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
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
100
|
model.layers.14.mlp.up_proj
| 0.088045
| 4,096
| 14,336
| 3.5
| 4.728654
| -10.57703
| 1.558624
| true
| 0.005797
|
dense
| -10.503501
| -0.974476
| -2.236795
| 64
| 0.106053
| 4,096
| 10
| 4,032
| 1
| 1.179104
| 0.005797
| 18.294415
|
success
| 0.076138
| 0.000001
| 4,032
| 0.005797
| 0.001769
|
|
101
|
model.layers.14.self_attn.k_proj
| 0.052885
| 1,024
| 4,096
| 4
| 7.301511
| -19.055762
| 1.129169
| true
| 0.002456
|
dense
| -19.051874
| -1.337155
| -2.609838
| 64
| 0.046009
| 1,024
| 62
| 960
| 1
| 0.800293
| 0.002456
| 18.736265
|
success
| 0.049554
| 0.000001
|
under-trained
| 960
| 0.002456
| 0.000601
|
102
|
model.layers.14.self_attn.o_proj
| 0.081484
| 4,096
| 4,096
| 1
| 6.163327
| -16.709728
| 1.564028
| true
| 0.001945
|
dense
| -16.529209
| -1.267445
| -2.711154
| 64
| 0.05402
| 4,096
| 14
| 4,032
| 1
| 1.379957
| 0.001945
| 27.778484
|
success
| 0.044098
| 0
|
under-trained
| 4,032
| 0.001945
| 0.000851
|
103
|
model.layers.14.self_attn.q_proj
| 0.078813
| 4,096
| 4,096
| 1
| 9.171611
| -23.894232
| 1.561724
| true
| 0.002482
|
dense
| -23.888121
| -1.267009
| -2.605238
| 64
| 0.054074
| 4,096
| 64
| 4,032
| 1
| 1.021451
| 0.002482
| 21.788572
|
success
| 0.049817
| 0
|
under-trained
| 4,032
| 0.002482
| 0.000732
|
104
|
model.layers.14.self_attn.v_proj
| 0.052027
| 1,024
| 4,096
| 4
| 15.531955
| -48.761606
| 1.136586
| true
| 0.000725
|
dense
| -48.656321
| -1.501851
| -3.139438
| 64
| 0.031488
| 1,024
| 26
| 960
| 1
| 2.849951
| 0.000725
| 43.409729
|
success
| 0.026933
| 0.000001
|
under-trained
| 960
| 0.000725
| 0.000495
|
105
|
model.layers.15.mlp.down_proj
| 0.03222
| 4,096
| 14,336
| 3.5
| 20.178456
| -54.219032
| 1.567939
| true
| 0.002056
|
dense
| -54.08938
| -1.004997
| -2.686976
| 64
| 0.098856
| 4,096
| 62
| 4,032
| 1
| 2.435666
| 0.002056
| 48.08157
|
success
| 0.045343
| 0.000001
|
under-trained
| 4,032
| 0.002056
| 0.001466
|
106
|
model.layers.15.mlp.gate_proj
| 0.071743
| 4,096
| 14,336
| 3.5
| 5.233762
| -11.880146
| 1.559517
| true
| 0.005371
|
dense
| -11.838327
| -1.002592
| -2.269906
| 64
| 0.099405
| 4,096
| 13
| 4,032
| 1
| 1.174234
| 0.005371
| 18.506042
|
success
| 0.07329
| 0.000001
| 4,032
| 0.005371
| 0.00155
|
|
107
|
model.layers.15.mlp.up_proj
| 0.066682
| 4,096
| 14,336
| 3.5
| 5.879578
| -13.534449
| 1.561189
| true
| 0.00499
|
dense
| -13.495264
| -0.986517
| -2.301942
| 64
| 0.103153
| 4,096
| 16
| 4,032
| 1
| 1.219894
| 0.00499
| 20.674023
|
success
| 0.070636
| 0.000001
| 4,032
| 0.00499
| 0.001588
|
|
108
|
model.layers.15.self_attn.k_proj
| 0.099247
| 1,024
| 4,096
| 4
| 9.423515
| -28.762983
| 1.136285
| true
| 0.000887
|
dense
| -27.768991
| -1.35326
| -3.052256
| 64
| 0.044334
| 1,024
| 50
| 960
| 1
| 1.191265
| 0.000887
| 50.003071
|
success
| 0.029776
| 0.000001
|
under-trained
| 960
| 0.000887
| 0.000633
|
109
|
model.layers.15.self_attn.o_proj
| 0.032321
| 4,096
| 4,096
| 1
| 15.634389
| -46.124784
| 1.567676
| true
| 0.001121
|
dense
| -45.919358
| -1.286214
| -2.950213
| 64
| 0.051735
| 4,096
| 34
| 4,032
| 1
| 2.509777
| 0.001121
| 46.13166
|
success
| 0.033488
| 0
|
under-trained
| 4,032
| 0.001121
| 0.00079
|
110
|
model.layers.15.self_attn.q_proj
| 0.064558
| 4,096
| 4,096
| 1
| 12.589234
| -35.11913
| 1.566411
| true
| 0.001623
|
dense
| -35.114409
| -1.288
| -2.789616
| 64
| 0.051523
| 4,096
| 53
| 4,032
| 1
| 1.591904
| 0.001623
| 31.740629
|
success
| 0.04029
| 0
|
under-trained
| 4,032
| 0.001623
| 0.000746
|
111
|
model.layers.15.self_attn.v_proj
| 0.064377
| 1,024
| 4,096
| 4
| 28.481666
| -92.912677
| 1.137139
| true
| 0.000547
|
dense
| -92.497945
| -1.528765
| -3.262192
| 64
| 0.029596
| 1,024
| 16
| 960
| 1
| 6.870417
| 0.000547
| 54.128735
|
success
| 0.023383
| 0.000001
|
under-trained
| 960
| 0.000547
| 0.000482
|
112
|
model.layers.16.mlp.down_proj
| 0.087122
| 4,096
| 14,336
| 3.5
| 18.278263
| -47.557774
| 1.567344
| true
| 0.002501
|
dense
| -47.528136
| -1.00071
| -2.601876
| 64
| 0.099837
| 4,096
| 64
| 4,032
| 1
| 2.159783
| 0.002501
| 39.917759
|
success
| 0.050011
| 0.000001
|
under-trained
| 4,032
| 0.002501
| 0.001466
|
113
|
model.layers.16.mlp.gate_proj
| 0.110417
| 4,096
| 14,336
| 3.5
| 4.460473
| -9.956797
| 1.55842
| true
| 0.005858
|
dense
| -9.879789
| -0.988953
| -2.232229
| 64
| 0.102576
| 4,096
| 8
| 4,032
| 1
| 1.223462
| 0.005858
| 17.509598
|
success
| 0.076539
| 0.000001
| 4,032
| 0.005858
| 0.001726
|
|
114
|
model.layers.16.mlp.up_proj
| 0.107535
| 4,096
| 14,336
| 3.5
| 4.569904
| -10.342811
| 1.559859
| true
| 0.005455
|
dense
| -10.244776
| -0.983598
| -2.263245
| 64
| 0.103849
| 4,096
| 8
| 4,032
| 1
| 1.262152
| 0.005455
| 19.039099
|
success
| 0.073855
| 0.000001
| 4,032
| 0.005455
| 0.001755
|
|
115
|
model.layers.16.self_attn.k_proj
| 0.095658
| 1,024
| 4,096
| 4
| 28.090519
| -86.373939
| 1.136644
| true
| 0.000842
|
dense
| -86.024576
| -1.364159
| -3.074843
| 64
| 0.043236
| 1,024
| 9
| 960
| 1
| 9.030173
| 0.000842
| 51.367046
|
success
| 0.029012
| 0.000001
|
under-trained
| 960
| 0.000842
| 0.000754
|
116
|
model.layers.16.self_attn.o_proj
| 0.030218
| 4,096
| 4,096
| 1
| 14.659859
| -42.945266
| 1.567561
| true
| 0.001176
|
dense
| -42.756544
| -1.27997
| -2.929446
| 64
| 0.052484
| 4,096
| 45
| 4,032
| 1
| 2.036292
| 0.001176
| 44.614502
|
success
| 0.034299
| 0
|
under-trained
| 4,032
| 0.001176
| 0.000781
|
117
|
model.layers.16.self_attn.q_proj
| 0.066623
| 4,096
| 4,096
| 1
| 12.333208
| -33.995883
| 1.565982
| true
| 0.001752
|
dense
| -33.993732
| -1.286641
| -2.756451
| 64
| 0.051684
| 4,096
| 55
| 4,032
| 1
| 1.528169
| 0.001752
| 29.499187
|
success
| 0.041858
| 0
|
under-trained
| 4,032
| 0.001752
| 0.000744
|
118
|
model.layers.16.self_attn.v_proj
| 0.086352
| 1,024
| 4,096
| 4
| 27.09401
| -87.411861
| 1.137041
| true
| 0.000594
|
dense
| -87.27872
| -1.519833
| -3.226243
| 64
| 0.030211
| 1,024
| 15
| 960
| 1
| 6.737444
| 0.000594
| 50.863968
|
success
| 0.024371
| 0.000001
|
under-trained
| 960
| 0.000594
| 0.000497
|
119
|
model.layers.17.mlp.down_proj
| 0.057253
| 4,096
| 14,336
| 3.5
| 19.359662
| -51.849015
| 1.567815
| true
| 0.002098
|
dense
| -51.711726
| -1.007425
| -2.678198
| 64
| 0.098305
| 4,096
| 64
| 4,032
| 1
| 2.294958
| 0.002098
| 46.856842
|
success
| 0.045804
| 0.000001
|
under-trained
| 4,032
| 0.002098
| 0.001451
|
120
|
model.layers.17.mlp.gate_proj
| 0.087451
| 4,096
| 14,336
| 3.5
| 5.048414
| -11.485839
| 1.560231
| true
| 0.005307
|
dense
| -11.425627
| -0.99271
| -2.275138
| 64
| 0.101693
| 4,096
| 11
| 4,032
| 1
| 1.220643
| 0.005307
| 19.161421
|
success
| 0.07285
| 0.000001
| 4,032
| 0.005307
| 0.001603
|
|
121
|
model.layers.17.mlp.up_proj
| 0.106461
| 4,096
| 14,336
| 3.5
| 4.94852
| -11.495758
| 1.561953
| true
| 0.004753
|
dense
| -11.37885
| -0.988145
| -2.32307
| 64
| 0.102767
| 4,096
| 8
| 4,032
| 1
| 1.396013
| 0.004753
| 21.623453
|
success
| 0.068939
| 0.000001
| 4,032
| 0.004753
| 0.001731
|
|
122
|
model.layers.17.self_attn.k_proj
| 0.079491
| 1,024
| 4,096
| 4
| 7.654828
| -19.952351
| 1.126326
| true
| 0.002475
|
dense
| -19.939089
| -1.35584
| -2.606506
| 64
| 0.044072
| 1,024
| 63
| 960
| 1
| 0.838429
| 0.002475
| 17.810081
|
success
| 0.049745
| 0.000001
|
under-trained
| 960
| 0.002475
| 0.000574
|
123
|
model.layers.17.self_attn.o_proj
| 0.028133
| 4,096
| 4,096
| 1
| 12.521953
| -36.428269
| 1.567143
| true
| 0.001233
|
dense
| -36.314292
| -1.304693
| -2.909152
| 64
| 0.04958
| 4,096
| 59
| 4,032
| 1
| 1.500031
| 0.001233
| 40.221554
|
success
| 0.035109
| 0
|
under-trained
| 4,032
| 0.001233
| 0.000712
|
124
|
model.layers.17.self_attn.q_proj
| 0.083729
| 4,096
| 4,096
| 1
| 9.104787
| -22.625788
| 1.557598
| true
| 0.003273
|
dense
| -22.625483
| -1.267234
| -2.485043
| 64
| 0.054046
| 4,096
| 64
| 4,032
| 1
| 1.013098
| 0.003273
| 16.512367
|
success
| 0.057211
| 0
|
under-trained
| 4,032
| 0.003273
| 0.000723
|
125
|
model.layers.17.self_attn.v_proj
| 0.070676
| 1,024
| 4,096
| 4
| 25.021776
| -81.282501
| 1.137071
| true
| 0.000564
|
dense
| -80.976471
| -1.530491
| -3.248471
| 64
| 0.029479
| 1,024
| 17
| 960
| 1
| 5.826136
| 0.000564
| 52.237156
|
success
| 0.023756
| 0.000001
|
under-trained
| 960
| 0.000564
| 0.000479
|
126
|
model.layers.18.mlp.down_proj
| 0.050305
| 4,096
| 14,336
| 3.5
| 22.059051
| -59.651624
| 1.567991
| true
| 0.001976
|
dense
| -59.524687
| -1.015775
| -2.704179
| 64
| 0.096433
| 4,096
| 62
| 4,032
| 1
| 2.674502
| 0.001976
| 48.798252
|
success
| 0.044454
| 0.000001
|
under-trained
| 4,032
| 0.001976
| 0.001437
|
127
|
model.layers.18.mlp.gate_proj
| 0.101667
| 4,096
| 14,336
| 3.5
| 4.72942
| -10.654039
| 1.559201
| true
| 0.005588
|
dense
| -10.596874
| -1.00335
| -2.252716
| 64
| 0.099232
| 4,096
| 9
| 4,032
| 1
| 1.24314
| 0.005588
| 17.756847
|
success
| 0.074755
| 0.000001
| 4,032
| 0.005588
| 0.001601
|
|
128
|
model.layers.18.mlp.up_proj
| 0.093648
| 4,096
| 14,336
| 3.5
| 5.078744
| -11.618822
| 1.560661
| true
| 0.005155
|
dense
| -11.560412
| -1.001033
| -2.287735
| 64
| 0.099762
| 4,096
| 10
| 4,032
| 1
| 1.289812
| 0.005155
| 19.350937
|
success
| 0.071801
| 0.000001
| 4,032
| 0.005155
| 0.001593
|
|
129
|
model.layers.18.self_attn.k_proj
| 0.084797
| 1,024
| 4,096
| 4
| 9.731679
| -29.269051
| 1.135682
| true
| 0.000983
|
dense
| -28.591311
| -1.352156
| -3.007606
| 64
| 0.044447
| 1,024
| 34
| 960
| 1
| 1.497471
| 0.000983
| 45.232372
|
success
| 0.031347
| 0.000001
|
under-trained
| 960
| 0.000983
| 0.000673
|
130
|
model.layers.18.self_attn.o_proj
| 0.053086
| 4,096
| 4,096
| 1
| 12.688044
| -36.572721
| 1.566637
| true
| 0.001311
|
dense
| -36.512068
| -1.321364
| -2.882455
| 64
| 0.047713
| 4,096
| 64
| 4,032
| 1
| 1.461006
| 0.001311
| 36.399193
|
success
| 0.036205
| 0
|
under-trained
| 4,032
| 0.001311
| 0.00068
|
131
|
model.layers.18.self_attn.q_proj
| 0.044601
| 4,096
| 4,096
| 1
| 11.852522
| -32.606474
| 1.565888
| true
| 0.001774
|
dense
| -32.602863
| -1.2781
| -2.751016
| 64
| 0.052711
| 4,096
| 43
| 4,032
| 1
| 1.654994
| 0.001774
| 29.71092
|
success
| 0.04212
| 0
|
under-trained
| 4,032
| 0.001774
| 0.000775
|
132
|
model.layers.18.self_attn.v_proj
| 0.08094
| 1,024
| 4,096
| 4
| 25.83335
| -83.407907
| 1.137018
| true
| 0.000591
|
dense
| -83.302488
| -1.530775
| -3.228691
| 64
| 0.029459
| 1,024
| 11
| 960
| 1
| 7.487537
| 0.000591
| 49.878788
|
success
| 0.024303
| 0.000001
|
under-trained
| 960
| 0.000591
| 0.000491
|
133
|
model.layers.19.mlp.down_proj
| 0.046149
| 4,096
| 14,336
| 3.5
| 24.274677
| -66.061206
| 1.568086
| true
| 0.001899
|
dense
| -65.986934
| -1.028575
| -2.721404
| 64
| 0.093632
| 4,096
| 63
| 4,032
| 1
| 2.932334
| 0.001899
| 49.298027
|
success
| 0.043581
| 0.000001
|
under-trained
| 4,032
| 0.001899
| 0.001401
|
134
|
model.layers.19.mlp.gate_proj
| 0.123848
| 4,096
| 14,336
| 3.5
| 4.70368
| -10.993695
| 1.561626
| true
| 0.0046
|
dense
| -10.883689
| -1.026132
| -2.337254
| 64
| 0.09416
| 4,096
| 7
| 4,032
| 1
| 1.39986
| 0.0046
| 20.470171
|
success
| 0.067822
| 0.000001
| 4,032
| 0.0046
| 0.001578
|
|
135
|
model.layers.19.mlp.up_proj
| 0.098325
| 4,096
| 14,336
| 3.5
| 5.139143
| -12.166721
| 1.562589
| true
| 0.004291
|
dense
| -12.069168
| -1.027631
| -2.367461
| 64
| 0.093836
| 4,096
| 9
| 4,032
| 1
| 1.379714
| 0.004291
| 21.869057
|
success
| 0.065504
| 0.000001
| 4,032
| 0.004291
| 0.001497
|
|
136
|
model.layers.19.self_attn.k_proj
| 0.051625
| 1,024
| 4,096
| 4
| 10.897674
| -32.478873
| 1.135455
| true
| 0.001046
|
dense
| -32.330556
| -1.402143
| -2.980349
| 64
| 0.039615
| 1,024
| 22
| 960
| 1
| 2.110191
| 0.001046
| 37.862217
|
success
| 0.032346
| 0.000001
|
under-trained
| 960
| 0.001046
| 0.000633
|
137
|
model.layers.19.self_attn.o_proj
| 0.04253
| 4,096
| 4,096
| 1
| 17.472803
| -52.45571
| 1.567787
| true
| 0.000995
|
dense
| -52.225657
| -1.323864
| -3.002135
| 64
| 0.047439
| 4,096
| 33
| 4,032
| 1
| 2.867547
| 0.000995
| 47.672775
|
success
| 0.031545
| 0
|
under-trained
| 4,032
| 0.000995
| 0.000728
|
138
|
model.layers.19.self_attn.q_proj
| 0.04941
| 4,096
| 4,096
| 1
| 10.202023
| -28.205337
| 1.565039
| true
| 0.001719
|
dense
| -28.201599
| -1.339994
| -2.764681
| 64
| 0.045709
| 4,096
| 64
| 4,032
| 1
| 1.150253
| 0.001719
| 26.588095
|
success
| 0.041463
| 0
|
under-trained
| 4,032
| 0.001719
| 0.000634
|
139
|
model.layers.19.self_attn.v_proj
| 0.064489
| 1,024
| 4,096
| 4
| 22.368846
| -71.606298
| 1.136987
| true
| 0.000629
|
dense
| -71.518224
| -1.51859
| -3.201162
| 64
| 0.030298
| 1,024
| 19
| 960
| 1
| 4.90235
| 0.000629
| 48.147243
|
success
| 0.025085
| 0.000001
|
under-trained
| 960
| 0.000629
| 0.000488
|
140
|
model.layers.20.mlp.down_proj
| 0.066527
| 4,096
| 14,336
| 3.5
| 26.106228
| -71.931461
| 1.56813
| true
| 0.001757
|
dense
| -71.776794
| -1.045039
| -2.755337
| 64
| 0.090149
| 4,096
| 63
| 4,032
| 1
| 3.163087
| 0.001757
| 51.321369
|
success
| 0.041911
| 0.000001
|
under-trained
| 4,032
| 0.001757
| 0.001353
|
141
|
model.layers.20.mlp.gate_proj
| 0.112275
| 4,096
| 14,336
| 3.5
| 5.347478
| -12.838731
| 1.563282
| true
| 0.003973
|
dense
| -12.746096
| -1.045397
| -2.400895
| 64
| 0.090075
| 4,096
| 8
| 4,032
| 1
| 1.537066
| 0.003973
| 22.672419
|
success
| 0.063031
| 0.000001
| 4,032
| 0.003973
| 0.001456
|
|
142
|
model.layers.20.mlp.up_proj
| 0.096243
| 4,096
| 14,336
| 3.5
| 5.597637
| -13.746404
| 1.564401
| true
| 0.003501
|
dense
| -13.614599
| -1.052082
| -2.455751
| 64
| 0.088699
| 4,096
| 9
| 4,032
| 1
| 1.532546
| 0.003501
| 25.332001
|
success
| 0.059173
| 0.000001
| 4,032
| 0.003501
| 0.001402
|
|
143
|
model.layers.20.self_attn.k_proj
| 0.056116
| 1,024
| 4,096
| 4
| 11.830419
| -36.589825
| 1.136153
| true
| 0.000807
|
dense
| -36.31897
| -1.462648
| -3.09286
| 64
| 0.034463
| 1,024
| 32
| 960
| 1
| 1.914566
| 0.000807
| 42.678757
|
success
| 0.028416
| 0.000001
|
under-trained
| 960
| 0.000807
| 0.000528
|
144
|
model.layers.20.self_attn.o_proj
| 0.069663
| 4,096
| 4,096
| 1
| 28.4237
| -87.707927
| 1.568112
| true
| 0.000821
|
dense
| -87.527496
| -1.362754
| -3.085732
| 64
| 0.043376
| 4,096
| 22
| 4,032
| 1
| 5.846752
| 0.000821
| 52.841881
|
success
| 0.028651
| 0
|
under-trained
| 4,032
| 0.000821
| 0.000688
|
145
|
model.layers.20.self_attn.q_proj
| 0.05119
| 4,096
| 4,096
| 1
| 10.494094
| -29.652063
| 1.565325
| true
| 0.001494
|
dense
| -29.646998
| -1.3821
| -2.825595
| 64
| 0.041486
| 4,096
| 64
| 4,032
| 1
| 1.186762
| 0.001494
| 27.764874
|
success
| 0.038655
| 0
|
under-trained
| 4,032
| 0.001494
| 0.000577
|
146
|
model.layers.20.self_attn.v_proj
| 0.093938
| 1,024
| 4,096
| 4
| 24.501967
| -79.827178
| 1.137067
| true
| 0.000552
|
dense
| -79.417424
| -1.53325
| -3.257991
| 64
| 0.029292
| 1,024
| 19
| 960
| 1
| 5.391721
| 0.000552
| 53.056709
|
success
| 0.023497
| 0.000001
|
under-trained
| 960
| 0.000552
| 0.000474
|
147
|
model.layers.21.mlp.down_proj
| 0.064974
| 4,096
| 14,336
| 3.5
| 26.468458
| -73.706019
| 1.568107
| true
| 0.001642
|
dense
| -73.33047
| -1.065387
| -2.784674
| 64
| 0.086023
| 4,096
| 63
| 4,032
| 1
| 3.208724
| 0.001642
| 52.394669
|
success
| 0.040519
| 0.000001
|
under-trained
| 4,032
| 0.001642
| 0.001292
|
148
|
model.layers.21.mlp.gate_proj
| 0.115016
| 4,096
| 14,336
| 3.5
| 6.141163
| -15.168297
| 1.564783
| true
| 0.003389
|
dense
| -15.086632
| -1.064503
| -2.469939
| 64
| 0.086198
| 4,096
| 8
| 4,032
| 1
| 1.817676
| 0.003389
| 25.435242
|
success
| 0.058214
| 0.000001
|
under-trained
| 4,032
| 0.003389
| 0.001383
|
149
|
model.layers.21.mlp.up_proj
| 0.106059
| 4,096
| 14,336
| 3.5
| 6.094915
| -15.4517
| 1.565676
| true
| 0.002916
|
dense
| -15.282092
| -1.076371
| -2.535179
| 64
| 0.083874
| 4,096
| 8
| 4,032
| 1
| 1.801325
| 0.002916
| 28.761208
|
success
| 0.054002
| 0.000001
|
under-trained
| 4,032
| 0.002916
| 0.001339
|
150
|
model.layers.21.self_attn.k_proj
| 0.049746
| 1,024
| 4,096
| 4
| 7.629897
| -21.971864
| 1.132671
| true
| 0.001319
|
dense
| -21.927961
| -1.469238
| -2.879707
| 64
| 0.033944
| 1,024
| 60
| 960
| 1
| 0.855916
| 0.001319
| 25.731724
|
success
| 0.03632
| 0.000001
|
under-trained
| 960
| 0.001319
| 0.000453
|
151
|
model.layers.21.self_attn.o_proj
| 0.061163
| 4,096
| 4,096
| 1
| 22.63699
| -70.924932
| 1.568127
| true
| 0.000736
|
dense
| -70.323526
| -1.395994
| -3.133143
| 64
| 0.04018
| 4,096
| 42
| 4,032
| 1
| 3.33866
| 0.000736
| 54.594528
|
success
| 0.027129
| 0
|
under-trained
| 4,032
| 0.000736
| 0.000612
|
152
|
model.layers.21.self_attn.q_proj
| 0.053863
| 4,096
| 4,096
| 1
| 9.267359
| -25.456937
| 1.562925
| true
| 0.001791
|
dense
| -25.45525
| -1.401946
| -2.746946
| 64
| 0.039633
| 4,096
| 64
| 4,032
| 1
| 1.03342
| 0.001791
| 22.130991
|
success
| 0.042318
| 0
|
under-trained
| 4,032
| 0.001791
| 0.000539
|
153
|
model.layers.21.self_attn.v_proj
| 0.08334
| 1,024
| 4,096
| 4
| 30.733462
| -100.703772
| 1.137111
| true
| 0.000529
|
dense
| -100.628457
| -1.568105
| -3.276682
| 64
| 0.027033
| 1,024
| 11
| 960
| 1
| 8.964976
| 0.000529
| 51.118313
|
success
| 0.022996
| 0.000001
|
under-trained
| 960
| 0.000529
| 0.000449
|
154
|
model.layers.22.mlp.down_proj
| 0.092055
| 4,096
| 14,336
| 3.5
| 26.495596
| -73.430247
| 1.568081
| true
| 0.001693
|
dense
| -73.376784
| -1.081067
| -2.771413
| 64
| 0.082972
| 4,096
| 62
| 4,032
| 1
| 3.237944
| 0.001693
| 49.01701
|
success
| 0.041143
| 0.000001
|
under-trained
| 4,032
| 0.001693
| 0.001247
|
155
|
model.layers.22.mlp.gate_proj
| 0.115706
| 4,096
| 14,336
| 3.5
| 6.272838
| -15.50362
| 1.564791
| true
| 0.003376
|
dense
| -15.429582
| -1.06528
| -2.471548
| 64
| 0.086044
| 4,096
| 8
| 4,032
| 1
| 1.86423
| 0.003376
| 25.484016
|
success
| 0.058107
| 0.000001
|
under-trained
| 4,032
| 0.003376
| 0.00139
|
156
|
model.layers.22.mlp.up_proj
| 0.109543
| 4,096
| 14,336
| 3.5
| 6.262851
| -15.84857
| 1.565468
| true
| 0.002947
|
dense
| -15.714697
| -1.082538
| -2.530568
| 64
| 0.082692
| 4,096
| 8
| 4,032
| 1
| 1.860699
| 0.002947
| 28.056255
|
success
| 0.05429
| 0.000001
|
under-trained
| 4,032
| 0.002947
| 0.001335
|
157
|
model.layers.22.self_attn.k_proj
| 0.061843
| 1,024
| 4,096
| 4
| 7.847612
| -24.359356
| 1.134993
| true
| 0.000787
|
dense
| -23.882569
| -1.512321
| -3.104047
| 64
| 0.030738
| 1,024
| 44
| 960
| 1
| 1.032316
| 0.000787
| 39.059383
|
success
| 0.028053
| 0.000001
|
under-trained
| 960
| 0.000787
| 0.000436
|
158
|
model.layers.22.self_attn.o_proj
| 0.047603
| 4,096
| 4,096
| 1
| 15.036358
| -46.856894
| 1.56769
| true
| 0.000765
|
dense
| -46.407214
| -1.432106
| -3.11624
| 64
| 0.036974
| 4,096
| 63
| 4,032
| 1
| 1.768415
| 0.000765
| 48.320675
|
success
| 0.027662
| 0
|
under-trained
| 4,032
| 0.000765
| 0.000537
|
159
|
model.layers.22.self_attn.q_proj
| 0.046817
| 4,096
| 4,096
| 1
| 9.643863
| -27.110748
| 1.563508
| true
| 0.001545
|
dense
| -27.109173
| -1.447843
| -2.811192
| 64
| 0.035658
| 4,096
| 49
| 4,032
| 1
| 1.234838
| 0.001545
| 23.08602
|
success
| 0.039301
| 0
|
under-trained
| 4,032
| 0.001545
| 0.000505
|
160
|
model.layers.22.self_attn.v_proj
| 0.058297
| 1,024
| 4,096
| 4
| 24.13966
| -79.221554
| 1.137047
| true
| 0.000523
|
dense
| -79.091265
| -1.58329
| -3.281801
| 64
| 0.026104
| 1,024
| 17
| 960
| 1
| 5.612192
| 0.000523
| 49.947212
|
success
| 0.022861
| 0.000001
|
under-trained
| 960
| 0.000523
| 0.000423
|
161
|
model.layers.23.mlp.down_proj
| 0.080725
| 4,096
| 14,336
| 3.5
| 26.884795
| -73.691522
| 1.567962
| true
| 0.001815
|
dense
| -73.689571
| -1.094295
| -2.741011
| 64
| 0.080483
| 4,096
| 62
| 4,032
| 1
| 3.287372
| 0.001815
| 44.331905
|
success
| 0.042608
| 0.000001
|
under-trained
| 4,032
| 0.001815
| 0.001209
|
162
|
model.layers.23.mlp.gate_proj
| 0.105507
| 4,096
| 14,336
| 3.5
| 6.553426
| -16.146519
| 1.564583
| true
| 0.003437
|
dense
| -16.098287
| -1.069908
| -2.463829
| 64
| 0.085132
| 4,096
| 9
| 4,032
| 1
| 1.851142
| 0.003437
| 24.769682
|
success
| 0.058625
| 0.000001
|
under-trained
| 4,032
| 0.003437
| 0.001351
|
163
|
model.layers.23.mlp.up_proj
| 0.098312
| 4,096
| 14,336
| 3.5
| 6.451926
| -16.419561
| 1.565579
| true
| 0.002852
|
dense
| -16.298551
| -1.0934
| -2.544909
| 64
| 0.080649
| 4,096
| 9
| 4,032
| 1
| 1.817309
| 0.002852
| 28.281919
|
success
| 0.053401
| 0.000001
|
under-trained
| 4,032
| 0.002852
| 0.001282
|
164
|
model.layers.23.self_attn.k_proj
| 0.044231
| 1,024
| 4,096
| 4
| 8.685878
| -26.818006
| 1.135234
| true
| 0.000817
|
dense
| -26.599642
| -1.528306
| -3.087541
| 64
| 0.029627
| 1,024
| 50
| 960
| 1
| 1.086947
| 0.000817
| 36.243912
|
success
| 0.028591
| 0.000001
|
under-trained
| 960
| 0.000817
| 0.000417
|
165
|
model.layers.23.self_attn.o_proj
| 0.086024
| 4,096
| 4,096
| 1
| 13.179125
| -38.548754
| 1.566138
| true
| 0.001189
|
dense
| -38.540363
| -1.420885
| -2.924986
| 64
| 0.037942
| 4,096
| 64
| 4,032
| 1
| 1.522391
| 0.001189
| 31.922808
|
success
| 0.034475
| 0
|
under-trained
| 4,032
| 0.001189
| 0.000542
|
166
|
model.layers.23.self_attn.q_proj
| 0.047519
| 4,096
| 4,096
| 1
| 10.634295
| -31.235869
| 1.565653
| true
| 0.001155
|
dense
| -31.228127
| -1.471754
| -2.937277
| 64
| 0.033748
| 4,096
| 48
| 4,032
| 1
| 1.390591
| 0.001155
| 29.209417
|
success
| 0.033991
| 0
|
under-trained
| 4,032
| 0.001155
| 0.000486
|
167
|
model.layers.23.self_attn.v_proj
| 0.04169
| 1,024
| 4,096
| 4
| 17.404055
| -56.238253
| 1.136861
| true
| 0.000587
|
dense
| -56.055635
| -1.56089
| -3.23133
| 64
| 0.027486
| 1,024
| 29
| 960
| 1
| 3.046157
| 0.000587
| 46.821026
|
success
| 0.024229
| 0.000001
|
under-trained
| 960
| 0.000587
| 0.000428
|
168
|
model.layers.24.mlp.down_proj
| 0.09546
| 4,096
| 14,336
| 3.5
| 24.953419
| -67.179076
| 1.567588
| true
| 0.002032
|
dense
| -67.178959
| -1.106459
| -2.692179
| 64
| 0.07826
| 4,096
| 64
| 4,032
| 1
| 2.994177
| 0.002032
| 38.523045
|
success
| 0.045072
| 0.000001
|
under-trained
| 4,032
| 0.002032
| 0.001169
|
169
|
model.layers.24.mlp.gate_proj
| 0.125072
| 4,096
| 14,336
| 3.5
| 15.395967
| -37.963343
| 1.564485
| true
| 0.003421
|
dense
| -37.963322
| -1.075045
| -2.465798
| 64
| 0.084131
| 4,096
| 64
| 4,032
| 1
| 1.799496
| 0.003421
| 24.589685
|
success
| 0.058493
| 0.000001
|
under-trained
| 4,032
| 0.003421
| 0.001211
|
170
|
model.layers.24.mlp.up_proj
| 0.095826
| 4,096
| 14,336
| 3.5
| 6.089533
| -15.509972
| 1.565375
| true
| 0.002838
|
dense
| -15.365067
| -1.10238
| -2.546989
| 64
| 0.078999
| 4,096
| 9
| 4,032
| 1
| 1.696511
| 0.002838
| 27.836147
|
success
| 0.053273
| 0.000001
|
under-trained
| 4,032
| 0.002838
| 0.001248
|
171
|
model.layers.24.self_attn.k_proj
| 0.047288
| 1,024
| 4,096
| 4
| 7.493427
| -22.751314
| 1.133444
| true
| 0.00092
|
dense
| -22.595868
| -1.558617
| -3.036169
| 64
| 0.02763
| 1,024
| 51
| 960
| 1
| 0.909262
| 0.00092
| 30.029797
|
success
| 0.030333
| 0.000001
|
under-trained
| 960
| 0.00092
| 0.000378
|
172
|
model.layers.24.self_attn.o_proj
| 0.071055
| 4,096
| 4,096
| 1
| 16.48228
| -49.786721
| 1.567127
| true
| 0.000954
|
dense
| -49.785523
| -1.479156
| -3.020621
| 64
| 0.033178
| 4,096
| 64
| 4,032
| 1
| 1.935285
| 0.000954
| 34.79084
|
success
| 0.030881
| 0
|
under-trained
| 4,032
| 0.000954
| 0.000484
|
173
|
model.layers.24.self_attn.q_proj
| 0.036041
| 4,096
| 4,096
| 1
| 9.925885
| -28.910437
| 1.564274
| true
| 0.001223
|
dense
| -28.908021
| -1.519081
| -2.912631
| 64
| 0.030263
| 4,096
| 56
| 4,032
| 1
| 1.192772
| 0.001223
| 24.74852
|
success
| 0.034969
| 0
|
under-trained
| 4,032
| 0.001223
| 0.000424
|
174
|
model.layers.24.self_attn.v_proj
| 0.058889
| 1,024
| 4,096
| 4
| 23.276687
| -76.282564
| 1.13697
| true
| 0.000528
|
dense
| -76.228967
| -1.599989
| -3.277209
| 64
| 0.02512
| 1,024
| 18
| 960
| 1
| 5.250666
| 0.000528
| 47.557606
|
success
| 0.022982
| 0.000001
|
under-trained
| 960
| 0.000528
| 0.000407
|
175
|
model.layers.25.mlp.down_proj
| 0.12544
| 4,096
| 14,336
| 3.5
| 22.601148
| -60.042548
| 1.567144
| true
| 0.002205
|
dense
| -60.04247
| -1.113156
| -2.656615
| 64
| 0.077063
| 4,096
| 64
| 4,032
| 1
| 2.700143
| 0.002205
| 34.95097
|
success
| 0.046956
| 0.000001
|
under-trained
| 4,032
| 0.002205
| 0.001145
|
176
|
model.layers.25.mlp.gate_proj
| 0.12068
| 4,096
| 14,336
| 3.5
| 13.940288
| -34.545454
| 1.564761
| true
| 0.003326
|
dense
| -34.545329
| -1.073043
| -2.478102
| 64
| 0.084519
| 4,096
| 64
| 4,032
| 1
| 1.617536
| 0.003326
| 25.413172
|
success
| 0.05767
| 0.000001
|
under-trained
| 4,032
| 0.003326
| 0.001208
|
177
|
model.layers.25.mlp.up_proj
| 0.09619
| 4,096
| 14,336
| 3.5
| 5.860057
| -14.98204
| 1.565308
| true
| 0.002776
|
dense
| -14.800526
| -1.108379
| -2.556637
| 64
| 0.077915
| 4,096
| 9
| 4,032
| 1
| 1.620019
| 0.002776
| 28.071037
|
success
| 0.052684
| 0.000001
| 4,032
| 0.002776
| 0.001226
|
|
178
|
model.layers.25.self_attn.k_proj
| 0.086496
| 1,024
| 4,096
| 4
| 7.71323
| -25.242188
| 1.135881
| true
| 0.000534
|
dense
| -24.216169
| -1.590238
| -3.272583
| 64
| 0.02569
| 1,024
| 63
| 960
| 1
| 0.845788
| 0.000534
| 48.122189
|
success
| 0.023105
| 0.000001
|
under-trained
| 960
| 0.000534
| 0.000344
|
179
|
model.layers.25.self_attn.o_proj
| 0.083508
| 4,096
| 4,096
| 1
| 13.930974
| -42.769201
| 1.566749
| true
| 0.000851
|
dense
| -42.640661
| -1.498674
| -3.07008
| 64
| 0.031719
| 4,096
| 63
| 4,032
| 1
| 1.62915
| 0.000851
| 37.273968
|
success
| 0.029172
| 0
|
under-trained
| 4,032
| 0.000851
| 0.000457
|
180
|
model.layers.25.self_attn.q_proj
| 0.039704
| 4,096
| 4,096
| 1
| 9.001914
| -26.694807
| 1.564694
| true
| 0.001083
|
dense
| -26.675192
| -1.524629
| -2.965459
| 64
| 0.029879
| 4,096
| 51
| 4,032
| 1
| 1.120492
| 0.001083
| 27.594992
|
success
| 0.032906
| 0
|
under-trained
| 4,032
| 0.001083
| 0.000419
|
181
|
model.layers.25.self_attn.v_proj
| 0.079096
| 1,024
| 4,096
| 4
| 23.327133
| -76.709015
| 1.136906
| true
| 0.000515
|
dense
| -76.58582
| -1.598524
| -3.288403
| 64
| 0.025204
| 1,024
| 11
| 960
| 1
| 6.731884
| 0.000515
| 48.964264
|
success
| 0.022688
| 0.000001
|
under-trained
| 960
| 0.000515
| 0.000422
|
182
|
model.layers.26.mlp.down_proj
| 0.134245
| 4,096
| 14,336
| 3.5
| 21.974989
| -57.246944
| 1.566523
| true
| 0.002483
|
dense
| -57.246938
| -1.118854
| -2.605095
| 64
| 0.076058
| 4,096
| 64
| 4,032
| 1
| 2.621874
| 0.002483
| 30.636671
|
success
| 0.049826
| 0.000001
|
under-trained
| 4,032
| 0.002483
| 0.001126
|
183
|
model.layers.26.mlp.gate_proj
| 0.145916
| 4,096
| 14,336
| 3.5
| 14.525749
| -35.792439
| 1.564134
| true
| 0.003435
|
dense
| -35.791913
| -1.068163
| -2.464068
| 64
| 0.085475
| 4,096
| 64
| 4,032
| 1
| 1.690719
| 0.003435
| 24.883167
|
success
| 0.058609
| 0.000001
|
under-trained
| 4,032
| 0.003435
| 0.001223
|
184
|
model.layers.26.mlp.up_proj
| 0.108684
| 4,096
| 14,336
| 3.5
| 6.368245
| -16.239063
| 1.564809
| true
| 0.002818
|
dense
| -16.093494
| -1.103885
| -2.550006
| 64
| 0.078725
| 4,096
| 13
| 4,032
| 1
| 1.488883
| 0.002818
| 27.93321
|
success
| 0.053088
| 0.000001
|
under-trained
| 4,032
| 0.002818
| 0.001206
|
185
|
model.layers.26.self_attn.k_proj
| 0.034856
| 1,024
| 4,096
| 4
| 7.456504
| -22.91698
| 1.132999
| true
| 0.000844
|
dense
| -22.644402
| -1.587041
| -3.073421
| 64
| 0.02588
| 1,024
| 49
| 960
| 1
| 0.922358
| 0.000844
| 30.646473
|
success
| 0.02906
| 0.000001
|
under-trained
| 960
| 0.000844
| 0.000356
|
186
|
model.layers.26.self_attn.o_proj
| 0.167697
| 4,096
| 4,096
| 1
| 10.922671
| -31.43949
| 1.562381
| true
| 0.001323
|
dense
| -31.402265
| -1.469525
| -2.87837
| 64
| 0.033922
| 4,096
| 64
| 4,032
| 1
| 1.240334
| 0.001323
| 25.635735
|
success
| 0.036376
| 0
|
under-trained
| 4,032
| 0.001323
| 0.00047
|
187
|
model.layers.26.self_attn.q_proj
| 0.042271
| 4,096
| 4,096
| 1
| 7.985482
| -22.489588
| 1.560908
| true
| 0.001526
|
dense
| -22.486146
| -1.516497
| -2.816309
| 64
| 0.030444
| 4,096
| 64
| 4,032
| 1
| 0.873185
| 0.001526
| 19.943983
|
success
| 0.03907
| 0
|
under-trained
| 4,032
| 0.001526
| 0.000403
|
188
|
model.layers.26.self_attn.v_proj
| 0.058746
| 1,024
| 4,096
| 4
| 24.701824
| -81.647791
| 1.137018
| true
| 0.000495
|
dense
| -81.5235
| -1.607704
| -3.305335
| 64
| 0.024677
| 1,024
| 15
| 960
| 1
| 6.119785
| 0.000495
| 49.846031
|
success
| 0.02225
| 0.000001
|
under-trained
| 960
| 0.000495
| 0.000404
|
189
|
model.layers.27.mlp.down_proj
| 0.169859
| 4,096
| 14,336
| 3.5
| 19.350975
| -49.017357
| 1.565103
| true
| 0.00293
|
dense
| -49.017354
| -1.122905
| -2.533069
| 64
| 0.075352
| 4,096
| 64
| 4,032
| 1
| 2.293872
| 0.00293
| 25.71369
|
success
| 0.054133
| 0.000001
|
under-trained
| 4,032
| 0.00293
| 0.001103
|
190
|
model.layers.27.mlp.gate_proj
| 0.154579
| 4,096
| 14,336
| 3.5
| 4.657099
| -11.249424
| 1.562604
| true
| 0.003841
|
dense
| -11.058984
| -1.059703
| -2.415543
| 64
| 0.087156
| 4,096
| 7
| 4,032
| 1
| 1.382253
| 0.003841
| 22.690315
|
success
| 0.061977
| 0.000001
| 4,032
| 0.003841
| 0.001419
|
|
191
|
model.layers.27.mlp.up_proj
| 0.139529
| 4,096
| 14,336
| 3.5
| 5.798713
| -14.547875
| 1.563372
| true
| 0.003099
|
dense
| -14.383105
| -1.09817
| -2.508811
| 64
| 0.079768
| 4,096
| 14
| 4,032
| 1
| 1.28251
| 0.003099
| 25.741913
|
success
| 0.055667
| 0.000001
| 4,032
| 0.003099
| 0.001208
|
|
192
|
model.layers.27.self_attn.k_proj
| 0.053247
| 1,024
| 4,096
| 4
| 7.088601
| -20.734525
| 1.129563
| true
| 0.001188
|
dense
| -20.46086
| -1.529256
| -2.925052
| 64
| 0.029563
| 1,024
| 63
| 960
| 1
| 0.767092
| 0.001188
| 24.876902
|
success
| 0.034473
| 0.000001
|
under-trained
| 960
| 0.001188
| 0.000383
|
193
|
model.layers.27.self_attn.o_proj
| 0.101908
| 4,096
| 4,096
| 1
| 12.312543
| -37.227076
| 1.566002
| true
| 0.000947
|
dense
| -37.146804
| -1.485103
| -3.023508
| 64
| 0.032726
| 4,096
| 64
| 4,032
| 1
| 1.414068
| 0.000947
| 34.546589
|
success
| 0.030778
| 0
|
under-trained
| 4,032
| 0.000947
| 0.000464
|
194
|
model.layers.27.self_attn.q_proj
| 0.042044
| 4,096
| 4,096
| 1
| 7.92628
| -21.679954
| 1.559018
| true
| 0.00184
|
dense
| -21.678854
| -1.490915
| -2.735199
| 64
| 0.032291
| 4,096
| 64
| 4,032
| 1
| 0.865785
| 0.00184
| 17.550272
|
success
| 0.042894
| 0
|
under-trained
| 4,032
| 0.00184
| 0.000425
|
195
|
model.layers.27.self_attn.v_proj
| 0.063521
| 1,024
| 4,096
| 4
| 16.373393
| -53.042834
| 1.136855
| true
| 0.000576
|
dense
| -52.951057
| -1.590571
| -3.239575
| 64
| 0.02567
| 1,024
| 38
| 960
| 1
| 2.493894
| 0.000576
| 44.566044
|
success
| 0.024
| 0.000001
|
under-trained
| 960
| 0.000576
| 0.00039
|
196
|
model.layers.28.mlp.down_proj
| 0.17393
| 4,096
| 14,336
| 3.5
| 4.513984
| -11.095919
| 1.563425
| true
| 0.003482
|
dense
| -10.931005
| -1.115081
| -2.458121
| 64
| 0.076722
| 4,096
| 5
| 4,032
| 1
| 1.571502
| 0.003482
| 22.03126
|
success
| 0.059012
| 0.000001
| 4,032
| 0.003482
| 0.001234
|
|
197
|
model.layers.28.mlp.gate_proj
| 0.174762
| 4,096
| 14,336
| 3.5
| 12.366044
| -29.875316
| 1.561714
| true
| 0.003838
|
dense
| -29.865175
| -1.061048
| -2.415915
| 64
| 0.086886
| 4,096
| 64
| 4,032
| 1
| 1.420755
| 0.003838
| 22.639526
|
success
| 0.06195
| 0.000001
|
under-trained
| 4,032
| 0.003838
| 0.001217
|
198
|
model.layers.28.mlp.up_proj
| 0.132646
| 4,096
| 14,336
| 3.5
| 5.04215
| -12.611106
| 1.562622
| true
| 0.003154
|
dense
| -12.314449
| -1.088936
| -2.501137
| 64
| 0.081482
| 4,096
| 12
| 4,032
| 1
| 1.166868
| 0.003154
| 25.834534
|
success
| 0.056161
| 0.000001
| 4,032
| 0.003154
| 0.001248
|
|
199
|
model.layers.28.self_attn.k_proj
| 0.065966
| 1,024
| 4,096
| 4
| 7.460837
| -22.041873
| 1.131685
| true
| 0.001111
|
dense
| -21.921246
| -1.543238
| -2.954343
| 64
| 0.028626
| 1,024
| 64
| 960
| 1
| 0.807605
| 0.001111
| 25.769484
|
success
| 0.033329
| 0.000001
|
under-trained
| 960
| 0.001111
| 0.000376
|
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