| true
| 0.002025
|
dense
| -40.442663
| -0.988075
| -2.693511
| 64
| 0.102784
| 1,024
| 26
| 960
| 1
| 2.798137
| 0.002025
| 50.750072
|
success
| 0.045003
| 0.000001
|
under-trained
| 960
| 0.002025
| 0.001623
|
56
|
model.layers.8.mlp.down_proj
| 0.066821
| 4,096
| 14,336
| 3.5
| 14.244871
| -30.541354
| 1.567048
| true
| 0.007178
|
dense
| -30.44064
| -0.543448
| -2.144025
| 64
| 0.286123
| 4,096
| 64
| 4,032
| 1
| 1.655609
| 0.007178
| 39.863625
|
success
| 0.08472
| 0.000001
|
under-trained
| 4,032
| 0.007178
| 0.004125
|
57
|
model.layers.8.mlp.gate_proj
| 0.057102
| 4,096
| 14,336
| 3.5
| 5.478192
| -10.632148
| 1.56052
| true
| 0.01146
|
dense
| -10.447779
| -0.562441
| -1.940813
| 64
| 0.273879
| 4,096
| 22
| 4,032
| 1
| 0.954754
| 0.01146
| 23.898603
|
success
| 0.107052
| 0.000001
| 4,032
| 0.01146
| 0.00408
|
|
58
|
model.layers.8.mlp.up_proj
| 0.052789
| 4,096
| 14,336
| 3.5
| 5.877397
| -11.587908
| 1.562137
| true
| 0.010676
|
dense
| -11.257199
| -0.517431
| -1.971605
| 64
| 0.303787
| 4,096
| 25
| 4,032
| 1
| 0.975479
| 0.010676
| 28.456011
|
success
| 0.103323
| 0.000001
| 4,032
| 0.010676
| 0.004476
|
|
59
|
model.layers.8.self_attn.k_proj
| 0.064081
| 1,024
| 4,096
| 4
| 6.659156
| -17.477803
| 1.132918
| true
| 0.002373
|
dense
| -16.862688
| -1.065404
| -2.624627
| 64
| 0.086019
| 1,024
| 64
| 960
| 1
| 0.707395
| 0.002373
| 36.242973
|
success
| 0.048718
| 0.000001
|
under-trained
| 960
| 0.002373
| 0.001107
|
60
|
model.layers.8.self_attn.o_proj
| 0.050797
| 4,096
| 4,096
| 1
| 9.906003
| -23.957714
| 1.566807
| true
| 0.003815
|
dense
| -23.247362
| -0.75672
| -2.418505
| 64
| 0.175098
| 4,096
| 39
| 4,032
| 1
| 1.426102
| 0.003815
| 45.897057
|
success
| 0.061766
| 0
|
under-trained
| 4,032
| 0.003815
| 0.002583
|
61
|
model.layers.8.self_attn.q_proj
| 0.064969
| 4,096
| 4,096
| 1
| 6.653043
| -16.193501
| 1.563653
| true
| 0.003681
|
dense
| -16.003354
| -0.962644
| -2.433999
| 64
| 0.108982
| 4,096
| 40
| 4,032
| 1
| 0.893825
| 0.003681
| 29.604328
|
success
| 0.060674
| 0
|
under-trained
| 4,032
| 0.003681
| 0.001538
|
62
|
model.layers.8.self_attn.v_proj
| 0.035499
| 1,024
| 4,096
| 4
| 12.053037
| -31.042204
| 1.135992
| true
| 0.002658
|
dense
| -30.961366
| -0.991929
| -2.575467
| 64
| 0.101876
| 1,024
| 28
| 960
| 1
| 2.088828
| 0.002658
| 38.329998
|
success
| 0.051554
| 0.000001
|
under-trained
| 960
| 0.002658
| 0.001577
|
63
|
model.layers.9.mlp.down_proj
| 0.044913
| 4,096
| 14,336
| 3.5
| 15.129803
| -32.638446
| 1.567325
| true
| 0.006963
|
dense
| -32.531992
| -0.537594
| -2.157229
| 64
| 0.290005
| 4,096
| 64
| 4,032
| 1
| 1.766225
| 0.006963
| 41.651878
|
success
| 0.083442
| 0.000001
|
under-trained
| 4,032
| 0.006963
| 0.004205
|
64
|
model.layers.9.mlp.gate_proj
| 0.05434
| 4,096
| 14,336
| 3.5
| 5.696961
| -11.08356
| 1.561272
| true
| 0.011336
|
dense
| -10.893989
| -0.545201
| -1.945521
| 64
| 0.28497
| 4,096
| 24
| 4,032
| 1
| 0.958763
| 0.011336
| 25.137403
|
success
| 0.106473
| 0.000001
| 4,032
| 0.011336
| 0.004224
|
|
65
|
model.layers.9.mlp.up_proj
| 0.043738
| 4,096
| 14,336
| 3.5
| 6.431358
| -12.675255
| 1.562701
| true
| 0.010694
|
dense
| -12.390135
| -0.503689
| -1.970852
| 64
| 0.313553
| 4,096
| 37
| 4,032
| 1
| 0.89291
| 0.010694
| 29.319954
|
success
| 0.103413
| 0.000001
|
under-trained
| 4,032
| 0.010694
| 0.00438
|
66
|
model.layers.9.self_attn.k_proj
| 0.064809
| 1,024
| 4,096
| 4
| 6.66346
| -16.885243
| 1.134151
| true
| 0.002924
|
dense
| -16.205545
| -0.939375
| -2.534005
| 64
| 0.114981
| 1,024
| 46
| 960
| 1
| 0.835032
| 0.002924
| 39.32151
|
success
| 0.054075
| 0.000001
|
under-trained
| 960
| 0.002924
| 0.001582
|
67
|
model.layers.9.self_attn.o_proj
| 0.044989
| 4,096
| 4,096
| 1
| 11.027726
| -26.397476
| 1.567061
| true
| 0.004039
|
dense
| -25.734566
| -0.722971
| -2.393737
| 64
| 0.189247
| 4,096
| 37
| 4,032
| 1
| 1.648548
| 0.004039
| 46.85614
|
success
| 0.063552
| 0
|
under-trained
| 4,032
| 0.004039
| 0.002835
|
68
|
model.layers.9.self_attn.q_proj
| 0.041058
| 4,096
| 4,096
| 1
| 8.645273
| -20.432758
| 1.564777
| true
| 0.004331
|
dense
| -20.36518
| -0.882691
| -2.36346
| 64
| 0.131011
| 4,096
| 27
| 4,032
| 1
| 1.471333
| 0.004331
| 30.253063
|
success
| 0.065807
| 0
|
under-trained
| 4,032
| 0.004331
| 0.002014
|
69
|
model.layers.9.self_attn.v_proj
| 0.048063
| 1,024
| 4,096
| 4
| 17.18794
| -45.376271
| 1.136577
| true
| 0.002291
|
dense
| -45.223033
| -0.980125
| -2.640006
| 64
| 0.104683
| 1,024
| 18
| 960
| 1
| 3.815534
| 0.002291
| 45.696308
|
success
| 0.047863
| 0.000001
|
under-trained
| 960
| 0.002291
| 0.001711
|
70
|
model.layers.10.mlp.down_proj
| 0.057979
| 4,096
| 14,336
| 3.5
| 13.5763
| -29.123454
| 1.56707
| true
| 0.007159
|
dense
| -28.963528
| -0.534644
| -2.145169
| 64
| 0.291982
| 4,096
| 64
| 4,032
| 1
| 1.572037
| 0.007159
| 40.787243
|
success
| 0.084609
| 0.000001
|
under-trained
| 4,032
| 0.007159
| 0.004192
|
71
|
model.layers.10.mlp.gate_proj
| 0.047552
| 4,096
| 14,336
| 3.5
| 5.482743
| -10.2929
| 1.558314
| true
| 0.013264
|
dense
| -10.129917
| -0.529934
| -1.877327
| 64
| 0.295166
| 4,096
| 38
| 4,032
| 1
| 0.727197
| 0.013264
| 22.253223
|
success
| 0.115169
| 0.000001
| 4,032
| 0.013264
| 0.00397
|
|
72
|
model.layers.10.mlp.up_proj
| 0.054996
| 4,096
| 14,336
| 3.5
| 6.165837
| -11.655581
| 1.559779
| true
| 0.012872
|
dense
| -11.462149
| -0.498474
| -1.890349
| 64
| 0.317341
| 4,096
| 51
| 4,032
| 1
| 0.723362
| 0.012872
| 24.653248
|
success
| 0.113456
| 0.000001
|
under-trained
| 4,032
| 0.012872
| 0.004137
|
73
|
model.layers.10.self_attn.k_proj
| 0.050952
| 1,024
| 4,096
| 4
| 6.928386
| -17.629741
| 1.133472
| true
| 0.002854
|
dense
| -17.102107
| -0.987223
| -2.544567
| 64
| 0.102986
| 1,024
| 63
| 960
| 1
| 0.746906
| 0.002854
| 36.08643
|
success
| 0.053422
| 0.000001
|
under-trained
| 960
| 0.002854
| 0.001342
|
74
|
model.layers.10.self_attn.o_proj
| 0.039311
| 4,096
| 4,096
| 1
| 8.08292
| -17.884937
| 1.564299
| true
| 0.006128
|
dense
| -17.605788
| -0.702513
| -2.212683
| 64
| 0.198375
| 4,096
| 60
| 4,032
| 1
| 0.914401
| 0.006128
| 32.37204
|
success
| 0.078281
| 0
|
under-trained
| 4,032
| 0.006128
| 0.002677
|
75
|
model.layers.10.self_attn.q_proj
| 0.060079
| 4,096
| 4,096
| 1
| 8.799813
| -21.045494
| 1.564504
| true
| 0.004059
|
dense
| -20.972091
| -0.900797
| -2.391584
| 64
| 0.125662
| 4,096
| 23
| 4,032
| 1
| 1.626373
| 0.004059
| 30.95904
|
success
| 0.06371
| 0
|
under-trained
| 4,032
| 0.004059
| 0.002024
|
76
|
model.layers.10.self_attn.v_proj
| 0.044839
| 1,024
| 4,096
| 4
| 11.125341
| -28.627597
| 1.135937
| true
| 0.002672
|
dense
| -28.327318
| -0.957065
| -2.573188
| 64
| 0.110391
| 1,024
| 38
| 960
| 1
| 1.642547
| 0.002672
| 41.316521
|
success
| 0.05169
| 0.000001
|
under-trained
| 960
| 0.002672
| 0.001649
|
77
|
model.layers.11.mlp.down_proj
| 0.056991
| 4,096
| 14,336
| 3.5
| 12.935681
| -27.08163
| 1.566674
| true
| 0.008062
|
dense
| -27.024306
| -0.530032
| -2.09356
| 64
| 0.2951
| 4,096
| 64
| 4,032
| 1
| 1.49196
| 0.008062
| 36.604042
|
success
| 0.089788
| 0.000001
|
under-trained
| 4,032
| 0.008062
| 0.004213
|
78
|
model.layers.11.mlp.gate_proj
| 0.050258
| 4,096
| 14,336
| 3.5
| 5.273043
| -10.023329
| 1.559382
| true
| 0.012564
|
dense
| -9.778413
| -0.518389
| -1.900863
| 64
| 0.303117
| 4,096
| 24
| 4,032
| 1
| 0.872231
| 0.012564
| 24.125341
|
success
| 0.11209
| 0.000001
| 4,032
| 0.012564
| 0.004489
|
|
79
|
model.layers.11.mlp.up_proj
| 0.044841
| 4,096
| 14,336
| 3.5
| 6.025806
| -11.473937
| 1.560522
| true
| 0.01247
|
dense
| -11.245172
| -0.493493
| -1.904133
| 64
| 0.321001
| 4,096
| 43
| 4,032
| 1
| 0.766428
| 0.01247
| 25.741854
|
success
| 0.111669
| 0.000001
|
under-trained
| 4,032
| 0.01247
| 0.004309
|
80
|
model.layers.11.self_attn.k_proj
| 0.060456
| 1,024
| 4,096
| 4
| 6.757037
| -17.235079
| 1.134413
| true
| 0.002814
|
dense
| -16.415399
| -0.930107
| -2.550686
| 64
| 0.117461
| 1,024
| 53
| 960
| 1
| 0.79079
| 0.002814
| 41.742561
|
success
| 0.053047
| 0.000001
|
under-trained
| 960
| 0.002814
| 0.001579
|
81
|
model.layers.11.self_attn.o_proj
| 0.032158
| 4,096
| 4,096
| 1
| 11.158902
| -26.44295
| 1.567071
| true
| 0.004269
|
dense
| -26.008332
| -0.724837
| -2.369673
| 64
| 0.188435
| 4,096
| 41
| 4,032
| 1
| 1.586554
| 0.004269
| 44.140343
|
success
| 0.065338
| 0
|
under-trained
| 4,032
| 0.004269
| 0.002785
|
82
|
model.layers.11.self_attn.q_proj
| 0.045011
| 4,096
| 4,096
| 1
| 9.484317
| -22.596014
| 1.565531
| true
| 0.004145
|
dense
| -22.532848
| -0.872075
| -2.382461
| 64
| 0.134253
| 4,096
| 24
| 4,032
| 1
| 1.731854
| 0.004145
| 32.388157
|
success
| 0.064383
| 0
|
under-trained
| 4,032
| 0.004145
| 0.002107
|
83
|
model.layers.11.self_attn.v_proj
| 0.101216
| 1,024
| 4,096
| 4
| 15.683077
| -41.547668
| 1.136782
| true
| 0.002243
|
dense
| -40.842064
| -0.936095
| -2.649204
| 64
| 0.115852
| 1,024
| 26
| 960
| 1
| 2.879588
| 0.002243
| 51.654556
|
success
| 0.047359
| 0.000001
|
under-trained
| 960
| 0.002243
| 0.001827
|
84
|
model.layers.12.mlp.down_proj
| 0.032652
| 4,096
| 14,336
| 3.5
| 14.15541
| -30.704631
| 1.567403
| true
| 0.006775
|
dense
| -30.458001
| -0.529252
| -2.169109
| 64
| 0.295629
| 4,096
| 64
| 4,032
| 1
| 1.644426
| 0.006775
| 43.637211
|
success
| 0.082309
| 0.000001
|
under-trained
| 4,032
| 0.006775
| 0.004265
|
85
|
model.layers.12.mlp.gate_proj
| 0.03655
| 4,096
| 14,336
| 3.5
| 5.6251
| -10.731252
| 1.560177
| true
| 0.012367
|
dense
| -10.539884
| -0.521513
| -1.907744
| 64
| 0.300945
| 4,096
| 33
| 4,032
| 1
| 0.805127
| 0.012367
| 24.334984
|
success
| 0.111206
| 0.000001
| 4,032
| 0.012367
| 0.004206
|
|
86
|
model.layers.12.mlp.up_proj
| 0.043853
| 4,096
| 14,336
| 3.5
| 5.902476
| -11.456355
| 1.562021
| true
| 0.011457
|
dense
| -11.172447
| -0.496813
| -1.94094
| 64
| 0.318557
| 4,096
| 29
| 4,032
| 1
| 0.910367
| 0.011457
| 27.805277
|
success
| 0.107036
| 0.000001
| 4,032
| 0.011457
| 0.004585
|
|
87
|
model.layers.12.self_attn.k_proj
| 0.090697
| 1,024
| 4,096
| 4
| 5.803976
| -14.697743
| 1.134736
| true
| 0.002935
|
dense
| -13.539768
| -0.862901
| -2.532357
| 64
| 0.13712
| 1,024
| 64
| 960
| 1
| 0.600497
| 0.002935
| 46.715065
|
success
| 0.054178
| 0.000001
| 960
| 0.002935
| 0.00172
|
|
88
|
model.layers.12.self_attn.o_proj
| 0.072164
| 4,096
| 4,096
| 1
| 12.682624
| -30.576485
| 1.567453
| true
| 0.003882
|
dense
| -29.915394
| -0.720165
| -2.410896
| 64
| 0.190474
| 4,096
| 37
| 4,032
| 1
| 1.920612
| 0.003882
| 49.060402
|
success
| 0.062309
| 0
|
under-trained
| 4,032
| 0.003882
| 0.002876
|
89
|
model.layers.12.self_attn.q_proj
| 0.055156
| 4,096
| 4,096
| 1
| 10.762409
| -25.686382
| 1.566173
| true
| 0.004105
|
dense
| -25.603435
| -0.833243
| -2.386676
| 64
| 0.146811
| 4,096
| 19
| 4,032
| 1
| 2.23965
| 0.004105
| 35.762928
|
success
| 0.064071
| 0
|
under-trained
| 4,032
| 0.004105
| 0.00238
|
90
|
model.layers.12.self_attn.v_proj
| 0.11485
| 1,024
| 4,096
| 4
| 11.876877
| -31.77564
| 1.13691
| true
| 0.002111
|
dense
| -30.658707
| -0.940515
| -2.675421
| 64
| 0.114679
| 1,024
| 52
| 960
| 1
| 1.508351
| 0.002111
| 54.313255
|
success
| 0.04595
| 0.000001
|
under-trained
| 960
| 0.002111
| 0.001665
|
91
|
model.layers.13.mlp.down_proj
| 0.036343
| 4,096
| 14,336
| 3.5
| 12.125812
| -25.628331
| 1.566873
| true
| 0.0077
|
dense
| -25.49984
| -0.521349
| -2.113535
| 64
| 0.301058
| 4,096
| 64
| 4,032
| 1
| 1.390727
| 0.0077
| 39.100815
|
success
| 0.087747
| 0.000001
|
under-trained
| 4,032
| 0.0077
| 0.004275
|
92
|
model.layers.13.mlp.gate_proj
| 0.032849
| 4,096
| 14,336
| 3.5
| 5.366135
| -10.105797
| 1.559179
| true
| 0.013084
|
dense
| -9.888976
| -0.506566
| -1.883254
| 64
| 0.311483
| 4,096
| 36
| 4,032
| 1
| 0.727689
| 0.013084
| 23.80612
|
success
| 0.114386
| 0.000001
| 4,032
| 0.013084
| 0.004238
|
|
93
|
model.layers.13.mlp.up_proj
| 0.037365
| 4,096
| 14,336
| 3.5
| 5.362235
| -10.155244
| 1.560663
| true
| 0.012769
|
dense
| -9.899726
| -0.488475
| -1.893845
| 64
| 0.324732
| 4,096
| 26
| 4,032
| 1
| 0.855505
| 0.012769
| 25.431419
|
success
| 0.113
| 0.000001
| 4,032
| 0.012769
| 0.00471
|
|
94
|
model.layers.13.self_attn.k_proj
| 0.055607
| 1,024
| 4,096
| 4
| 7.153452
| -18.283749
| 1.133874
| true
| 0.00278
|
dense
| -17.556995
| -0.957891
| -2.555934
| 64
| 0.110182
| 1,024
| 59
| 960
| 1
| 0.801111
| 0.00278
| 39.631744
|
success
| 0.052727
| 0.000001
|
under-trained
| 960
| 0.00278
| 0.001462
|
95
|
model.layers.13.self_attn.o_proj
| 0.040657
| 4,096
| 4,096
| 1
| 10.363712
| -23.618383
| 1.566533
| true
| 0.005261
|
dense
| -23.320876
| -0.681243
| -2.27895
| 64
| 0.208332
| 4,096
| 46
| 4,032
| 1
| 1.380604
| 0.005261
| 39.601051
|
success
| 0.072531
| 0
|
under-trained
| 4,032
| 0.005261
| 0.003017
|
96
|
model.layers.13.self_attn.q_proj
| 0.046576
| 4,096
| 4,096
| 1
| 9.668471
| -22.784899
| 1.565295
| true
| 0.004399
|
dense
| -22.73273
| -0.851471
| -2.356619
| 64
| 0.140776
| 4,096
| 20
| 4,032
| 1
| 1.938329
| 0.004399
| 31.999794
|
success
| 0.066327
| 0
|
under-trained
| 4,032
| 0.004399
| 0.002285
|
97
|
model.layers.13.self_attn.v_proj
| 0.069671
| 1,024
| 4,096
| 4
| 20.504022
| -53.933001
| 1.136864
| true
| 0.002342
|
dense
| -53.52314
| -0.922778
| -2.630362
| 64
| 0.11946
| 1,024
| 19
| 960
| 1
| 4.47453
| 0.002342
| 51.001656
|
success
| 0.048397
| 0.000001
|
under-trained
| 960
| 0.002342
| 0.001942
|
98
|
model.layers.14.mlp.down_proj
| 0.032288
| 4,096
| 14,336
| 3.5
| 10.464349
| -21.796519
| 1.566664
| true
| 0.008262
|
dense
| -21.630572
| -0.50299
| -2.082931
| 64
| 0.314058
| 4,096
| 34
| 4,032
| 1
| 1.623122
| 0.008262
| 38.013767
|
success
| 0.090894
| 0.000001
|
under-trained
| 4,032
| 0.008262
| 0.004672
|
99
|
model.layers.14.mlp.gate_proj
| 0.039619
| 4,096
| 14,336
| 3.5
| 5.266263
| -9.813683
| 1.55907
| true
| 0.013693
|
dense
| -9.606431
| -0.497325
| -1.8635
| 64
| 0.318182
| 4,096
| 31
| 4,032
| 1
| 0.766243
| 0.013693
| 23.236776
|
success
| 0.117017
| 0.000001
| 4,032
| 0.013693
| 0.004443
|
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