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
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
100
|
model.layers.14.mlp.up_proj
| 0.04407
| 4,096
| 14,336
| 3.5
| 5.35609
| -9.927089
| 1.560365
| true
| 0.014015
|
dense
| -9.748356
| -0.481377
| -1.853421
| 64
| 0.330083
| 4,096
| 24
| 4,032
| 1
| 0.889183
| 0.014015
| 23.552853
|
success
| 0.118383
| 0.000001
| 4,032
| 0.014015
| 0.004832
|
|
101
|
model.layers.14.self_attn.k_proj
| 0.050633
| 1,024
| 4,096
| 4
| 7.090553
| -17.852702
| 1.13429
| true
| 0.003035
|
dense
| -17.129008
| -0.910717
| -2.517815
| 64
| 0.122824
| 1,024
| 51
| 960
| 1
| 0.852848
| 0.003035
| 40.466755
|
success
| 0.055092
| 0.000001
|
under-trained
| 960
| 0.003035
| 0.001672
|
102
|
model.layers.14.self_attn.o_proj
| 0.027317
| 4,096
| 4,096
| 1
| 10.210347
| -23.017842
| 1.566375
| true
| 0.005567
|
dense
| -22.823744
| -0.681389
| -2.254364
| 64
| 0.208262
| 4,096
| 56
| 4,032
| 1
| 1.230784
| 0.005567
| 37.408894
|
success
| 0.074614
| 0
|
under-trained
| 4,032
| 0.005567
| 0.002941
|
103
|
model.layers.14.self_attn.q_proj
| 0.049554
| 4,096
| 4,096
| 1
| 8.232165
| -19.06172
| 1.564752
| true
| 0.004836
|
dense
| -18.963099
| -0.828161
| -2.315517
| 64
| 0.148538
| 4,096
| 33
| 4,032
| 1
| 1.258958
| 0.004836
| 30.715399
|
success
| 0.069541
| 0
|
under-trained
| 4,032
| 0.004836
| 0.002207
|
104
|
model.layers.14.self_attn.v_proj
| 0.079832
| 1,024
| 4,096
| 4
| 20.738459
| -53.412723
| 1.136854
| true
| 0.002657
|
dense
| -53.051262
| -0.87145
| -2.57554
| 64
| 0.134447
| 1,024
| 17
| 960
| 1
| 4.78728
| 0.002657
| 50.592876
|
success
| 0.05155
| 0.000001
|
under-trained
| 960
| 0.002657
| 0.002202
|
105
|
model.layers.15.mlp.down_proj
| 0.029379
| 4,096
| 14,336
| 3.5
| 14.231365
| -30.512898
| 1.567433
| true
| 0.007177
|
dense
| -30.400055
| -0.516115
| -2.14406
| 64
| 0.304709
| 4,096
| 64
| 4,032
| 1
| 1.653921
| 0.007177
| 42.456596
|
success
| 0.084717
| 0.000001
|
under-trained
| 4,032
| 0.007177
| 0.004398
|
106
|
model.layers.15.mlp.gate_proj
| 0.051791
| 4,096
| 14,336
| 3.5
| 5.879363
| -11.277452
| 1.560675
| true
| 0.012074
|
dense
| -11.035696
| -0.507647
| -1.918142
| 64
| 0.310708
| 4,096
| 35
| 4,032
| 1
| 0.824763
| 0.012074
| 25.733248
|
success
| 0.109883
| 0.000001
| 4,032
| 0.012074
| 0.004324
|
|
107
|
model.layers.15.mlp.up_proj
| 0.04936
| 4,096
| 14,336
| 3.5
| 6.388651
| -12.393745
| 1.562404
| true
| 0.011483
|
dense
| -12.144656
| -0.49289
| -1.939963
| 64
| 0.321448
| 4,096
| 30
| 4,032
| 1
| 0.983829
| 0.011483
| 27.99452
|
success
| 0.107157
| 0.000001
|
under-trained
| 4,032
| 0.011483
| 0.00465
|
108
|
model.layers.15.self_attn.k_proj
| 0.08746
| 1,024
| 4,096
| 4
| 12.41401
| -31.451232
| 1.13555
| true
| 0.002927
|
dense
| -30.806589
| -0.867215
| -2.533527
| 64
| 0.135764
| 1,024
| 19
| 960
| 1
| 2.618554
| 0.002927
| 46.378033
|
success
| 0.054105
| 0.000001
|
under-trained
| 960
| 0.002927
| 0.002266
|
109
|
model.layers.15.self_attn.o_proj
| 0.073486
| 4,096
| 4,096
| 1
| 22.78947
| -54.912991
| 1.567856
| true
| 0.003894
|
dense
| -54.643475
| -0.702228
| -2.409577
| 64
| 0.198505
| 4,096
| 14
| 4,032
| 1
| 5.823481
| 0.003894
| 50.974079
|
success
| 0.062404
| 0
|
under-trained
| 4,032
| 0.003894
| 0.003261
|
110
|
model.layers.15.self_attn.q_proj
| 0.038691
| 4,096
| 4,096
| 1
| 11.393952
| -27.145479
| 1.566538
| true
| 0.004145
|
dense
| -27.047657
| -0.808669
| -2.382446
| 64
| 0.155357
| 4,096
| 27
| 4,032
| 1
| 2.000317
| 0.004145
| 37.478085
|
success
| 0.064384
| 0
|
under-trained
| 4,032
| 0.004145
| 0.002417
|
111
|
model.layers.15.self_attn.v_proj
| 0.09666
| 1,024
| 4,096
| 4
| 19.74294
| -52.107331
| 1.137044
| true
| 0.002295
|
dense
| -51.163957
| -0.894979
| -2.639289
| 64
| 0.127356
| 1,024
| 26
| 960
| 1
| 3.675793
| 0.002295
| 55.502193
|
success
| 0.047902
| 0.000001
|
under-trained
| 960
| 0.002295
| 0.002011
|
112
|
model.layers.16.mlp.down_proj
| 0.03637
| 4,096
| 14,336
| 3.5
| 12.299618
| -25.960552
| 1.56721
| true
| 0.00775
|
dense
| -25.864351
| -0.513355
| -2.11068
| 64
| 0.306651
| 4,096
| 27
| 4,032
| 1
| 2.174612
| 0.00775
| 39.566231
|
success
| 0.088036
| 0.000001
|
under-trained
| 4,032
| 0.00775
| 0.004679
|
113
|
model.layers.16.mlp.gate_proj
| 0.04882
| 4,096
| 14,336
| 3.5
| 5.786708
| -11.038166
| 1.56046
| true
| 0.012374
|
dense
| -10.783695
| -0.500731
| -1.907503
| 64
| 0.315696
| 4,096
| 34
| 4,032
| 1
| 0.820914
| 0.012374
| 25.513638
|
success
| 0.111237
| 0.000001
| 4,032
| 0.012374
| 0.004401
|
|
114
|
model.layers.16.mlp.up_proj
| 0.050119
| 4,096
| 14,336
| 3.5
| 6.408145
| -12.304469
| 1.562002
| true
| 0.012019
|
dense
| -12.090176
| -0.489292
| -1.92013
| 64
| 0.324122
| 4,096
| 32
| 4,032
| 1
| 0.956034
| 0.012019
| 26.9673
|
success
| 0.109631
| 0.000001
|
under-trained
| 4,032
| 0.012019
| 0.004628
|
115
|
model.layers.16.self_attn.k_proj
| 0.052562
| 1,024
| 4,096
| 4
| 7.736304
| -19.403313
| 1.134752
| true
| 0.003104
|
dense
| -18.746053
| -0.895812
| -2.508086
| 64
| 0.127113
| 1,024
| 47
| 960
| 1
| 0.982591
| 0.003104
| 40.951885
|
success
| 0.055713
| 0.000001
|
under-trained
| 960
| 0.003104
| 0.001778
|
116
|
model.layers.16.self_attn.o_proj
| 0.044595
| 4,096
| 4,096
| 1
| 16.782293
| -39.838156
| 1.567677
| true
| 0.004228
|
dense
| -39.667576
| -0.707306
| -2.373821
| 64
| 0.196198
| 4,096
| 31
| 4,032
| 1
| 2.834584
| 0.004228
| 46.399624
|
success
| 0.065026
| 0
|
under-trained
| 4,032
| 0.004228
| 0.003038
|
117
|
model.layers.16.self_attn.q_proj
| 0.059982
| 4,096
| 4,096
| 1
| 9.882449
| -23.644621
| 1.566412
| true
| 0.00405
|
dense
| -23.432238
| -0.811707
| -2.392587
| 64
| 0.154274
| 4,096
| 35
| 4,032
| 1
| 1.501408
| 0.00405
| 38.096092
|
success
| 0.063637
| 0
|
under-trained
| 4,032
| 0.00405
| 0.002305
|
118
|
model.layers.16.self_attn.v_proj
| 0.110164
| 1,024
| 4,096
| 4
| 17.070893
| -45.159406
| 1.137101
| true
| 0.002263
|
dense
| -44.087106
| -0.895655
| -2.645404
| 64
| 0.127158
| 1,024
| 39
| 960
| 1
| 2.573402
| 0.002263
| 56.201641
|
success
| 0.047566
| 0.000001
|
under-trained
| 960
| 0.002263
| 0.001937
|
119
|
model.layers.17.mlp.down_proj
| 0.045365
| 4,096
| 14,336
| 3.5
| 12.22335
| -25.598136
| 1.566806
| true
| 0.00805
|
dense
| -25.536009
| -0.521363
| -2.0942
| 64
| 0.301049
| 4,096
| 64
| 4,032
| 1
| 1.402919
| 0.00805
| 37.39695
|
success
| 0.089722
| 0.000001
|
under-trained
| 4,032
| 0.00805
| 0.004277
|
120
|
model.layers.17.mlp.gate_proj
| 0.04479
| 4,096
| 14,336
| 3.5
| 6.020877
| -11.465776
| 1.561047
| true
| 0.012464
|
dense
| -11.293104
| -0.506241
| -1.904336
| 64
| 0.311716
| 4,096
| 31
| 4,032
| 1
| 0.901776
| 0.012464
| 25.008944
|
success
| 0.111643
| 0.000001
|
under-trained
| 4,032
| 0.012464
| 0.00445
|
121
|
model.layers.17.mlp.up_proj
| 0.055498
| 4,096
| 14,336
| 3.5
| 6.33513
| -12.266333
| 1.562622
| true
| 0.011581
|
dense
| -12.056853
| -0.498333
| -1.93624
| 64
| 0.317444
| 4,096
| 25
| 4,032
| 1
| 1.067026
| 0.011581
| 27.40988
|
success
| 0.107617
| 0.000001
|
under-trained
| 4,032
| 0.011581
| 0.004714
|
122
|
model.layers.17.self_attn.k_proj
| 0.050712
| 1,024
| 4,096
| 4
| 7.179098
| -18.214098
| 1.134169
| true
| 0.002903
|
dense
| -17.593216
| -0.947164
| -2.537101
| 64
| 0.112937
| 1,024
| 48
| 960
| 1
| 0.891876
| 0.002903
| 38.898895
|
success
| 0.053883
| 0.000001
|
under-trained
| 960
| 0.002903
| 0.001556
|
123
|
model.layers.17.self_attn.o_proj
| 0.054669
| 4,096
| 4,096
| 1
| 17.646075
| -43.286266
| 1.567636
| true
| 0.003524
|
dense
| -42.894703
| -0.759549
| -2.453025
| 64
| 0.173961
| 4,096
| 19
| 4,032
| 1
| 3.818872
| 0.003524
| 49.371487
|
success
| 0.059359
| 0
|
under-trained
| 4,032
| 0.003524
| 0.002814
|
124
|
model.layers.17.self_attn.q_proj
| 0.035606
| 4,096
| 4,096
| 1
| 8.667275
| -20.609269
| 1.565403
| true
| 0.00419
|
dense
| -20.455829
| -0.848533
| -2.377826
| 64
| 0.141732
| 4,096
| 32
| 4,032
| 1
| 1.355396
| 0.00419
| 33.82925
|
success
| 0.064727
| 0
|
under-trained
| 4,032
| 0.00419
| 0.00213
|
125
|
model.layers.17.self_attn.v_proj
| 0.103416
| 1,024
| 4,096
| 4
| 22.441121
| -59.716689
| 1.136952
| true
| 0.002183
|
dense
| -59.160964
| -0.936391
| -2.661039
| 64
| 0.115773
| 1,024
| 18
| 960
| 1
| 5.053721
| 0.002183
| 53.045414
|
success
| 0.046718
| 0.000001
|
under-trained
| 960
| 0.002183
| 0.001888
|
126
|
model.layers.18.mlp.down_proj
| 0.047888
| 4,096
| 14,336
| 3.5
| 13.341258
| -28.149363
| 1.566923
| true
| 0.007763
|
dense
| -28.090671
| -0.529976
| -2.109948
| 64
| 0.295137
| 4,096
| 64
| 4,032
| 1
| 1.542657
| 0.007763
| 38.016453
|
success
| 0.08811
| 0.000001
|
under-trained
| 4,032
| 0.007763
| 0.004229
|
127
|
model.layers.18.mlp.gate_proj
| 0.047416
| 4,096
| 14,336
| 3.5
| 5.802708
| -11.059557
| 1.559926
| true
| 0.012419
|
dense
| -10.841252
| -0.517615
| -1.905931
| 64
| 0.303658
| 4,096
| 34
| 4,032
| 1
| 0.823658
| 0.012419
| 24.45204
|
success
| 0.111438
| 0.000001
| 4,032
| 0.012419
| 0.00423
|
|
128
|
model.layers.18.mlp.up_proj
| 0.05985
| 4,096
| 14,336
| 3.5
| 6.70596
| -12.740621
| 1.56102
| true
| 0.012592
|
dense
| -12.626483
| -0.511941
| -1.899895
| 64
| 0.307652
| 4,096
| 47
| 4,032
| 1
| 0.8323
| 0.012592
| 24.431744
|
success
| 0.112215
| 0.000001
|
under-trained
| 4,032
| 0.012592
| 0.004142
|
129
|
model.layers.18.self_attn.k_proj
| 0.108372
| 1,024
| 4,096
| 4
| 6.960606
| -17.857317
| 1.135391
| true
| 0.00272
|
dense
| -16.791156
| -0.89
| -2.565483
| 64
| 0.128825
| 1,024
| 54
| 960
| 1
| 0.811136
| 0.00272
| 47.367775
|
success
| 0.05215
| 0.000001
|
under-trained
| 960
| 0.00272
| 0.00174
|
130
|
model.layers.18.self_attn.o_proj
| 0.088649
| 4,096
| 4,096
| 1
| 8.089083
| -17.517363
| 1.561164
| true
| 0.00683
|
dense
| -17.390266
| -0.768608
| -2.165556
| 64
| 0.17037
| 4,096
| 64
| 4,032
| 1
| 0.886135
| 0.00683
| 24.942989
|
success
| 0.082646
| 0
|
under-trained
| 4,032
| 0.00683
| 0.002256
|
131
|
model.layers.18.self_attn.q_proj
| 0.046052
| 4,096
| 4,096
| 1
| 8.924982
| -21.457456
| 1.566115
| true
| 0.003943
|
dense
| -21.25436
| -0.8447
| -2.404202
| 64
| 0.142988
| 4,096
| 44
| 4,032
| 1
| 1.194736
| 0.003943
| 36.26619
|
success
| 0.062791
| 0
|
under-trained
| 4,032
| 0.003943
| 0.002054
|
132
|
model.layers.18.self_attn.v_proj
| 0.050976
| 1,024
| 4,096
| 4
| 14.76355
| -38.182098
| 1.136514
| true
| 0.002593
|
dense
| -37.95285
| -0.933353
| -2.586241
| 64
| 0.116586
| 1,024
| 18
| 960
| 1
| 3.2441
| 0.002593
| 44.966438
|
success
| 0.050919
| 0.000001
|
under-trained
| 960
| 0.002593
| 0.001889
|
133
|
model.layers.19.mlp.down_proj
| 0.052127
| 4,096
| 14,336
| 3.5
| 15.739191
| -33.756519
| 1.567286
| true
| 0.007166
|
dense
| -33.731273
| -0.550695
| -2.144743
| 64
| 0.281388
| 4,096
| 64
| 4,032
| 1
| 1.842399
| 0.007166
| 39.268841
|
success
| 0.08465
| 0.000001
|
under-trained
| 4,032
| 0.007166
| 0.004091
|
134
|
model.layers.19.mlp.gate_proj
| 0.046502
| 4,096
| 14,336
| 3.5
| 5.941198
| -11.533365
| 1.560244
| true
| 0.011448
|
dense
| -11.287487
| -0.541057
| -1.941252
| 64
| 0.287702
| 4,096
| 37
| 4,032
| 1
| 0.812328
| 0.011448
| 25.130192
|
success
| 0.106998
| 0.000001
| 4,032
| 0.011448
| 0.003959
|
|
135
|
model.layers.19.mlp.up_proj
| 0.058156
| 4,096
| 14,336
| 3.5
| 6.254391
| -12.406597
| 1.561834
| true
| 0.010383
|
dense
| -12.083018
| -0.539091
| -1.983662
| 64
| 0.289008
| 4,096
| 29
| 4,032
| 1
| 0.975716
| 0.010383
| 27.8337
|
success
| 0.101899
| 0.000001
|
under-trained
| 4,032
| 0.010383
| 0.004184
|
136
|
model.layers.19.self_attn.k_proj
| 0.052233
| 1,024
| 4,096
| 4
| 7.138026
| -18.337259
| 1.134431
| true
| 0.002698
|
dense
| -17.599834
| -0.95689
| -2.568954
| 64
| 0.110436
| 1,024
| 50
| 960
| 1
| 0.868048
| 0.002698
| 40.932098
|
success
| 0.051943
| 0.000001
|
under-trained
| 960
| 0.002698
| 0.001515
|
137
|
model.layers.19.self_attn.o_proj
| 0.075721
| 4,096
| 4,096
| 1
| 18.962458
| -47.43336
| 1.567721
| true
| 0.003152
|
dense
| -47.108238
| -0.806771
| -2.501435
| 64
| 0.156037
| 4,096
| 16
| 4,032
| 1
| 4.490614
| 0.003152
| 49.506718
|
success
| 0.056141
| 0
|
under-trained
| 4,032
| 0.003152
| 0.002545
|
138
|
model.layers.19.self_attn.q_proj
| 0.049252
| 4,096
| 4,096
| 1
| 11.574794
| -28.732051
| 1.566537
| true
| 0.003294
|
dense
| -28.514098
| -0.873983
| -2.482295
| 64
| 0.133665
| 4,096
| 22
| 4,032
| 1
| 2.254554
| 0.003294
| 40.579983
|
success
| 0.057392
| 0
|
under-trained
| 4,032
| 0.003294
| 0.002148
|
139
|
model.layers.19.self_attn.v_proj
| 0.112999
| 1,024
| 4,096
| 4
| 11.720165
| -31.715583
| 1.137021
| true
| 0.001968
|
dense
| -30.618044
| -0.971436
| -2.70607
| 64
| 0.106798
| 1,024
| 63
| 960
| 1
| 1.350614
| 0.001968
| 54.279236
|
success
| 0.044357
| 0.000001
|
under-trained
| 960
| 0.001968
| 0.001519
|
140
|
model.layers.20.mlp.down_proj
| 0.061206
| 4,096
| 14,336
| 3.5
| 18.627453
| -40.568402
| 1.567502
| true
| 0.006639
|
dense
| -40.560511
| -0.577345
| -2.177882
| 64
| 0.26464
| 4,096
| 63
| 4,032
| 1
| 2.22085
| 0.006639
| 39.860016
|
success
| 0.081481
| 0.000001
|
under-trained
| 4,032
| 0.006639
| 0.003898
|
141
|
model.layers.20.mlp.gate_proj
| 0.051517
| 4,096
| 14,336
| 3.5
| 6.108503
| -12.000854
| 1.560681
| true
| 0.010849
|
dense
| -11.798363
| -0.563479
| -1.964615
| 64
| 0.273225
| 4,096
| 39
| 4,032
| 1
| 0.818015
| 0.010849
| 25.184643
|
success
| 0.104158
| 0.000001
|
under-trained
| 4,032
| 0.010849
| 0.003738
|
142
|
model.layers.20.mlp.up_proj
| 0.058065
| 4,096
| 14,336
| 3.5
| 6.712795
| -13.641759
| 1.562814
| true
| 0.009285
|
dense
| -13.338223
| -0.568168
| -2.032203
| 64
| 0.270291
| 4,096
| 30
| 4,032
| 1
| 1.043009
| 0.009285
| 29.109493
|
success
| 0.09636
| 0.000001
|
under-trained
| 4,032
| 0.009285
| 0.003918
|
143
|
model.layers.20.self_attn.k_proj
| 0.041516
| 1,024
| 4,096
| 4
| 7.861621
| -20.866377
| 1.134635
| true
| 0.002217
|
dense
| -20.097021
| -1.026386
| -2.654208
| 64
| 0.094105
| 1,024
| 37
| 960
| 1
| 1.128044
| 0.002217
| 42.444511
|
success
| 0.047086
| 0.000001
|
under-trained
| 960
| 0.002217
| 0.001376
|
144
|
model.layers.20.self_attn.o_proj
| 0.052326
| 4,096
| 4,096
| 1
| 15.763416
| -40.379479
| 1.567751
| true
| 0.002744
|
dense
| -40.009999
| -0.874711
| -2.561594
| 64
| 0.133441
| 4,096
| 37
| 4,032
| 1
| 2.427091
| 0.002744
| 48.627666
|
success
| 0.052384
| 0
|
under-trained
| 4,032
| 0.002744
| 0.002028
|
145
|
model.layers.20.self_attn.q_proj
| 0.044572
| 4,096
| 4,096
| 1
| 8.874127
| -21.844081
| 1.565419
| true
| 0.003455
|
dense
| -21.730231
| -0.940223
| -2.461547
| 64
| 0.114756
| 4,096
| 25
| 4,032
| 1
| 1.574825
| 0.003455
| 33.214188
|
success
| 0.05878
| 0
|
under-trained
| 4,032
| 0.003455
| 0.001787
|
146
|
model.layers.20.self_attn.v_proj
| 0.101759
| 1,024
| 4,096
| 4
| 23.903313
| -65.707531
| 1.137016
| true
| 0.001783
|
dense
| -64.963068
| -1.009508
| -2.748888
| 64
| 0.097834
| 1,024
| 21
| 960
| 1
| 4.997913
| 0.001783
| 54.875648
|
success
| 0.042224
| 0.000001
|
under-trained
| 960
| 0.001783
| 0.00158
|
147
|
model.layers.21.mlp.down_proj
| 0.067235
| 4,096
| 14,336
| 3.5
| 20.880401
| -46.272757
| 1.56767
| true
| 0.00608
|
dense
| -46.269135
| -0.604594
| -2.216086
| 64
| 0.248545
| 4,096
| 63
| 4,032
| 1
| 2.504695
| 0.00608
| 40.878166
|
success
| 0.077975
| 0.000001
|
under-trained
| 4,032
| 0.00608
| 0.003686
|
148
|
model.layers.21.mlp.gate_proj
| 0.047487
| 4,096
| 14,336
| 3.5
| 6.654224
| -13.189706
| 1.561156
| true
| 0.010419
|
dense
| -13.053557
| -0.584819
| -1.982155
| 64
| 0.260124
| 4,096
| 47
| 4,032
| 1
| 0.824753
| 0.010419
| 24.965286
|
success
| 0.102076
| 0.000001
|
under-trained
| 4,032
| 0.010419
| 0.003499
|
149
|
model.layers.21.mlp.up_proj
| 0.058968
| 4,096
| 14,336
| 3.5
| 6.700749
| -13.659004
| 1.562909
| true
| 0.009153
|
dense
| -13.446833
| -0.590596
| -2.038429
| 64
| 0.256687
| 4,096
| 28
| 4,032
| 1
| 1.07734
| 0.009153
| 28.043589
|
success
| 0.095672
| 0.000001
|
under-trained
| 4,032
| 0.009153
| 0.003754
|
150
|
model.layers.21.self_attn.k_proj
| 0.049508
| 1,024
| 4,096
| 4
| 6.538743
| -17.295736
| 1.133256
| true
| 0.002264
|
dense
| -16.618364
| -1.068307
| -2.645116
| 64
| 0.085446
| 1,024
| 46
| 960
| 1
| 0.816643
| 0.002264
| 37.740685
|
success
| 0.047582
| 0.000001
|
under-trained
| 960
| 0.002264
| 0.001169
|
151
|
model.layers.21.self_attn.o_proj
| 0.065618
| 4,096
| 4,096
| 1
| 16.770174
| -44.283508
| 1.567853
| true
| 0.002288
|
dense
| -43.920455
| -0.94789
| -2.640611
| 64
| 0.112748
| 4,096
| 38
| 4,032
| 1
| 2.55826
| 0.002288
| 49.285667
|
success
| 0.047829
| 0
|
under-trained
| 4,032
| 0.002288
| 0.001711
|
152
|
model.layers.21.self_attn.q_proj
| 0.049632
| 4,096
| 4,096
| 1
| 9.066903
| -22.476881
| 1.564873
| true
| 0.003319
|
dense
| -22.418352
| -0.988838
| -2.479003
| 64
| 0.102603
| 4,096
| 19
| 4,032
| 1
| 1.850674
| 0.003319
| 30.914713
|
success
| 0.05761
| 0
|
under-trained
| 4,032
| 0.003319
| 0.001678
|
153
|
model.layers.21.self_attn.v_proj
| 0.102323
| 1,024
| 4,096
| 4
| 12.668749
| -35.473683
| 1.136968
| true
| 0.001585
|
dense
| -34.520934
| -1.075054
| -2.800094
| 64
| 0.084129
| 1,024
| 54
| 960
| 1
| 1.587916
| 0.001585
| 53.093327
|
success
| 0.039806
| 0.000001
|
under-trained
| 960
| 0.001585
| 0.001223
|
154
|
model.layers.22.mlp.down_proj
| 0.065357
| 4,096
| 14,336
| 3.5
| 21.333619
| -47.843349
| 1.567693
| true
| 0.00572
|
dense
| -47.83868
| -0.625556
| -2.242627
| 64
| 0.236834
| 4,096
| 63
| 4,032
| 1
| 2.561795
| 0.00572
| 41.406754
|
success
| 0.075629
| 0.000001
|
under-trained
| 4,032
| 0.00572
| 0.003517
|
155
|
model.layers.22.mlp.gate_proj
| 0.052411
| 4,096
| 14,336
| 3.5
| 6.327244
| -12.577383
| 1.561112
| true
| 0.010285
|
dense
| -12.401841
| -0.586662
| -1.987814
| 64
| 0.259023
| 4,096
| 35
| 4,032
| 1
| 0.900469
| 0.010285
| 25.185551
|
success
| 0.101413
| 0.000001
|
under-trained
| 4,032
| 0.010285
| 0.003633
|
156
|
model.layers.22.mlp.up_proj
| 0.055813
| 4,096
| 14,336
| 3.5
| 6.512486
| -13.175072
| 1.56233
| true
| 0.009483
|
dense
| -12.987822
| -0.595345
| -2.023048
| 64
| 0.253895
| 4,096
| 29
| 4,032
| 1
| 1.023643
| 0.009483
| 26.773323
|
success
| 0.097381
| 0.000001
|
under-trained
| 4,032
| 0.009483
| 0.003677
|
157
|
model.layers.22.self_attn.k_proj
| 0.049827
| 1,024
| 4,096
| 4
| 6.607918
| -17.565098
| 1.132208
| true
| 0.002197
|
dense
| -16.957388
| -1.10369
| -2.65819
| 64
| 0.078761
| 1,024
| 29
| 960
| 1
| 1.041364
| 0.002197
| 35.850883
|
success
| 0.046871
| 0.000001
|
under-trained
| 960
| 0.002197
| 0.001194
|
158
|
model.layers.22.self_attn.o_proj
| 0.041494
| 4,096
| 4,096
| 1
| 13.129645
| -34.940046
| 1.567293
| true
| 0.002182
|
dense
| -34.489469
| -1.004539
| -2.661157
| 64
| 0.09896
| 4,096
| 55
| 4,032
| 1
| 1.635561
| 0.002182
| 45.354275
|
success
| 0.046711
| 0
|
under-trained
| 4,032
| 0.002182
| 0.001436
|
159
|
model.layers.22.self_attn.q_proj
| 0.04183
| 4,096
| 4,096
| 1
| 7.694742
| -19.28764
| 1.564005
| true
| 0.003115
|
dense
| -19.193126
| -1.041616
| -2.5066
| 64
| 0.090862
| 4,096
| 27
| 4,032
| 1
| 1.288404
| 0.003115
| 29.173191
|
success
| 0.055808
| 0
|
under-trained
| 4,032
| 0.003115
| 0.001394
|
160
|
model.layers.22.self_attn.v_proj
| 0.079668
| 1,024
| 4,096
| 4
| 19.708094
| -55.116658
| 1.136799
| true
| 0.001597
|
dense
| -54.796141
| -1.100267
| -2.796651
| 64
| 0.079384
| 1,024
| 15
| 960
| 1
| 4.830409
| 0.001597
| 49.703156
|
success
| 0.039965
| 0.000001
|
under-trained
| 960
| 0.001597
| 0.001312
|
161
|
model.layers.23.mlp.down_proj
| 0.067607
| 4,096
| 14,336
| 3.5
| 21.848974
| -49.418214
| 1.567716
| true
| 0.005473
|
dense
| -49.41545
| -0.647612
| -2.261809
| 64
| 0.225106
| 4,096
| 64
| 4,032
| 1
| 2.606122
| 0.005473
| 41.133663
|
success
| 0.073977
| 0.000001
|
under-trained
| 4,032
| 0.005473
| 0.003344
|
162
|
model.layers.23.mlp.gate_proj
| 0.056297
| 4,096
| 14,336
| 3.5
| 6.059427
| -11.977099
| 1.560636
| true
| 0.010553
|
dense
| -11.811683
| -0.592699
| -1.976606
| 64
| 0.255447
| 4,096
| 28
| 4,032
| 1
| 0.956142
| 0.010553
| 24.205093
|
success
| 0.10273
| 0.000001
|
under-trained
| 4,032
| 0.010553
| 0.003698
|
163
|
model.layers.23.mlp.up_proj
| 0.063931
| 4,096
| 14,336
| 3.5
| 6.466909
| -13.111112
| 1.561809
| true
| 0.009388
|
dense
| -12.900208
| -0.607263
| -2.027416
| 64
| 0.247023
| 4,096
| 29
| 4,032
| 1
| 1.015179
| 0.009388
| 26.311918
|
success
| 0.096893
| 0.000001
|
under-trained
| 4,032
| 0.009388
| 0.003575
|
164
|
model.layers.23.self_attn.k_proj
| 0.047964
| 1,024
| 4,096
| 4
| 5.956014
| -16.085416
| 1.131418
| true
| 0.001992
|
dense
| -15.357696
| -1.148579
| -2.700702
| 64
| 0.071027
| 1,024
| 64
| 960
| 1
| 0.619502
| 0.001992
| 35.65517
|
success
| 0.044632
| 0.000001
| 960
| 0.001992
| 0.000886
|
|
165
|
model.layers.23.self_attn.o_proj
| 0.057257
| 4,096
| 4,096
| 1
| 9.506238
| -23.880512
| 1.565192
| true
| 0.003075
|
dense
| -23.710591
| -0.986447
| -2.512089
| 64
| 0.10317
| 4,096
| 64
| 4,032
| 1
| 1.06328
| 0.003075
| 33.546062
|
success
| 0.055457
| 0
|
under-trained
| 4,032
| 0.003075
| 0.001416
|
166
|
model.layers.23.self_attn.q_proj
| 0.043697
| 4,096
| 4,096
| 1
| 6.710396
| -17.197635
| 1.564053
| true
| 0.002736
|
dense
| -16.960834
| -1.072318
| -2.562835
| 64
| 0.084661
| 4,096
| 45
| 4,032
| 1
| 0.851256
| 0.002736
| 30.93972
|
success
| 0.05231
| 0
|
under-trained
| 4,032
| 0.002736
| 0.001165
|
167
|
model.layers.23.self_attn.v_proj
| 0.07277
| 1,024
| 4,096
| 4
| 12.088783
| -33.232434
| 1.136598
| true
| 0.001782
|
dense
| -32.706667
| -1.075935
| -2.749031
| 64
| 0.083959
| 1,024
| 44
| 960
| 1
| 1.671697
| 0.001782
| 47.108139
|
success
| 0.042217
| 0.000001
|
under-trained
| 960
| 0.001782
| 0.001241
|
168
|
model.layers.24.mlp.down_proj
| 0.065622
| 4,096
| 14,336
| 3.5
| 21.169251
| -48.697705
| 1.567789
| true
| 0.005007
|
dense
| -48.690095
| -0.671119
| -2.300398
| 64
| 0.213246
| 4,096
| 64
| 4,032
| 1
| 2.521156
| 0.005007
| 42.587193
|
success
| 0.070762
| 0.000001
|
under-trained
| 4,032
| 0.005007
| 0.003164
|
169
|
model.layers.24.mlp.gate_proj
| 0.06806
| 4,096
| 14,336
| 3.5
| 6.658305
| -13.271129
| 1.560756
| true
| 0.010159
|
dense
| -13.148111
| -0.613375
| -1.993169
| 64
| 0.243571
| 4,096
| 39
| 4,032
| 1
| 0.906054
| 0.010159
| 23.976974
|
success
| 0.10079
| 0.000001
|
under-trained
| 4,032
| 0.010159
| 0.00337
|
170
|
model.layers.24.mlp.up_proj
| 0.078056
| 4,096
| 14,336
| 3.5
| 6.230828
| -12.752574
| 1.562227
| true
| 0.008981
|
dense
| -12.565062
| -0.631209
| -2.04669
| 64
| 0.233771
| 4,096
| 22
| 4,032
| 1
| 1.115216
| 0.008981
| 26.030411
|
success
| 0.094767
| 0.000001
|
under-trained
| 4,032
| 0.008981
| 0.003496
|
171
|
model.layers.24.self_attn.k_proj
| 0.037613
| 1,024
| 4,096
| 4
| 5.32169
| -14.107453
| 1.13031
| true
| 0.002234
|
dense
| -13.541941
| -1.153247
| -2.650934
| 64
| 0.070267
| 1,024
| 52
| 960
| 1
| 0.599311
| 0.002234
| 31.454811
|
success
| 0.047264
| 0.000001
| 960
| 0.002234
| 0.000892
|
|
172
|
model.layers.24.self_attn.o_proj
| 0.044291
| 4,096
| 4,096
| 1
| 13.472331
| -36.547637
| 1.56741
| true
| 0.001937
|
dense
| -36.173019
| -1.054174
| -2.712792
| 64
| 0.088273
| 4,096
| 58
| 4,032
| 1
| 1.637697
| 0.001937
| 45.563667
|
success
| 0.044015
| 0
|
under-trained
| 4,032
| 0.001937
| 0.001278
|
173
|
model.layers.24.self_attn.q_proj
| 0.039975
| 4,096
| 4,096
| 1
| 7.641116
| -19.853336
| 1.564035
| true
| 0.002522
|
dense
| -19.672138
| -1.105511
| -2.598225
| 64
| 0.078431
| 4,096
| 30
| 4,032
| 1
| 1.212496
| 0.002522
| 31.096643
|
success
| 0.050221
| 0
|
under-trained
| 4,032
| 0.002522
| 0.001185
|
174
|
model.layers.24.self_attn.v_proj
| 0.087479
| 1,024
| 4,096
| 4
| 22.192286
| -62.33312
| 1.136846
| true
| 0.001553
|
dense
| -61.984562
| -1.103115
| -2.808774
| 64
| 0.078865
| 1,024
| 13
| 960
| 1
| 5.877683
| 0.001553
| 50.776108
|
success
| 0.039411
| 0.000001
|
under-trained
| 960
| 0.001553
| 0.001317
|
175
|
model.layers.25.mlp.down_proj
| 0.048318
| 4,096
| 14,336
| 3.5
| 20.719397
| -47.925841
| 1.567751
| true
| 0.004863
|
dense
| -47.917582
| -0.686748
| -2.313091
| 64
| 0.205709
| 4,096
| 64
| 4,032
| 1
| 2.464925
| 0.004863
| 42.300262
|
success
| 0.069736
| 0.000001
|
under-trained
| 4,032
| 0.004863
| 0.003048
|
176
|
model.layers.25.mlp.gate_proj
| 0.069656
| 4,096
| 14,336
| 3.5
| 6.934986
| -13.859512
| 1.561265
| true
| 0.010035
|
dense
| -13.775954
| -0.623837
| -1.998492
| 64
| 0.237773
| 4,096
| 35
| 4,032
| 1
| 1.003196
| 0.010035
| 23.694872
|
success
| 0.100174
| 0.000001
|
under-trained
| 4,032
| 0.010035
| 0.003364
|
177
|
model.layers.25.mlp.up_proj
| 0.099564
| 4,096
| 14,336
| 3.5
| 7.081751
| -14.561236
| 1.562385
| true
| 0.008787
|
dense
| -14.43802
| -0.646459
| -2.056163
| 64
| 0.225705
| 4,096
| 27
| 4,032
| 1
| 1.170433
| 0.008787
| 25.686459
|
success
| 0.093739
| 0.000001
|
under-trained
| 4,032
| 0.008787
| 0.003317
|
178
|
model.layers.25.self_attn.k_proj
| 0.055758
| 1,024
| 4,096
| 4
| 7.444985
| -20.07066
| 1.133036
| true
| 0.002014
|
dense
| -19.664577
| -1.152309
| -2.695863
| 64
| 0.070419
| 1,024
| 25
| 960
| 1
| 1.288997
| 0.002014
| 34.958603
|
success
| 0.044882
| 0.000001
|
under-trained
| 960
| 0.002014
| 0.00111
|
179
|
model.layers.25.self_attn.o_proj
| 0.050357
| 4,096
| 4,096
| 1
| 11.625005
| -31.168731
| 1.566863
| true
| 0.002084
|
dense
| -30.821281
| -1.057331
| -2.68118
| 64
| 0.087633
| 4,096
| 64
| 4,032
| 1
| 1.328126
| 0.002084
| 42.058033
|
success
| 0.045647
| 0
|
under-trained
| 4,032
| 0.002084
| 0.001239
|
180
|
model.layers.25.self_attn.q_proj
| 0.049175
| 4,096
| 4,096
| 1
| 6.111549
| -16.078789
| 1.564285
| true
| 0.002339
|
dense
| -15.621483
| -1.100344
| -2.630886
| 64
| 0.07937
| 4,096
| 64
| 4,032
| 1
| 0.638944
| 0.002339
| 33.926746
|
success
| 0.048368
| 0
|
under-trained
| 4,032
| 0.002339
| 0.001004
|
181
|
model.layers.25.self_attn.v_proj
| 0.061502
| 1,024
| 4,096
| 4
| 15.363986
| -43.231103
| 1.13677
| true
| 0.001535
|
dense
| -42.63318
| -1.112548
| -2.813795
| 64
| 0.077171
| 1,024
| 28
| 960
| 1
| 2.714538
| 0.001535
| 50.262863
|
success
| 0.039183
| 0.000001
|
under-trained
| 960
| 0.001535
| 0.001205
|
182
|
model.layers.26.mlp.down_proj
| 0.055896
| 4,096
| 14,336
| 3.5
| 19.291067
| -45.162404
| 1.567739
| true
| 0.004559
|
dense
| -45.122915
| -0.700354
| -2.341105
| 64
| 0.199364
| 4,096
| 62
| 4,032
| 1
| 2.322968
| 0.004559
| 43.727108
|
success
| 0.067522
| 0.000001
|
under-trained
| 4,032
| 0.004559
| 0.002947
|
183
|
model.layers.26.mlp.gate_proj
| 0.085826
| 4,096
| 14,336
| 3.5
| 6.934983
| -13.885229
| 1.561158
| true
| 0.009949
|
dense
| -13.801381
| -0.631356
| -2.002201
| 64
| 0.233692
| 4,096
| 33
| 4,032
| 1
| 1.033148
| 0.009949
| 23.487938
|
success
| 0.099747
| 0.000001
|
under-trained
| 4,032
| 0.009949
| 0.003328
|
184
|
model.layers.26.mlp.up_proj
| 0.104035
| 4,096
| 14,336
| 3.5
| 6.006644
| -12.376087
| 1.562014
| true
| 0.008702
|
dense
| -12.173414
| -0.654805
| -2.0604
| 64
| 0.221409
| 4,096
| 18
| 4,032
| 1
| 1.180077
| 0.008702
| 25.444557
|
success
| 0.093283
| 0.000001
|
under-trained
| 4,032
| 0.008702
| 0.003379
|
185
|
model.layers.26.self_attn.k_proj
| 0.056932
| 1,024
| 4,096
| 4
| 5.374071
| -14.446276
| 1.131228
| true
| 0.00205
|
dense
| -13.682997
| -1.136951
| -2.688144
| 64
| 0.072954
| 1,024
| 50
| 960
| 1
| 0.618587
| 0.00205
| 35.578926
|
success
| 0.045282
| 0.000001
| 960
| 0.00205
| 0.00094
|
|
186
|
model.layers.26.self_attn.o_proj
| 0.088726
| 4,096
| 4,096
| 1
| 4.214271
| -9.801506
| 1.554751
| true
| 0.004723
|
dense
| -9.488855
| -1.02519
| -2.325789
| 64
| 0.094365
| 4,096
| 17
| 4,032
| 1
| 0.779575
| 0.004723
| 19.980146
|
success
| 0.068724
| 0
| 4,032
| 0.004723
| 0.001383
|
|
187
|
model.layers.26.self_attn.q_proj
| 0.043501
| 4,096
| 4,096
| 1
| 6.091549
| -15.42408
| 1.562849
| true
| 0.002937
|
dense
| -15.203184
| -1.081572
| -2.532046
| 64
| 0.082876
| 4,096
| 52
| 4,032
| 1
| 0.706071
| 0.002937
| 28.214588
|
success
| 0.054197
| 0
|
under-trained
| 4,032
| 0.002937
| 0.001088
|
188
|
model.layers.26.self_attn.v_proj
| 0.054334
| 1,024
| 4,096
| 4
| 13.788339
| -38.606445
| 1.136559
| true
| 0.001585
|
dense
| -38.187704
| -1.129555
| -2.799934
| 64
| 0.074207
| 1,024
| 26
| 960
| 1
| 2.508
| 0.001585
| 46.814354
|
success
| 0.039814
| 0.000001
|
under-trained
| 960
| 0.001585
| 0.001162
|
189
|
model.layers.27.mlp.down_proj
| 0.06611
| 4,096
| 14,336
| 3.5
| 17.607994
| -41.717967
| 1.567614
| true
| 0.004273
|
dense
| -41.524366
| -0.71679
| -2.369263
| 64
| 0.19196
| 4,096
| 64
| 4,032
| 1
| 2.075999
| 0.004273
| 44.92347
|
success
| 0.065369
| 0.000001
|
under-trained
| 4,032
| 0.004273
| 0.002816
|
190
|
model.layers.27.mlp.gate_proj
| 0.085341
| 4,096
| 14,336
| 3.5
| 7.507809
| -14.940597
| 1.560531
| true
| 0.010233
|
dense
| -14.876542
| -0.630876
| -1.990008
| 64
| 0.23395
| 4,096
| 51
| 4,032
| 1
| 0.911276
| 0.010233
| 22.862886
|
success
| 0.101157
| 0.000001
|
under-trained
| 4,032
| 0.010233
| 0.003158
|
191
|
model.layers.27.mlp.up_proj
| 0.090429
| 4,096
| 14,336
| 3.5
| 6.337803
| -13.036704
| 1.561669
| true
| 0.008771
|
dense
| -12.855776
| -0.657381
| -2.056975
| 64
| 0.220099
| 4,096
| 23
| 4,032
| 1
| 1.113009
| 0.008771
| 25.09539
|
success
| 0.093651
| 0.000001
|
under-trained
| 4,032
| 0.008771
| 0.003267
|
192
|
model.layers.27.self_attn.k_proj
| 0.062667
| 1,024
| 4,096
| 4
| 6.433864
| -17.394814
| 1.131266
| true
| 0.001979
|
dense
| -16.810661
| -1.179399
| -2.703634
| 64
| 0.066161
| 1,024
| 64
| 960
| 1
| 0.679233
| 0.001979
| 33.43763
|
success
| 0.044482
| 0.000001
|
under-trained
| 960
| 0.001979
| 0.00084
|
193
|
model.layers.27.self_attn.o_proj
| 0.052241
| 4,096
| 4,096
| 1
| 7.273309
| -18.565491
| 1.5641
| true
| 0.002802
|
dense
| -18.431408
| -1.090858
| -2.552551
| 64
| 0.081123
| 4,096
| 28
| 4,032
| 1
| 1.185544
| 0.002802
| 28.952957
|
success
| 0.052933
| 0
|
under-trained
| 4,032
| 0.002802
| 0.001198
|
194
|
model.layers.27.self_attn.q_proj
| 0.042504
| 4,096
| 4,096
| 1
| 5.579411
| -14.485803
| 1.562452
| true
| 0.002533
|
dense
| -14.109143
| -1.120044
| -2.596296
| 64
| 0.07585
| 4,096
| 64
| 4,032
| 1
| 0.572426
| 0.002533
| 29.940044
|
success
| 0.050333
| 0
| 4,032
| 0.002533
| 0.000931
|
|
195
|
model.layers.27.self_attn.v_proj
| 0.047939
| 1,024
| 4,096
| 4
| 12.779446
| -35.765415
| 1.136394
| true
| 0.00159
|
dense
| -35.399751
| -1.146404
| -2.798667
| 64
| 0.071383
| 1,024
| 29
| 960
| 1
| 2.187388
| 0.00159
| 44.901775
|
success
| 0.039872
| 0.000001
|
under-trained
| 960
| 0.00159
| 0.001103
|
196
|
model.layers.28.mlp.down_proj
| 0.04537
| 4,096
| 14,336
| 3.5
| 15.507892
| -36.617226
| 1.567459
| true
| 0.004353
|
dense
| -36.349747
| -0.712012
| -2.361199
| 64
| 0.194083
| 4,096
| 64
| 4,032
| 1
| 1.813487
| 0.004353
| 44.584877
|
success
| 0.065978
| 0.000001
|
under-trained
| 4,032
| 0.004353
| 0.00282
|
197
|
model.layers.28.mlp.gate_proj
| 0.055398
| 4,096
| 14,336
| 3.5
| 7.201658
| -14.241886
| 1.559661
| true
| 0.01053
|
dense
| -14.181808
| -0.636204
| -1.977584
| 64
| 0.231098
| 4,096
| 63
| 4,032
| 1
| 0.781335
| 0.01053
| 21.947275
|
success
| 0.102614
| 0.000001
|
under-trained
| 4,032
| 0.01053
| 0.002993
|
198
|
model.layers.28.mlp.up_proj
| 0.070715
| 4,096
| 14,336
| 3.5
| 6.613636
| -13.41884
| 1.561279
| true
| 0.009355
|
dense
| -13.332549
| -0.659056
| -2.028966
| 64
| 0.219252
| 4,096
| 30
| 4,032
| 1
| 1.024905
| 0.009355
| 23.437424
|
success
| 0.09672
| 0.000001
|
under-trained
| 4,032
| 0.009355
| 0.003147
|
199
|
model.layers.28.self_attn.k_proj
| 0.037904
| 1,024
| 4,096
| 4
| 5.71132
| -15.440612
| 1.131899
| true
| 0.001979
|
dense
| -14.690031
| -1.143304
| -2.70351
| 64
| 0.071895
| 1,024
| 63
| 960
| 1
| 0.593571
| 0.001979
| 36.325069
|
success
| 0.044488
| 0.000001
| 960
| 0.001979
| 0.000892
|
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