layer_id
int64 0
223
| name
stringlengths 26
32
| D
float64 0.02
0.18
| M
int64 1.02k
4.1k
| N
int64 4.1k
14.3k
| Q
float64 1
4
| alpha
float64 3.57
40.4
| alpha_weighted
float64 -123.19
-7.38
| entropy
float64 1.1
1.57
| has_esd
bool 1
class | lambda_max
float32 0
0.01
| layer_type
stringclasses 1
value | log_alpha_norm
float64 -123.03
-6.97
| log_norm
float32 -1.93
-0.76
| log_spectral_norm
float32 -3.35
-2
| matrix_rank
int64 64
64
| norm
float32 0.01
0.17
| num_evals
int64 1.02k
4.1k
| num_pl_spikes
int64 7
64
| rank_loss
int64 960
4.03k
| rf
int64 1
1
| sigma
float64 0.59
11.9
| spectral_norm
float32 0
0.01
| stable_rank
float32 14
56.5
| status
stringclasses 1
value | sv_max
float64 0.02
0.1
| 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 | 0.070595 | 4,096 | 14,336 | 3.5 | 5.295959 | -11.124345 | 1.560849 | true | 0.007934 | dense | -11.020632 | -0.761963 | -2.100535 | 64 | 0.172996 | 4,096 | 17 | 4,032 | 1 | 1.041923 | 0.007934 | 21.805763 | success | 0.08907 | 0.000001 | 4,032 | 0.007934 | 0.002631 |
|
101 | model.layers.14.self_attn.k_proj | 0.108818 | 1,024 | 4,096 | 4 | 9.374769 | -27.164726 | 1.136578 | true | 0.001266 | dense | -26.117086 | -1.18827 | -2.897642 | 64 | 0.064823 | 1,024 | 60 | 960 | 1 | 1.081178 | 0.001266 | 51.21207 | success | 0.035578 | 0.000001 | under-trained | 960 | 0.001266 | 0.000903 |
102 | model.layers.14.self_attn.o_proj | 0.063818 | 4,096 | 4,096 | 1 | 10.309597 | -27.056012 | 1.565609 | true | 0.002375 | dense | -26.82605 | -1.075338 | -2.624352 | 64 | 0.084074 | 4,096 | 64 | 4,032 | 1 | 1.1637 | 0.002375 | 35.400898 | success | 0.048733 | 0 | under-trained | 4,032 | 0.002375 | 0.001168 |
103 | model.layers.14.self_attn.q_proj | 0.038597 | 4,096 | 4,096 | 1 | 10.648016 | -27.996992 | 1.566439 | true | 0.002348 | dense | -27.951509 | -1.095221 | -2.629315 | 64 | 0.080312 | 4,096 | 64 | 4,032 | 1 | 1.206002 | 0.002348 | 34.20536 | success | 0.048455 | 0 | under-trained | 4,032 | 0.002348 | 0.001123 |
104 | model.layers.14.self_attn.v_proj | 0.063967 | 1,024 | 4,096 | 4 | 18.977392 | -56.967035 | 1.136897 | true | 0.000996 | dense | -56.612306 | -1.303714 | -3.001837 | 64 | 0.049692 | 1,024 | 21 | 960 | 1 | 3.922989 | 0.000996 | 49.902519 | success | 0.031556 | 0.000001 | under-trained | 960 | 0.000996 | 0.000796 |
105 | model.layers.15.mlp.down_proj | 0.030025 | 4,096 | 14,336 | 3.5 | 19.888242 | -49.551639 | 1.567968 | true | 0.003225 | dense | -49.298357 | -0.794197 | -2.491504 | 64 | 0.160621 | 4,096 | 64 | 4,032 | 1 | 2.36103 | 0.003225 | 49.808956 | success | 0.056787 | 0.000001 | under-trained | 4,032 | 0.003225 | 0.002376 |
106 | model.layers.15.mlp.gate_proj | 0.068083 | 4,096 | 14,336 | 3.5 | 5.924201 | -12.518264 | 1.561087 | true | 0.007708 | dense | -12.462627 | -0.777118 | -2.113072 | 64 | 0.167064 | 4,096 | 22 | 4,032 | 1 | 1.049843 | 0.007708 | 21.674715 | success | 0.087794 | 0.000001 | 4,032 | 0.007708 | 0.002473 |
|
107 | model.layers.15.mlp.up_proj | 0.079643 | 4,096 | 14,336 | 3.5 | 5.669253 | -12.220102 | 1.562827 | true | 0.00699 | dense | -12.101856 | -0.76957 | -2.155505 | 64 | 0.169992 | 4,096 | 12 | 4,032 | 1 | 1.347897 | 0.00699 | 24.318357 | success | 0.083608 | 0.000001 | 4,032 | 0.00699 | 0.002777 |
|
108 | model.layers.15.self_attn.k_proj | 0.101475 | 1,024 | 4,096 | 4 | 10.378981 | -29.608627 | 1.136357 | true | 0.001404 | dense | -28.722908 | -1.157424 | -2.852749 | 64 | 0.069595 | 1,024 | 42 | 960 | 1 | 1.447208 | 0.001404 | 49.582108 | success | 0.037465 | 0.000001 | under-trained | 960 | 0.001404 | 0.001026 |
109 | model.layers.15.self_attn.o_proj | 0.058208 | 4,096 | 4,096 | 1 | 22.957791 | -64.240785 | 1.567953 | true | 0.001591 | dense | -64.025073 | -1.092063 | -2.798213 | 64 | 0.080898 | 4,096 | 18 | 4,032 | 1 | 5.175501 | 0.001591 | 50.83342 | success | 0.039893 | 0 | under-trained | 4,032 | 0.001591 | 0.0013 |
110 | model.layers.15.self_attn.q_proj | 0.058694 | 4,096 | 4,096 | 1 | 13.271464 | -35.264829 | 1.567114 | true | 0.002202 | dense | -35.242807 | -1.089259 | -2.657192 | 64 | 0.081422 | 4,096 | 46 | 4,032 | 1 | 1.809329 | 0.002202 | 36.977089 | success | 0.046925 | 0 | under-trained | 4,032 | 0.002202 | 0.001202 |
111 | model.layers.15.self_attn.v_proj | 0.11419 | 1,024 | 4,096 | 4 | 22.354517 | -68.653411 | 1.137139 | true | 0.000849 | dense | -67.828455 | -1.325262 | -3.07112 | 64 | 0.047287 | 1,024 | 26 | 960 | 1 | 4.187965 | 0.000849 | 55.700417 | success | 0.029137 | 0.000001 | under-trained | 960 | 0.000849 | 0.000747 |
112 | model.layers.16.mlp.down_proj | 0.064003 | 4,096 | 14,336 | 3.5 | 18.423216 | -44.586561 | 1.567581 | true | 0.003801 | dense | -44.537154 | -0.789763 | -2.420129 | 64 | 0.162269 | 4,096 | 64 | 4,032 | 1 | 2.177902 | 0.003801 | 42.693913 | success | 0.06165 | 0.000001 | under-trained | 4,032 | 0.003801 | 0.002387 |
113 | model.layers.16.mlp.gate_proj | 0.095854 | 4,096 | 14,336 | 3.5 | 6.133836 | -12.7012 | 1.56011 | true | 0.008498 | dense | -12.670542 | -0.765247 | -2.070678 | 64 | 0.171693 | 4,096 | 25 | 4,032 | 1 | 1.026767 | 0.008498 | 20.203686 | success | 0.092185 | 0.000001 | under-trained | 4,032 | 0.008498 | 0.002498 |
114 | model.layers.16.mlp.up_proj | 0.09054 | 4,096 | 14,336 | 3.5 | 6.53151 | -13.916047 | 1.562146 | true | 0.007403 | dense | -13.871134 | -0.768526 | -2.130602 | 64 | 0.170402 | 4,096 | 24 | 4,032 | 1 | 1.129115 | 0.007403 | 23.018433 | success | 0.08604 | 0.000001 | under-trained | 4,032 | 0.007403 | 0.002511 |
115 | model.layers.16.self_attn.k_proj | 0.115521 | 1,024 | 4,096 | 4 | 9.912147 | -28.712586 | 1.136763 | true | 0.001269 | dense | -27.50179 | -1.163768 | -2.896707 | 64 | 0.068585 | 1,024 | 60 | 960 | 1 | 1.150553 | 0.001269 | 54.067829 | success | 0.035616 | 0.000001 | under-trained | 960 | 0.001269 | 0.000962 |
116 | model.layers.16.self_attn.o_proj | 0.054619 | 4,096 | 4,096 | 1 | 21.033314 | -58.536135 | 1.567931 | true | 0.001648 | dense | -58.320719 | -1.082587 | -2.78302 | 64 | 0.082682 | 4,096 | 26 | 4,032 | 1 | 3.928856 | 0.001648 | 50.168678 | success | 0.040597 | 0 | under-trained | 4,032 | 0.001648 | 0.001299 |
117 | model.layers.16.self_attn.q_proj | 0.045936 | 4,096 | 4,096 | 1 | 13.197938 | -34.586 | 1.56682 | true | 0.002396 | dense | -34.576094 | -1.080902 | -2.620561 | 64 | 0.083004 | 4,096 | 41 | 4,032 | 1 | 1.904998 | 0.002396 | 34.646488 | success | 0.048946 | 0 | under-trained | 4,032 | 0.002396 | 0.001237 |
118 | model.layers.16.self_attn.v_proj | 0.078067 | 1,024 | 4,096 | 4 | 40.403046 | -123.190286 | 1.137152 | true | 0.000893 | dense | -123.031911 | -1.316324 | -3.049035 | 64 | 0.04827 | 1,024 | 11 | 960 | 1 | 11.880465 | 0.000893 | 54.039471 | success | 0.029887 | 0.000001 | under-trained | 960 | 0.000893 | 0.000805 |
119 | model.layers.17.mlp.down_proj | 0.06046 | 4,096 | 14,336 | 3.5 | 17.860272 | -43.56073 | 1.567649 | true | 0.003639 | dense | -43.471237 | -0.794595 | -2.438973 | 64 | 0.160474 | 4,096 | 64 | 4,032 | 1 | 2.107534 | 0.003639 | 44.093876 | success | 0.060327 | 0.000001 | under-trained | 4,032 | 0.003639 | 0.002356 |
120 | model.layers.17.mlp.gate_proj | 0.082128 | 4,096 | 14,336 | 3.5 | 5.495079 | -11.656814 | 1.561849 | true | 0.007563 | dense | -11.56735 | -0.772201 | -2.121319 | 64 | 0.168966 | 4,096 | 13 | 4,032 | 1 | 1.246711 | 0.007563 | 22.341782 | success | 0.086964 | 0.000001 | 4,032 | 0.007563 | 0.0027 |
|
121 | model.layers.17.mlp.up_proj | 0.063486 | 4,096 | 14,336 | 3.5 | 6.23721 | -13.59188 | 1.563557 | true | 0.00662 | dense | -13.499983 | -0.775867 | -2.17916 | 64 | 0.167545 | 4,096 | 14 | 4,032 | 1 | 1.399703 | 0.00662 | 25.310049 | success | 0.081362 | 0.000001 | under-trained | 4,032 | 0.00662 | 0.002663 |
122 | model.layers.17.self_attn.k_proj | 0.05194 | 1,024 | 4,096 | 4 | 13.234445 | -38.008686 | 1.136307 | true | 0.001343 | dense | -37.564366 | -1.20944 | -2.871952 | 64 | 0.061739 | 1,024 | 21 | 960 | 1 | 2.669775 | 0.001343 | 45.973885 | success | 0.036646 | 0.000001 | under-trained | 960 | 0.001343 | 0.000991 |
123 | model.layers.17.self_attn.o_proj | 0.033461 | 4,096 | 4,096 | 1 | 14.530256 | -40.348406 | 1.567569 | true | 0.001672 | dense | -39.98802 | -1.106861 | -2.776855 | 64 | 0.078188 | 4,096 | 37 | 4,032 | 1 | 2.22436 | 0.001672 | 46.772816 | success | 0.040886 | 0 | under-trained | 4,032 | 0.001672 | 0.001184 |
124 | model.layers.17.self_attn.q_proj | 0.034492 | 4,096 | 4,096 | 1 | 11.908328 | -31.226268 | 1.566418 | true | 0.002387 | dense | -31.21486 | -1.107816 | -2.622221 | 64 | 0.078016 | 4,096 | 47 | 4,032 | 1 | 1.591143 | 0.002387 | 32.689209 | success | 0.048853 | 0 | under-trained | 4,032 | 0.002387 | 0.001138 |
125 | model.layers.17.self_attn.v_proj | 0.090111 | 1,024 | 4,096 | 4 | 25.721496 | -78.962157 | 1.137121 | true | 0.000851 | dense | -78.326813 | -1.329413 | -3.06989 | 64 | 0.046837 | 1,024 | 21 | 960 | 1 | 5.394673 | 0.000851 | 55.01442 | success | 0.029178 | 0.000001 | under-trained | 960 | 0.000851 | 0.000753 |
126 | model.layers.18.mlp.down_proj | 0.035721 | 4,096 | 14,336 | 3.5 | 20.031384 | -49.405232 | 1.567859 | true | 0.003417 | dense | -49.336911 | -0.806355 | -2.466391 | 64 | 0.156187 | 4,096 | 64 | 4,032 | 1 | 2.378923 | 0.003417 | 45.712662 | success | 0.058453 | 0.000001 | under-trained | 4,032 | 0.003417 | 0.002311 |
127 | model.layers.18.mlp.gate_proj | 0.063541 | 4,096 | 14,336 | 3.5 | 5.057453 | -10.494784 | 1.559962 | true | 0.008412 | dense | -10.422957 | -0.782374 | -2.075113 | 64 | 0.165054 | 4,096 | 14 | 4,032 | 1 | 1.0844 | 0.008412 | 19.621803 | success | 0.091716 | 0.000001 | 4,032 | 0.008412 | 0.00255 |
|
128 | model.layers.18.mlp.up_proj | 0.063435 | 4,096 | 14,336 | 3.5 | 5.346702 | -11.310891 | 1.561263 | true | 0.007665 | dense | -11.227929 | -0.787416 | -2.115489 | 64 | 0.163149 | 4,096 | 14 | 4,032 | 1 | 1.161705 | 0.007665 | 21.284979 | success | 0.08755 | 0.000001 | 4,032 | 0.007665 | 0.002524 |
|
129 | model.layers.18.self_attn.k_proj | 0.113236 | 1,024 | 4,096 | 4 | 7.800461 | -22.423279 | 1.136252 | true | 0.001335 | dense | -21.267073 | -1.168217 | -2.874609 | 64 | 0.067887 | 1,024 | 62 | 960 | 1 | 0.863659 | 0.001335 | 50.861946 | success | 0.036534 | 0.000001 | under-trained | 960 | 0.001335 | 0.000915 |
130 | model.layers.18.self_attn.o_proj | 0.073369 | 4,096 | 4,096 | 1 | 11.414136 | -29.839959 | 1.565693 | true | 0.002431 | dense | -29.820689 | -1.120096 | -2.614299 | 64 | 0.075841 | 4,096 | 64 | 4,032 | 1 | 1.301767 | 0.002431 | 31.203423 | success | 0.0493 | 0 | under-trained | 4,032 | 0.002431 | 0.001066 |
131 | model.layers.18.self_attn.q_proj | 0.053146 | 4,096 | 4,096 | 1 | 12.021277 | -31.476889 | 1.566602 | true | 0.002408 | dense | -31.460674 | -1.089056 | -2.618431 | 64 | 0.08146 | 4,096 | 48 | 4,032 | 1 | 1.590784 | 0.002408 | 33.835728 | success | 0.049066 | 0 | under-trained | 4,032 | 0.002408 | 0.001188 |
132 | model.layers.18.self_attn.v_proj | 0.074868 | 1,024 | 4,096 | 4 | 31.943612 | -97.858903 | 1.137107 | true | 0.000864 | dense | -97.507446 | -1.330271 | -3.063489 | 64 | 0.046744 | 1,024 | 12 | 960 | 1 | 8.932651 | 0.000864 | 54.102608 | success | 0.029394 | 0.000001 | under-trained | 960 | 0.000864 | 0.000776 |
133 | model.layers.19.mlp.down_proj | 0.052651 | 4,096 | 14,336 | 3.5 | 23.80037 | -59.519345 | 1.568035 | true | 0.003157 | dense | -59.475479 | -0.821488 | -2.500774 | 64 | 0.150839 | 4,096 | 63 | 4,032 | 1 | 2.872577 | 0.003157 | 47.78442 | success | 0.056184 | 0.000001 | under-trained | 4,032 | 0.003157 | 0.002254 |
134 | model.layers.19.mlp.gate_proj | 0.074004 | 4,096 | 14,336 | 3.5 | 5.484326 | -11.727247 | 1.561759 | true | 0.007272 | dense | -11.654583 | -0.803156 | -2.13832 | 64 | 0.157342 | 4,096 | 14 | 4,032 | 1 | 1.198487 | 0.007272 | 21.635359 | success | 0.085279 | 0.000001 | 4,032 | 0.007272 | 0.002451 |
|
135 | model.layers.19.mlp.up_proj | 0.081407 | 4,096 | 14,336 | 3.5 | 5.57579 | -12.189419 | 1.563044 | true | 0.006514 | dense | -12.085657 | -0.812214 | -2.186133 | 64 | 0.154094 | 4,096 | 11 | 4,032 | 1 | 1.379653 | 0.006514 | 23.654802 | success | 0.080711 | 0.000001 | 4,032 | 0.006514 | 0.002491 |
|
136 | model.layers.19.self_attn.k_proj | 0.103896 | 1,024 | 4,096 | 4 | 9.422241 | -27.63405 | 1.136375 | true | 0.001167 | dense | -26.58249 | -1.22558 | -2.932853 | 64 | 0.059487 | 1,024 | 50 | 960 | 1 | 1.191085 | 0.001167 | 50.965183 | success | 0.034164 | 0.000001 | under-trained | 960 | 0.001167 | 0.000849 |
137 | model.layers.19.self_attn.o_proj | 0.044688 | 4,096 | 4,096 | 1 | 21.054933 | -59.327508 | 1.567926 | true | 0.001521 | dense | -59.104358 | -1.11806 | -2.817749 | 64 | 0.076197 | 4,096 | 23 | 4,032 | 1 | 4.181743 | 0.001521 | 50.082825 | success | 0.039005 | 0 | under-trained | 4,032 | 0.001521 | 0.001205 |
138 | model.layers.19.self_attn.q_proj | 0.043086 | 4,096 | 4,096 | 1 | 13.007356 | -34.852457 | 1.566701 | true | 0.002092 | dense | -34.840439 | -1.140514 | -2.679442 | 64 | 0.072358 | 4,096 | 32 | 4,032 | 1 | 2.122621 | 0.002092 | 34.588226 | success | 0.045738 | 0 | under-trained | 4,032 | 0.002092 | 0.001104 |
139 | model.layers.19.self_attn.v_proj | 0.085536 | 1,024 | 4,096 | 4 | 32.112979 | -97.924641 | 1.137149 | true | 0.000893 | dense | -97.656135 | -1.317667 | -3.049379 | 64 | 0.048121 | 1,024 | 17 | 960 | 1 | 7.546006 | 0.000893 | 53.915321 | success | 0.029875 | 0.000001 | under-trained | 960 | 0.000893 | 0.000785 |
140 | model.layers.20.mlp.down_proj | 0.06154 | 4,096 | 14,336 | 3.5 | 25.728871 | -64.630048 | 1.568064 | true | 0.003076 | dense | -64.612966 | -0.836834 | -2.511966 | 64 | 0.145602 | 4,096 | 63 | 4,032 | 1 | 3.115545 | 0.003076 | 47.329498 | success | 0.055465 | 0.000001 | under-trained | 4,032 | 0.003076 | 0.002184 |
141 | model.layers.20.mlp.gate_proj | 0.07428 | 4,096 | 14,336 | 3.5 | 5.7562 | -12.622673 | 1.56318 | true | 0.006414 | dense | -12.538929 | -0.821344 | -2.192883 | 64 | 0.150888 | 4,096 | 12 | 4,032 | 1 | 1.372997 | 0.006414 | 23.525513 | success | 0.080086 | 0.000001 | 4,032 | 0.006414 | 0.002385 |
|
142 | model.layers.20.mlp.up_proj | 0.067795 | 4,096 | 14,336 | 3.5 | 6.416853 | -14.515735 | 1.564549 | true | 0.005469 | dense | -14.415343 | -0.835165 | -2.262127 | 64 | 0.146162 | 4,096 | 13 | 4,032 | 1 | 1.502365 | 0.005469 | 26.727709 | success | 0.07395 | 0.000001 | under-trained | 4,032 | 0.005469 | 0.002298 |
143 | model.layers.20.self_attn.k_proj | 0.084596 | 1,024 | 4,096 | 4 | 16.050775 | -47.779777 | 1.136508 | true | 0.001055 | dense | -47.116229 | -1.274841 | -2.976789 | 64 | 0.053108 | 1,024 | 16 | 960 | 1 | 3.762694 | 0.001055 | 50.344112 | success | 0.032479 | 0.000001 | under-trained | 960 | 0.001055 | 0.00088 |
144 | model.layers.20.self_attn.o_proj | 0.095816 | 4,096 | 4,096 | 1 | 35.030403 | -101.934399 | 1.568151 | true | 0.001231 | dense | -101.410505 | -1.157785 | -2.909884 | 64 | 0.069537 | 4,096 | 16 | 4,032 | 1 | 8.507601 | 0.001231 | 56.506565 | success | 0.03508 | 0 | under-trained | 4,032 | 0.001231 | 0.001121 |
145 | model.layers.20.self_attn.q_proj | 0.043583 | 4,096 | 4,096 | 1 | 11.930345 | -32.120584 | 1.566411 | true | 0.002031 | dense | -32.11039 | -1.180249 | -2.692343 | 64 | 0.066032 | 4,096 | 39 | 4,032 | 1 | 1.750256 | 0.002031 | 32.515812 | success | 0.045064 | 0 | under-trained | 4,032 | 0.002031 | 0.000981 |
146 | model.layers.20.self_attn.v_proj | 0.113966 | 1,024 | 4,096 | 4 | 14.136786 | -43.462944 | 1.137104 | true | 0.000842 | dense | -42.349018 | -1.328369 | -3.074457 | 64 | 0.04695 | 1,024 | 53 | 960 | 1 | 1.804476 | 0.000842 | 55.729904 | success | 0.029025 | 0.000001 | under-trained | 960 | 0.000842 | 0.00069 |
147 | model.layers.21.mlp.down_proj | 0.069908 | 4,096 | 14,336 | 3.5 | 25.507698 | -64.295016 | 1.568023 | true | 0.003016 | dense | -64.282851 | -0.853733 | -2.520612 | 64 | 0.140045 | 4,096 | 61 | 4,032 | 1 | 3.137889 | 0.003016 | 46.438583 | success | 0.054915 | 0.000001 | under-trained | 4,032 | 0.003016 | 0.002102 |
148 | model.layers.21.mlp.gate_proj | 0.108281 | 4,096 | 14,336 | 3.5 | 5.774525 | -12.953684 | 1.564314 | true | 0.005712 | dense | -12.833288 | -0.836879 | -2.243247 | 64 | 0.145587 | 4,096 | 8 | 4,032 | 1 | 1.688049 | 0.005712 | 25.489885 | success | 0.075575 | 0.000001 | 4,032 | 0.005712 | 0.002424 |
|
149 | model.layers.21.mlp.up_proj | 0.093581 | 4,096 | 14,336 | 3.5 | 6.776335 | -15.681946 | 1.565386 | true | 0.00485 | dense | -15.571955 | -0.857898 | -2.314222 | 64 | 0.138708 | 4,096 | 11 | 4,032 | 1 | 1.741631 | 0.00485 | 28.597256 | success | 0.069645 | 0.000001 | under-trained | 4,032 | 0.00485 | 0.002209 |
150 | model.layers.21.self_attn.k_proj | 0.059948 | 1,024 | 4,096 | 4 | 11.910162 | -35.071107 | 1.136015 | true | 0.001136 | dense | -34.693005 | -1.302377 | -2.944637 | 64 | 0.049845 | 1,024 | 22 | 960 | 1 | 2.326054 | 0.001136 | 43.879395 | success | 0.033704 | 0.000001 | under-trained | 960 | 0.001136 | 0.000798 |
151 | model.layers.21.self_attn.o_proj | 0.074732 | 4,096 | 4,096 | 1 | 36.651508 | -107.643644 | 1.568171 | true | 0.001156 | dense | -107.320781 | -1.191226 | -2.93695 | 64 | 0.064383 | 4,096 | 13 | 4,032 | 1 | 9.887949 | 0.001156 | 55.683193 | success | 0.034004 | 0 | under-trained | 4,032 | 0.001156 | 0.001042 |
152 | model.layers.21.self_attn.q_proj | 0.047363 | 4,096 | 4,096 | 1 | 11.346615 | -30.906445 | 1.566245 | true | 0.001889 | dense | -30.892907 | -1.217366 | -2.723847 | 64 | 0.060623 | 4,096 | 46 | 4,032 | 1 | 1.525525 | 0.001889 | 32.098225 | success | 0.043459 | 0 | under-trained | 4,032 | 0.001889 | 0.000883 |
153 | model.layers.21.self_attn.v_proj | 0.113763 | 1,024 | 4,096 | 4 | 14.337243 | -44.625051 | 1.137172 | true | 0.000772 | dense | -43.490099 | -1.362799 | -3.112527 | 64 | 0.043371 | 1,024 | 56 | 960 | 1 | 1.782264 | 0.000772 | 56.198883 | success | 0.02778 | 0.000001 | under-trained | 960 | 0.000772 | 0.000635 |
154 | model.layers.22.mlp.down_proj | 0.066965 | 4,096 | 14,336 | 3.5 | 26.614543 | -68.025058 | 1.568099 | true | 0.00278 | dense | -67.988984 | -0.866974 | -2.555936 | 64 | 0.13584 | 4,096 | 62 | 4,032 | 1 | 3.25305 | 0.00278 | 48.86095 | success | 0.052727 | 0.000001 | under-trained | 4,032 | 0.00278 | 0.002042 |
155 | model.layers.22.mlp.gate_proj | 0.097833 | 4,096 | 14,336 | 3.5 | 6.001974 | -13.491658 | 1.564459 | true | 0.005651 | dense | -13.385668 | -0.836949 | -2.24787 | 64 | 0.145563 | 4,096 | 9 | 4,032 | 1 | 1.667325 | 0.005651 | 25.758545 | success | 0.075174 | 0.000001 | under-trained | 4,032 | 0.005651 | 0.002382 |
156 | model.layers.22.mlp.up_proj | 0.08121 | 4,096 | 14,336 | 3.5 | 6.807247 | -15.786899 | 1.565366 | true | 0.004796 | dense | -15.680063 | -0.863387 | -2.319131 | 64 | 0.136966 | 4,096 | 11 | 4,032 | 1 | 1.750951 | 0.004796 | 28.55909 | success | 0.069252 | 0.000001 | under-trained | 4,032 | 0.004796 | 0.00219 |
157 | model.layers.22.self_attn.k_proj | 0.101224 | 1,024 | 4,096 | 4 | 6.56137 | -19.691763 | 1.135512 | true | 0.000997 | dense | -18.594873 | -1.324471 | -3.001166 | 64 | 0.047373 | 1,024 | 64 | 960 | 1 | 0.695171 | 0.000997 | 47.500237 | success | 0.03158 | 0.000001 | under-trained | 960 | 0.000997 | 0.000613 |
158 | model.layers.22.self_attn.o_proj | 0.064047 | 4,096 | 4,096 | 1 | 14.630623 | -41.505533 | 1.567305 | true | 0.001456 | dense | -41.424312 | -1.22554 | -2.836895 | 64 | 0.059492 | 4,096 | 63 | 4,032 | 1 | 1.717297 | 0.001456 | 40.865242 | success | 0.038155 | 0 | under-trained | 4,032 | 0.001456 | 0.000861 |
159 | model.layers.22.self_attn.q_proj | 0.03411 | 4,096 | 4,096 | 1 | 9.809994 | -26.862289 | 1.565564 | true | 0.001827 | dense | -26.838374 | -1.255902 | -2.738257 | 64 | 0.055475 | 4,096 | 42 | 4,032 | 1 | 1.359412 | 0.001827 | 30.363724 | success | 0.042744 | 0 | under-trained | 4,032 | 0.001827 | 0.000807 |
160 | model.layers.22.self_attn.v_proj | 0.054654 | 1,024 | 4,096 | 4 | 21.498415 | -66.059842 | 1.136995 | true | 0.000846 | dense | -65.872133 | -1.378539 | -3.072777 | 64 | 0.041827 | 1,024 | 20 | 960 | 1 | 4.583585 | 0.000846 | 49.458221 | success | 0.029081 | 0.000001 | under-trained | 960 | 0.000846 | 0.000671 |
161 | model.layers.23.mlp.down_proj | 0.062324 | 4,096 | 14,336 | 3.5 | 27.278771 | -70.935617 | 1.568166 | true | 0.00251 | dense | -70.675347 | -0.879847 | -2.600396 | 64 | 0.131872 | 4,096 | 63 | 4,032 | 1 | 3.310814 | 0.00251 | 52.547184 | success | 0.050096 | 0.000001 | under-trained | 4,032 | 0.00251 | 0.001983 |
162 | model.layers.23.mlp.gate_proj | 0.102704 | 4,096 | 14,336 | 3.5 | 6.167049 | -13.731182 | 1.564025 | true | 0.005936 | dense | -13.667456 | -0.841866 | -2.22654 | 64 | 0.143924 | 4,096 | 9 | 4,032 | 1 | 1.72235 | 0.005936 | 24.247877 | success | 0.077042 | 0.000001 | under-trained | 4,032 | 0.005936 | 0.002354 |
163 | model.layers.23.mlp.up_proj | 0.072697 | 4,096 | 14,336 | 3.5 | 7.470926 | -17.248557 | 1.565169 | true | 0.004912 | dense | -17.20196 | -0.8729 | -2.308758 | 64 | 0.133998 | 4,096 | 13 | 4,032 | 1 | 1.794712 | 0.004912 | 27.280809 | success | 0.070084 | 0.000001 | under-trained | 4,032 | 0.004912 | 0.00211 |
164 | model.layers.23.self_attn.k_proj | 0.050034 | 1,024 | 4,096 | 4 | 9.433142 | -28.276416 | 1.135838 | true | 0.001006 | dense | -27.622812 | -1.349703 | -2.997561 | 64 | 0.044699 | 1,024 | 48 | 960 | 1 | 1.217219 | 0.001006 | 44.448589 | success | 0.031712 | 0.000001 | under-trained | 960 | 0.001006 | 0.000639 |
165 | model.layers.23.self_attn.o_proj | 0.073546 | 4,096 | 4,096 | 1 | 5.384058 | -14.183412 | 1.56385 | true | 0.002321 | dense | -13.935122 | -1.200379 | -2.634335 | 64 | 0.063041 | 4,096 | 12 | 4,032 | 1 | 1.265568 | 0.002321 | 27.161652 | success | 0.048176 | 0 | 4,032 | 0.002321 | 0.00099 |
|
166 | model.layers.23.self_attn.q_proj | 0.026508 | 4,096 | 4,096 | 1 | 10.00856 | -27.863208 | 1.565898 | true | 0.001645 | dense | -27.811764 | -1.269355 | -2.783938 | 64 | 0.053783 | 4,096 | 49 | 4,032 | 1 | 1.286937 | 0.001645 | 32.702648 | success | 0.040554 | 0 | under-trained | 4,032 | 0.001645 | 0.000769 |
167 | model.layers.23.self_attn.v_proj | 0.066253 | 1,024 | 4,096 | 4 | 17.725424 | -54.425669 | 1.136923 | true | 0.00085 | dense | -53.875092 | -1.360398 | -3.070486 | 64 | 0.043612 | 1,024 | 26 | 960 | 1 | 3.280126 | 0.00085 | 51.296551 | success | 0.029158 | 0.000001 | under-trained | 960 | 0.00085 | 0.000687 |
168 | model.layers.24.mlp.down_proj | 0.088589 | 4,096 | 14,336 | 3.5 | 25.547802 | -65.549568 | 1.568011 | true | 0.002718 | dense | -65.519276 | -0.893975 | -2.565762 | 64 | 0.127651 | 4,096 | 63 | 4,032 | 1 | 3.092732 | 0.002718 | 46.966293 | success | 0.052134 | 0.000001 | under-trained | 4,032 | 0.002718 | 0.001913 |
169 | model.layers.24.mlp.gate_proj | 0.116326 | 4,096 | 14,336 | 3.5 | 5.891471 | -13.039916 | 1.563655 | true | 0.006119 | dense | -12.980163 | -0.84982 | -2.213355 | 64 | 0.141312 | 4,096 | 8 | 4,032 | 1 | 1.729396 | 0.006119 | 23.09589 | success | 0.078221 | 0.000001 | 4,032 | 0.006119 | 0.002318 |
|
170 | model.layers.24.mlp.up_proj | 0.084695 | 4,096 | 14,336 | 3.5 | 7.723819 | -17.807934 | 1.564945 | true | 0.004948 | dense | -17.779779 | -0.88595 | -2.305587 | 64 | 0.130032 | 4,096 | 14 | 4,032 | 1 | 1.797016 | 0.004948 | 26.280695 | success | 0.070341 | 0.000001 | under-trained | 4,032 | 0.004948 | 0.002026 |
171 | model.layers.24.self_attn.k_proj | 0.042094 | 1,024 | 4,096 | 4 | 9.26434 | -27.923382 | 1.135516 | true | 0.000968 | dense | -27.431276 | -1.393554 | -3.014071 | 64 | 0.040406 | 1,024 | 40 | 960 | 1 | 1.306707 | 0.000968 | 41.736637 | success | 0.031115 | 0.000001 | under-trained | 960 | 0.000968 | 0.000592 |
172 | model.layers.24.self_attn.o_proj | 0.063429 | 4,096 | 4,096 | 1 | 18.543035 | -53.72646 | 1.567791 | true | 0.001267 | dense | -53.706925 | -1.265283 | -2.897393 | 64 | 0.05429 | 4,096 | 58 | 4,032 | 1 | 2.303513 | 0.001267 | 42.865685 | success | 0.035588 | 0 | under-trained | 4,032 | 0.001267 | 0.000804 |
173 | model.layers.24.self_attn.q_proj | 0.03856 | 4,096 | 4,096 | 1 | 10.280278 | -28.986392 | 1.565957 | true | 0.001515 | dense | -28.963955 | -1.323311 | -2.819612 | 64 | 0.0475 | 4,096 | 49 | 4,032 | 1 | 1.325754 | 0.001515 | 31.354559 | success | 0.038922 | 0 | under-trained | 4,032 | 0.001515 | 0.000681 |
174 | model.layers.24.self_attn.v_proj | 0.059587 | 1,024 | 4,096 | 4 | 26.995273 | -83.393638 | 1.137081 | true | 0.000814 | dense | -83.276914 | -1.383491 | -3.089194 | 64 | 0.041353 | 1,024 | 16 | 960 | 1 | 6.498818 | 0.000814 | 50.781246 | success | 0.028537 | 0.000001 | under-trained | 960 | 0.000814 | 0.000675 |
175 | model.layers.25.mlp.down_proj | 0.088452 | 4,096 | 14,336 | 3.5 | 22.674786 | -57.540608 | 1.567786 | true | 0.0029 | dense | -57.530036 | -0.90192 | -2.537647 | 64 | 0.125337 | 4,096 | 64 | 4,032 | 1 | 2.709348 | 0.0029 | 43.224232 | success | 0.053849 | 0.000001 | under-trained | 4,032 | 0.0029 | 0.001866 |
176 | model.layers.25.mlp.gate_proj | 0.115405 | 4,096 | 14,336 | 3.5 | 7.173909 | -15.938461 | 1.563881 | true | 0.006002 | dense | -15.919066 | -0.851489 | -2.221726 | 64 | 0.14077 | 4,096 | 12 | 4,032 | 1 | 1.782254 | 0.006002 | 23.455097 | success | 0.077471 | 0.000001 | under-trained | 4,032 | 0.006002 | 0.002222 |
177 | model.layers.25.mlp.up_proj | 0.117501 | 4,096 | 14,336 | 3.5 | 7.724192 | -17.831249 | 1.564917 | true | 0.004915 | dense | -17.805651 | -0.893028 | -2.308494 | 64 | 0.12793 | 4,096 | 13 | 4,032 | 1 | 1.864955 | 0.004915 | 26.029451 | success | 0.070106 | 0.000001 | under-trained | 4,032 | 0.004915 | 0.002006 |
178 | model.layers.25.self_attn.k_proj | 0.102301 | 1,024 | 4,096 | 4 | 7.238527 | -22.14815 | 1.135898 | true | 0.000871 | dense | -21.109452 | -1.379533 | -3.059759 | 64 | 0.041732 | 1,024 | 62 | 960 | 1 | 0.792294 | 0.000871 | 47.887905 | success | 0.02952 | 0.000001 | under-trained | 960 | 0.000871 | 0.000555 |
179 | model.layers.25.self_attn.o_proj | 0.072905 | 4,096 | 4,096 | 1 | 15.151347 | -43.711322 | 1.567377 | true | 0.001303 | dense | -43.662192 | -1.280084 | -2.884979 | 64 | 0.052471 | 4,096 | 63 | 4,032 | 1 | 1.782902 | 0.001303 | 40.262028 | success | 0.0361 | 0 | under-trained | 4,032 | 0.001303 | 0.000762 |
180 | model.layers.25.self_attn.q_proj | 0.024015 | 4,096 | 4,096 | 1 | 10.113745 | -28.551966 | 1.565922 | true | 0.001503 | dense | -28.520994 | -1.319469 | -2.823085 | 64 | 0.047922 | 4,096 | 40 | 4,032 | 1 | 1.44101 | 0.001503 | 31.887217 | success | 0.038767 | 0 | under-trained | 4,032 | 0.001503 | 0.000703 |
181 | model.layers.25.self_attn.v_proj | 0.050871 | 1,024 | 4,096 | 4 | 22.102889 | -67.771573 | 1.13697 | true | 0.000859 | dense | -67.671703 | -1.382476 | -3.066186 | 64 | 0.04145 | 1,024 | 20 | 960 | 1 | 4.718749 | 0.000859 | 48.273659 | success | 0.029303 | 0.000001 | under-trained | 960 | 0.000859 | 0.000666 |
182 | model.layers.26.mlp.down_proj | 0.099921 | 4,096 | 14,336 | 3.5 | 21.817002 | -54.155571 | 1.567389 | true | 0.003294 | dense | -54.155059 | -0.910668 | -2.482265 | 64 | 0.122838 | 4,096 | 64 | 4,032 | 1 | 2.602125 | 0.003294 | 37.290382 | success | 0.057394 | 0.000001 | under-trained | 4,032 | 0.003294 | 0.001823 |
183 | model.layers.26.mlp.gate_proj | 0.08999 | 4,096 | 14,336 | 3.5 | 6.457537 | -14.237801 | 1.563379 | true | 0.00624 | dense | -14.209257 | -0.85408 | -2.204835 | 64 | 0.139933 | 4,096 | 11 | 4,032 | 1 | 1.645509 | 0.00624 | 22.426134 | success | 0.078992 | 0.000001 | under-trained | 4,032 | 0.00624 | 0.002202 |
184 | model.layers.26.mlp.up_proj | 0.100135 | 4,096 | 14,336 | 3.5 | 6.472845 | -14.783802 | 1.564256 | true | 0.0052 | dense | -14.732363 | -0.893702 | -2.283973 | 64 | 0.127732 | 4,096 | 11 | 4,032 | 1 | 1.650125 | 0.0052 | 24.562418 | success | 0.072113 | 0.000001 | under-trained | 4,032 | 0.0052 | 0.002022 |
185 | model.layers.26.self_attn.k_proj | 0.030124 | 1,024 | 4,096 | 4 | 8.838954 | -26.360515 | 1.135024 | true | 0.001042 | dense | -26.077297 | -1.411301 | -2.982311 | 64 | 0.038788 | 1,024 | 34 | 960 | 1 | 1.34437 | 0.001042 | 37.240086 | success | 0.032273 | 0.000001 | under-trained | 960 | 0.001042 | 0.000578 |
186 | model.layers.26.self_attn.o_proj | 0.080145 | 4,096 | 4,096 | 1 | 4.237009 | -11.025414 | 1.560244 | true | 0.002499 | dense | -10.726383 | -1.24904 | -2.602169 | 64 | 0.056359 | 4,096 | 12 | 4,032 | 1 | 0.934444 | 0.002499 | 22.549124 | success | 0.049994 | 0 | 4,032 | 0.002499 | 0.000862 |
|
187 | model.layers.26.self_attn.q_proj | 0.036869 | 4,096 | 4,096 | 1 | 8.40632 | -23.18886 | 1.564288 | true | 0.001744 | dense | -23.157452 | -1.324999 | -2.758503 | 64 | 0.047315 | 4,096 | 64 | 4,032 | 1 | 0.92579 | 0.001744 | 27.133411 | success | 0.041759 | 0 | under-trained | 4,032 | 0.001744 | 0.000637 |
188 | model.layers.26.self_attn.v_proj | 0.06321 | 1,024 | 4,096 | 4 | 14.601195 | -43.401385 | 1.136401 | true | 0.001065 | dense | -43.379188 | -1.386946 | -2.972454 | 64 | 0.041025 | 1,024 | 38 | 960 | 1 | 2.206405 | 0.001065 | 38.5042 | success | 0.032642 | 0.000001 | under-trained | 960 | 0.001065 | 0.00062 |
189 | model.layers.27.mlp.down_proj | 0.125634 | 4,096 | 14,336 | 3.5 | 20.134975 | -48.749573 | 1.566567 | true | 0.003792 | dense | -48.749521 | -0.922233 | -2.421139 | 64 | 0.11961 | 4,096 | 64 | 4,032 | 1 | 2.391872 | 0.003792 | 31.543194 | success | 0.061579 | 0.000001 | under-trained | 4,032 | 0.003792 | 0.001763 |
190 | model.layers.27.mlp.gate_proj | 0.080541 | 4,096 | 14,336 | 3.5 | 5.975536 | -12.835613 | 1.561437 | true | 0.007112 | dense | -12.813628 | -0.853734 | -2.148027 | 64 | 0.140044 | 4,096 | 12 | 4,032 | 1 | 1.436314 | 0.007112 | 19.692146 | success | 0.084331 | 0.000001 | 4,032 | 0.007112 | 0.002181 |
|
191 | model.layers.27.mlp.up_proj | 0.090913 | 4,096 | 14,336 | 3.5 | 5.596395 | -12.553345 | 1.56291 | true | 0.005713 | dense | -12.483229 | -0.893531 | -2.243113 | 64 | 0.127782 | 4,096 | 10 | 4,032 | 1 | 1.453508 | 0.005713 | 22.365685 | success | 0.075586 | 0.000001 | 4,032 | 0.005713 | 0.002055 |
|
192 | model.layers.27.self_attn.k_proj | 0.061444 | 1,024 | 4,096 | 4 | 10.763951 | -32.338098 | 1.135765 | true | 0.00099 | dense | -32.04649 | -1.391835 | -3.004296 | 64 | 0.040566 | 1,024 | 27 | 960 | 1 | 1.879073 | 0.00099 | 40.969563 | success | 0.031467 | 0.000001 | under-trained | 960 | 0.00099 | 0.000631 |
193 | model.layers.27.self_attn.o_proj | 0.09495 | 4,096 | 4,096 | 1 | 11.720985 | -32.742357 | 1.565708 | true | 0.001609 | dense | -32.718908 | -1.288713 | -2.793482 | 64 | 0.051438 | 4,096 | 64 | 4,032 | 1 | 1.340123 | 0.001609 | 31.971897 | success | 0.040111 | 0 | under-trained | 4,032 | 0.001609 | 0.000725 |
194 | model.layers.27.self_attn.q_proj | 0.030258 | 4,096 | 4,096 | 1 | 9.312165 | -26.042982 | 1.565224 | true | 0.001597 | dense | -26.018858 | -1.331789 | -2.796662 | 64 | 0.046581 | 4,096 | 51 | 4,032 | 1 | 1.163936 | 0.001597 | 29.165789 | success | 0.039964 | 0 | under-trained | 4,032 | 0.001597 | 0.000656 |
195 | model.layers.27.self_attn.v_proj | 0.054073 | 1,024 | 4,096 | 4 | 16.699773 | -50.638051 | 1.136774 | true | 0.000928 | dense | -50.55997 | -1.387949 | -3.03226 | 64 | 0.040931 | 1,024 | 31 | 960 | 1 | 2.819762 | 0.000928 | 44.087074 | success | 0.03047 | 0.000001 | under-trained | 960 | 0.000928 | 0.000633 |
196 | model.layers.28.mlp.down_proj | 0.147856 | 4,096 | 14,336 | 3.5 | 17.659206 | -40.82923 | 1.564656 | true | 0.004875 | dense | -40.829228 | -0.920379 | -2.312065 | 64 | 0.120122 | 4,096 | 64 | 4,032 | 1 | 2.082401 | 0.004875 | 24.642588 | success | 0.069818 | 0.000001 | under-trained | 4,032 | 0.004875 | 0.001747 |
197 | model.layers.28.mlp.gate_proj | 0.091559 | 4,096 | 14,336 | 3.5 | 5.433214 | -11.60878 | 1.560451 | true | 0.007301 | dense | -11.576672 | -0.863321 | -2.136632 | 64 | 0.136987 | 4,096 | 11 | 4,032 | 1 | 1.336664 | 0.007301 | 18.763388 | success | 0.085444 | 0.000001 | 4,032 | 0.007301 | 0.002153 |
|
198 | model.layers.28.mlp.up_proj | 0.081664 | 4,096 | 14,336 | 3.5 | 5.483033 | -12.276219 | 1.562416 | true | 0.005768 | dense | -12.196294 | -0.893248 | -2.238947 | 64 | 0.127865 | 4,096 | 11 | 4,032 | 1 | 1.351685 | 0.005768 | 22.166574 | success | 0.07595 | 0.000001 | 4,032 | 0.005768 | 0.002042 |
|
199 | model.layers.28.self_attn.k_proj | 0.049955 | 1,024 | 4,096 | 4 | 8.914576 | -27.248532 | 1.135713 | true | 0.000878 | dense | -26.40493 | -1.391175 | -3.056627 | 64 | 0.040628 | 1,024 | 45 | 960 | 1 | 1.179835 | 0.000878 | 46.28624 | success | 0.029627 | 0.000001 | under-trained | 960 | 0.000878 | 0.000583 |
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