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train · 224 rows

layer_id int64 0 223	name stringlengths 26 32	D float64 0.07 0.18	M int64 1.02k 4.1k	N int64 4.1k 14.3k	Q float64 1 4	alpha float64 1.67 8.98	alpha_weighted float64 -8.36 1.59	entropy float64 0.8 1.31	has_esd bool 1 class	lambda_max float32 0.03 5.52	layer_type stringclasses 1 value	log_alpha_norm float64 -8.25 1.61	log_norm float32 -0.65 1.02	log_spectral_norm float32 -1.47 0.74	matrix_rank int64 64 64	norm float32 0.22 10.5	num_evals int64 1.02k 4.1k	num_pl_spikes int64 5 24	rank_loss int64 960 4.03k	rf int64 1 1	sigma float64 0.14 3.57	spectral_norm float32 0.03 5.52	stable_rank float32 1.46 10.7	status stringclasses 1 value	sv_max float64 0.18 2.35	sv_min float64 0 0	warning stringclasses 3 values	weak_rank_loss int64 960 4.03k	xmax float64 0.03 5.52	xmin float64 0 0.72
0	model.layers.0.mlp.down_proj	0.076356	4,096	14,336	3.5	1.976659	0.641223	1.111537	true	2.110559	dense	0.776857	0.739268	0.324398	64	5.486152	4,096	13	4,032	1	0.270876	2.110559	2.599383	success	1.452776	0.000002	over-trained	4,032	2.110559	0.0763
1	model.layers.0.mlp.gate_proj	0.097636	4,096	14,336	3.5	1.975295	1.465367	1.041065	true	5.518834	dense	1.494165	1.007699	0.741847	64	10.178849	4,096	13	4,032	1	0.270498	5.518834	1.844384	success	2.34922	0.000003	over-trained	4,032	5.518834	0.129959
2	model.layers.0.mlp.up_proj	0.108372	4,096	14,336	3.5	2.199473	1.163998	1.129014	true	3.382336	dense	1.224962	0.933887	0.529217	64	8.587893	4,096	12	4,032	1	0.346258	3.382336	2.539042	success	1.839113	0.000003		4,032	3.382336	0.188612
3	model.layers.0.self_attn.k_proj	0.111312	1,024	4,096	4	2.045406	-1.442043	0.836641	true	0.197235	dense	-1.367215	-0.272036	-0.705016	64	0.53452	1,024	13	960	1	0.289943	0.197235	2.710064	success	0.444112	0.000001		960	0.197235	0.004435
4	model.layers.0.self_attn.o_proj	0.13921	4,096	4,096	1	2.428003	-1.241056	1.204532	true	0.308218	dense	-0.972342	0.131642	-0.511142	64	1.354072	4,096	10	4,032	1	0.451574	0.308218	4.393232	success	0.555174	0		4,032	0.308218	0.045807
5	model.layers.0.self_attn.q_proj	0.110216	4,096	4,096	1	1.745021	-0.045243	1.079604	true	0.942048	dense	-0.027297	0.187667	-0.025927	64	1.540518	4,096	7	4,032	1	0.281591	0.942048	1.635286	success	0.970592	0	over-trained	4,032	0.942048	0.011045
6	model.layers.0.self_attn.v_proj	0.139601	1,024	4,096	4	1.665781	-2.123338	0.868317	true	0.053128	dense	-1.80718	-0.652068	-1.27468	64	0.222809	1,024	23	960	1	0.138825	0.053128	4.193841	success	0.230494	0.000001	over-trained	960	0.053128	0.000891
7	model.layers.1.mlp.down_proj	0.101949	4,096	14,336	3.5	1.719556	0.767172	0.949792	true	2.79348	dense	0.785344	0.611519	0.446146	64	4.088073	4,096	16	4,032	1	0.179889	2.79348	1.463434	success	1.671371	0.000002	over-trained	4,032	2.79348	0.016781
8	model.layers.1.mlp.gate_proj	0.107671	4,096	14,336	3.5	2.701273	0.824367	1.214594	true	2.019191	dense	0.958328	0.928768	0.305177	64	8.48726	4,096	10	4,032	1	0.53799	2.019191	4.203298	success	1.420982	0.000003		4,032	2.019191	0.322694
9	model.layers.1.mlp.up_proj	0.102802	4,096	14,336	3.5	3.300739	0.875642	1.22134	true	1.841987	dense	0.932314	0.888636	0.265287	64	7.738125	4,096	9	4,032	1	0.766913	1.841987	4.200965	success	1.357198	0.000003		4,032	1.841987	0.361084
10	model.layers.1.self_attn.k_proj	0.08085	1,024	4,096	4	2.360889	-2.882427	1.017059	true	0.06013	dense	-2.741234	-0.475349	-1.220908	64	0.334697	1,024	19	960	1	0.312209	0.06013	5.566203	success	0.245215	0.000001		960	0.06013	0.003562
11	model.layers.1.self_attn.o_proj	0.11793	4,096	4,096	1	2.604368	-1.317499	1.241264	true	0.311975	dense	-1.013566	0.226974	-0.50588	64	1.686452	4,096	12	4,032	1	0.463141	0.311975	5.405729	success	0.558547	0		4,032	0.311975	0.055241
12	model.layers.1.self_attn.q_proj	0.126949	4,096	4,096	1	2.072133	-0.947831	1.275919	true	0.348805	dense	-0.841066	0.052785	-0.457418	64	1.129237	4,096	12	4,032	1	0.309498	0.348805	3.237449	success	0.590597	0		4,032	0.348805	0.01895
13	model.layers.1.self_attn.v_proj	0.169919	1,024	4,096	4	2.527824	-3.656965	0.913994	true	0.035753	dense	-3.182534	-0.563165	-1.446685	64	0.273423	1,024	12	960	1	0.441045	0.035753	7.647514	success	0.189085	0.000001		960	0.035753	0.007994
14	model.layers.2.mlp.down_proj	0.110411	4,096	14,336	3.5	1.969377	0.598623	1.136016	true	2.013565	dense	0.711509	0.726285	0.303966	64	5.324576	4,096	15	4,032	1	0.250292	2.013565	2.644352	success	1.419001	0.000002	over-trained	4,032	2.013565	0.069722
15	model.layers.2.mlp.gate_proj	0.104275	4,096	14,336	3.5	2.848692	1.331815	1.171957	true	2.934391	dense	1.359826	0.934592	0.467518	64	8.601845	4,096	8	4,032	1	0.653611	2.934391	2.93139	success	1.713006	0.000003		4,032	2.934391	0.360468
16	model.layers.2.mlp.up_proj	0.080501	4,096	14,336	3.5	2.615539	0.902959	1.192592	true	2.21426	dense	0.988758	0.887691	0.345229	64	7.721309	4,096	11	4,032	1	0.487103	2.21426	3.487084	success	1.488039	0.000003		4,032	2.21426	0.250273
17	model.layers.2.self_attn.k_proj	0.11145	1,024	4,096	4	2.114741	-2.017564	0.956911	true	0.111161	dense	-1.777128	-0.235082	-0.954048	64	0.581993	1,024	16	960	1	0.278685	0.111161	5.235595	success	0.333408	0.000001		960	0.111161	0.007331
18	model.layers.2.self_attn.o_proj	0.141994	4,096	4,096	1	3.93533	-1.795762	1.230097	true	0.349689	dense	-1.707074	0.232389	-0.456318	64	1.707611	4,096	5	4,032	1	1.31272	0.349689	4.883228	success	0.591345	0		4,032	0.349689	0.132564
19	model.layers.2.self_attn.q_proj	0.104989	4,096	4,096	1	2.516689	-0.836226	1.272481	true	0.465294	dense	-0.752782	0.233927	-0.332272	64	1.71367	4,096	9	4,032	1	0.505563	0.465294	3.682979	success	0.682125	0		4,032	0.465294	0.056918
20	model.layers.2.self_attn.v_proj	0.119055	1,024	4,096	4	2.579519	-3.018373	0.853179	true	0.067588	dense	-2.747374	-0.461957	-1.17013	64	0.345178	1,024	11	960	1	0.476243	0.067588	5.107087	success	0.259977	0.000001		960	0.067588	0.010475
21	model.layers.3.mlp.down_proj	0.126696	4,096	14,336	3.5	1.9602	0.149524	1.17489	true	1.19201	dense	0.465348	0.671329	0.07628	64	4.691691	4,096	13	4,032	1	0.266311	1.19201	3.93595	success	1.091792	0.000002	over-trained	4,032	1.19201	0.078711
22	model.layers.3.mlp.gate_proj	0.116071	4,096	14,336	3.5	2.344844	1.0169	1.169203	true	2.714407	dense	1.085425	0.901845	0.433675	64	7.977097	4,096	12	4,032	1	0.388223	2.714407	2.938799	success	1.647546	0.000003		4,032	2.714407	0.204137
23	model.layers.3.mlp.up_proj	0.100062	4,096	14,336	3.5	2.796167	1.043718	1.177172	true	2.361932	dense	1.089993	0.868782	0.373267	64	7.392345	4,096	8	4,032	1	0.635041	2.361932	3.129788	success	1.536858	0.000003		4,032	2.361932	0.312789
24	model.layers.3.self_attn.k_proj	0.109798	1,024	4,096	4	2.123883	-2.532217	0.99227	true	0.064231	dense	-2.059328	-0.296245	-1.192258	64	0.50554	1,024	17	960	1	0.272582	0.064231	7.870701	success	0.253438	0.000001		960	0.064231	0.006133
25	model.layers.3.self_attn.o_proj	0.109008	4,096	4,096	1	2.340976	-0.896558	1.214465	true	0.414014	dense	-0.659986	0.24802	-0.382985	64	1.770192	4,096	11	4,032	1	0.40432	0.414014	4.275679	success	0.643439	0		4,032	0.414014	0.051132
26	model.layers.3.self_attn.q_proj	0.118265	4,096	4,096	1	2.194257	-1.095463	1.304062	true	0.316781	dense	-0.844544	0.19141	-0.499241	64	1.553855	4,096	15	4,032	1	0.308356	0.316781	4.905139	success	0.562833	0		4,032	0.316781	0.029841
27	model.layers.3.self_attn.v_proj	0.126515	1,024	4,096	4	2.500194	-3.016375	0.869775	true	0.062165	dense	-2.658711	-0.442423	-1.206456	64	0.361058	1,024	11	960	1	0.452325	0.062165	5.808084	success	0.249328	0.000001		960	0.062165	0.010689
28	model.layers.4.mlp.down_proj	0.103996	4,096	14,336	3.5	1.91414	0.15396	1.164155	true	1.203463	dense	0.454112	0.646136	0.080433	64	4.427268	4,096	15	4,032	1	0.23603	1.203463	3.678772	success	1.097025	0.000002	over-trained	4,032	1.203463	0.056798
29	model.layers.4.mlp.gate_proj	0.088468	4,096	14,336	3.5	2.330314	1.01381	1.172862	true	2.723034	dense	1.0994	0.924686	0.435053	64	8.407862	4,096	13	4,032	1	0.368963	2.723034	3.087681	success	1.650162	0.000003		4,032	2.723034	0.206369
30	model.layers.4.mlp.up_proj	0.112494	4,096	14,336	3.5	2.411922	0.7567	1.19018	true	2.059364	dense	0.84922	0.840916	0.313733	64	6.932912	4,096	13	4,032	1	0.391597	2.059364	3.36653	success	1.435049	0.000003		4,032	2.059364	0.182713
31	model.layers.4.self_attn.k_proj	0.106653	1,024	4,096	4	1.965432	-1.811593	0.935161	true	0.119749	dense	-1.515501	-0.213677	-0.921727	64	0.611397	1,024	16	960	1	0.241358	0.119749	5.105644	success	0.346048	0.000001	over-trained	960	0.119749	0.006634
32	model.layers.4.self_attn.o_proj	0.156342	4,096	4,096	1	2.040308	-1.240466	1.247873	true	0.246615	dense	-0.68488	0.218244	-0.60798	64	1.652891	4,096	16	4,032	1	0.260077	0.246615	6.702302	success	0.496604	0		4,032	0.246615	0.030612
33	model.layers.4.self_attn.q_proj	0.106517	4,096	4,096	1	2.118331	-0.048152	1.163578	true	0.949006	dense	-0.004813	0.343573	-0.022731	64	2.205837	4,096	12	4,032	1	0.322834	0.949006	2.324366	success	0.974169	0		4,032	0.949006	0.036759
34	model.layers.4.self_attn.v_proj	0.098556	1,024	4,096	4	2.270948	-2.337106	0.826632	true	0.093512	dense	-2.127962	-0.435603	-1.029132	64	0.366772	1,024	12	960	1	0.366891	0.093512	3.922195	success	0.305797	0.000001		960	0.093512	0.007871
35	model.layers.5.mlp.down_proj	0.109637	4,096	14,336	3.5	2.100318	0.406167	1.129674	true	1.560931	dense	0.554776	0.642646	0.193384	64	4.39183	4,096	10	4,032	1	0.347951	1.560931	2.813596	success	1.249372	0.000002		4,032	1.560931	0.097031
36	model.layers.5.mlp.gate_proj	0.099106	4,096	14,336	3.5	2.027693	1.223991	1.095415	true	4.014554	dense	1.289638	0.961005	0.603637	64	9.141247	4,096	13	4,032	1	0.285031	4.014554	2.277027	success	2.003635	0.000003		4,032	4.014554	0.140928
37	model.layers.5.mlp.up_proj	0.078598	4,096	14,336	3.5	2.681518	0.603089	1.209362	true	1.67844	dense	0.710326	0.817694	0.224906	64	6.571946	4,096	12	4,032	1	0.485412	1.67844	3.915508	success	1.295546	0.000003		4,032	1.67844	0.216032
38	model.layers.5.self_attn.k_proj	0.102649	1,024	4,096	4	2.076816	-1.952721	0.951571	true	0.11475	dense	-1.712682	-0.227943	-0.940248	64	0.59164	1,024	15	960	1	0.278033	0.11475	5.155904	success	0.338748	0.000001		960	0.11475	0.008165
39	model.layers.5.self_attn.o_proj	0.162993	4,096	4,096	1	2.339322	-1.435271	1.255186	true	0.243477	dense	-0.995128	0.18907	-0.613542	64	1.545505	4,096	16	4,032	1	0.33483	0.243477	6.347635	success	0.493434	0		4,032	0.243477	0.0367
40	model.layers.5.self_attn.q_proj	0.093223	4,096	4,096	1	2.245052	-0.889302	1.285391	true	0.401683	dense	-0.64295	0.281537	-0.396116	64	1.912217	4,096	14	4,032	1	0.332754	0.401683	4.760511	success	0.633785	0		4,032	0.401683	0.040819
41	model.layers.5.self_attn.v_proj	0.101257	1,024	4,096	4	2.374842	-2.704781	0.863961	true	0.072622	dense	-2.498283	-0.466641	-1.138931	64	0.341475	1,024	13	960	1	0.381313	0.072622	4.702079	success	0.269485	0.000001		960	0.072622	0.008183
42	model.layers.6.mlp.down_proj	0.071468	4,096	14,336	3.5	2.035732	0.400232	1.137449	true	1.572546	dense	0.512145	0.619253	0.196603	64	4.161528	4,096	14	4,032	1	0.276811	1.572546	2.646363	success	1.254012	0.000002		4,032	1.572546	0.061191
43	model.layers.6.mlp.gate_proj	0.119994	4,096	14,336	3.5	1.953833	0.906343	1.142175	true	2.909911	dense	1.050445	0.91896	0.46388	64	8.297745	4,096	15	4,032	1	0.246279	2.909911	2.851546	success	1.705846	0.000003	over-trained	4,032	2.909911	0.113972
44	model.layers.6.mlp.up_proj	0.128267	4,096	14,336	3.5	3.331498	0.422375	1.22456	true	1.339005	dense	0.518199	0.783048	0.126782	64	6.068035	4,096	9	4,032	1	0.777166	1.339005	4.531749	success	1.157154	0.000003		4,032	1.339005	0.293744
45	model.layers.6.self_attn.k_proj	0.136179	1,024	4,096	4	2.26844	-2.471877	0.969799	true	0.081343	dense	-2.094685	-0.255944	-1.089682	64	0.554697	1,024	13	960	1	0.351802	0.081343	6.819263	success	0.285206	0.000001		960	0.081343	0.010278
46	model.layers.6.self_attn.o_proj	0.126876	4,096	4,096	1	2.412226	-1.192384	1.228731	true	0.320399	dense	-0.884048	0.20558	-0.494309	64	1.605389	4,096	12	4,032	1	0.407675	0.320399	5.01059	success	0.566038	0		4,032	0.320399	0.047149
47	model.layers.6.self_attn.q_proj	0.101797	4,096	4,096	1	3.283433	-1.484998	1.299478	true	0.352964	dense	-1.381936	0.244457	-0.45227	64	1.755727	4,096	7	4,032	1	0.863056	0.352964	4.974241	success	0.594108	0		4,032	0.352964	0.089685
48	model.layers.6.self_attn.v_proj	0.077175	1,024	4,096	4	2.272744	-2.044697	0.79907	true	0.125991	dense	-1.970046	-0.425561	-0.89966	64	0.375352	1,024	12	960	1	0.36741	0.125991	2.979194	success	0.354952	0.000001		960	0.125991	0.00779
49	model.layers.7.mlp.down_proj	0.097933	4,096	14,336	3.5	2.113675	0.373255	1.155359	true	1.501726	dense	0.433841	0.579983	0.176591	64	3.801748	4,096	16	4,032	1	0.278419	1.501726	2.531586	success	1.225449	0.000002		4,032	1.501726	0.057097
50	model.layers.7.mlp.gate_proj	0.120298	4,096	14,336	3.5	2.53411	1.171962	1.152454	true	2.900514	dense	1.220762	0.90765	0.462475	64	8.084437	4,096	9	4,032	1	0.51137	2.900514	2.787243	success	1.70309	0.000003		4,032	2.900514	0.291948
51	model.layers.7.mlp.up_proj	0.120661	4,096	14,336	3.5	3.394365	0.288046	1.233795	true	1.215794	dense	0.375921	0.760848	0.08486	64	5.765645	4,096	8	4,032	1	0.846536	1.215794	4.742287	success	1.102631	0.000003		4,032	1.215794	0.298249
52	model.layers.7.self_attn.k_proj	0.097194	1,024	4,096	4	2.03992	-1.77188	0.93983	true	0.135331	dense	-1.558067	-0.19748	-0.868602	64	0.634629	1,024	16	960	1	0.25998	0.135331	4.689452	success	0.367874	0.000001		960	0.135331	0.007392
53	model.layers.7.self_attn.o_proj	0.1291	4,096	4,096	1	2.514249	-1.735049	1.268097	true	0.204133	dense	-1.337075	0.119222	-0.690086	64	1.315897	4,096	14	4,032	1	0.4047	0.204133	6.446266	success	0.451811	0		4,032	0.204133	0.037969
54	model.layers.7.self_attn.q_proj	0.103556	4,096	4,096	1	2.209192	-0.781709	1.271026	true	0.442748	dense	-0.571732	0.276067	-0.353844	64	1.888281	4,096	14	4,032	1	0.32317	0.442748	4.264915	success	0.665393	0		4,032	0.442748	0.037452
55	model.layers.7.self_attn.v_proj	0.116714	1,024	4,096	4	3.199264	-3.84439	0.884482	true	0.062857	dense	-3.679862	-0.454043	-1.201648	64	0.351525	1,024	9	960	1	0.733088	0.062857	5.592487	success	0.250712	0.000001		960	0.062857	0.014862
56	model.layers.8.mlp.down_proj	0.105301	4,096	14,336	3.5	2.192544	0.192926	1.166888	true	1.224593	dense	0.317413	0.568647	0.087992	64	3.703793	4,096	9	4,032	1	0.397515	1.224593	3.024509	success	1.106613	0.000002		4,032	1.224593	0.107301
57	model.layers.8.mlp.gate_proj	0.133873	4,096	14,336	3.5	2.461473	1.166411	1.141331	true	2.977607	dense	1.219701	0.904393	0.473867	64	8.024048	4,096	7	4,032	1	0.552385	2.977607	2.694798	success	1.725574	0.000003		4,032	2.977607	0.341856
58	model.layers.8.mlp.up_proj	0.098681	4,096	14,336	3.5	2.717492	0.070589	1.230717	true	1.061637	dense	0.363549	0.755756	0.025976	64	5.698434	4,096	12	4,032	1	0.495797	1.061637	5.367594	success	1.030357	0.000003		4,032	1.061637	0.195069
59	model.layers.8.self_attn.k_proj	0.086707	1,024	4,096	4	1.840124	-1.371642	0.895757	true	0.179719	dense	-1.197006	-0.181361	-0.745407	64	0.658626	1,024	21	960	1	0.18333	0.179719	3.664766	success	0.423932	0.000001	over-trained	960	0.179719	0.00387
60	model.layers.8.self_attn.o_proj	0.121409	4,096	4,096	1	3.583161	-2.131071	1.25919	true	0.254246	dense	-2.002284	0.130527	-0.594746	64	1.350601	4,096	7	4,032	1	0.976343	0.254246	5.312185	success	0.504228	0		4,032	0.254246	0.077565
61	model.layers.8.self_attn.q_proj	0.11208	4,096	4,096	1	2.427144	-0.644107	1.239413	true	0.542779	dense	-0.560986	0.254495	-0.265377	64	1.796781	4,096	9	4,032	1	0.475715	0.542779	3.310334	success	0.736736	0		4,032	0.542779	0.056712
62	model.layers.8.self_attn.v_proj	0.159415	1,024	4,096	4	2.033145	-2.506298	0.892429	true	0.058517	dense	-2.071934	-0.441358	-1.23272	64	0.361944	1,024	16	960	1	0.258286	0.058517	6.185312	success	0.241902	0.000002		960	0.058517	0.005716
63	model.layers.9.mlp.down_proj	0.12605	4,096	14,336	3.5	2.558539	-0.058346	1.199251	true	0.948846	dense	0.100675	0.554804	-0.022804	64	3.5876	4,096	7	4,032	1	0.589072	0.948846	3.781014	success	0.974087	0.000002		4,032	0.948846	0.169765
64	model.layers.9.mlp.gate_proj	0.127432	4,096	14,336	3.5	2.110989	0.754511	1.168852	true	2.277303	dense	0.960674	0.905857	0.357421	64	8.051132	4,096	11	4,032	1	0.334976	2.277303	3.535381	success	1.509073	0.000003		4,032	2.277303	0.196398
65	model.layers.9.mlp.up_proj	0.106688	4,096	14,336	3.5	2.725478	0.176719	1.230213	true	1.16102	dense	0.375216	0.750498	0.06484	64	5.629871	4,096	10	4,032	1	0.545644	1.16102	4.849074	success	1.077506	0.000003		4,032	1.16102	0.217533
66	model.layers.9.self_attn.k_proj	0.12144	1,024	4,096	4	1.904055	-1.685887	0.933734	true	0.130191	dense	-1.40812	-0.193478	-0.885419	64	0.640504	1,024	17	960	1	0.219266	0.130191	4.919728	success	0.36082	0.000001	over-trained	960	0.130191	0.006303
67	model.layers.9.self_attn.o_proj	0.124536	4,096	4,096	1	2.527644	-1.755166	1.264118	true	0.202121	dense	-1.317633	0.126397	-0.694388	64	1.337817	4,096	13	4,032	1	0.423692	0.202121	6.618884	success	0.449579	0		4,032	0.202121	0.040725
68	model.layers.9.self_attn.q_proj	0.141387	4,096	4,096	1	2.235578	-0.484324	1.228025	true	0.607234	dense	-0.363379	0.306138	-0.216644	64	2.023663	4,096	11	4,032	1	0.372541	0.607234	3.332588	success	0.779253	0		4,032	0.607234	0.048829
69	model.layers.9.self_attn.v_proj	0.156159	1,024	4,096	4	2.508996	-3.357604	0.892527	true	0.045896	dense	-2.908927	-0.480481	-1.338226	64	0.330764	1,024	13	960	1	0.41852	0.045896	7.206834	success	0.214233	0.000002		960	0.045896	0.009209
70	model.layers.10.mlp.down_proj	0.145644	4,096	14,336	3.5	2.310299	-0.13993	1.207432	true	0.869826	dense	0.07998	0.545591	-0.060568	64	3.512296	4,096	10	4,032	1	0.414353	0.869826	4.037931	success	0.932644	0.000002		4,032	0.869826	0.108121
71	model.layers.10.mlp.gate_proj	0.129242	4,096	14,336	3.5	1.983117	0.972382	1.117747	true	3.092645	dense	1.070145	0.891728	0.49033	64	7.793423	4,096	12	4,032	1	0.283801	3.092645	2.519986	success	1.758592	0.000003	over-trained	4,032	3.092645	0.133782
72	model.layers.10.mlp.up_proj	0.095463	4,096	14,336	3.5	2.807535	0.215918	1.227676	true	1.193731	dense	0.389662	0.747633	0.076906	64	5.59285	4,096	9	4,032	1	0.602512	1.193731	4.685184	success	1.09258	0.000003		4,032	1.193731	0.234278
73	model.layers.10.self_attn.k_proj	0.086916	1,024	4,096	4	2.299372	-2.133121	0.946239	true	0.118114	dense	-1.906117	-0.211709	-0.927697	64	0.614173	1,024	12	960	1	0.375096	0.118114	5.199819	success	0.343678	0.000001		960	0.118114	0.012086
74	model.layers.10.self_attn.o_proj	0.151336	4,096	4,096	1	4.212849	-2.743123	1.262647	true	0.223289	dense	-2.66085	0.078266	-0.651133	64	1.197475	4,096	5	4,032	1	1.43683	0.223289	5.362892	success	0.472535	0		4,032	0.223289	0.087148
75	model.layers.10.self_attn.q_proj	0.11007	4,096	4,096	1	2.299952	-0.997625	1.289676	true	0.368333	dense	-0.770098	0.246096	-0.433759	64	1.762364	4,096	15	4,032	1	0.335646	0.368333	4.784697	success	0.606905	0		4,032	0.368333	0.037428
76	model.layers.10.self_attn.v_proj	0.108391	1,024	4,096	4	2.863954	-3.271382	0.871677	true	0.072067	dense	-3.166746	-0.492168	-1.142261	64	0.321982	1,024	8	960	1	0.659007	0.072067	4.467789	success	0.268454	0.000001		960	0.072067	0.013138
77	model.layers.11.mlp.down_proj	0.121044	4,096	14,336	3.5	2.033375	-0.104563	1.208015	true	0.888335	dense	0.109249	0.519107	-0.051423	64	3.304507	4,096	15	4,032	1	0.266816	0.888335	3.71989	success	0.942515	0.000002		4,032	0.888335	0.053927
78	model.layers.11.mlp.gate_proj	0.104508	4,096	14,336	3.5	1.962975	0.654276	1.175149	true	2.15431	dense	0.895246	0.892658	0.333308	64	7.81013	4,096	14	4,032	1	0.257366	2.15431	3.625351	success	1.467757	0.000003	over-trained	4,032	2.15431	0.127026
79	model.layers.11.mlp.up_proj	0.088319	4,096	14,336	3.5	2.811194	0.076357	1.236399	true	1.064539	dense	0.364986	0.775995	0.027162	64	5.970279	4,096	11	4,032	1	0.546095	1.064539	5.608321	success	1.031765	0.000002		4,032	1.064539	0.22812
80	model.layers.11.self_attn.k_proj	0.100558	1,024	4,096	4	2.295746	-1.923274	0.938058	true	0.145293	dense	-1.789883	-0.18921	-0.837756	64	0.64683	1,024	12	960	1	0.37405	0.145293	4.451905	success	0.381173	0.000001		960	0.145293	0.012554
81	model.layers.11.self_attn.o_proj	0.133897	4,096	4,096	1	4.338986	-3.751656	1.293143	true	0.136572	dense	-3.278237	0.107854	-0.864639	64	1.281901	4,096	9	4,032	1	1.112995	0.136572	9.386274	success	0.369556	0		4,032	0.136572	0.068166
82	model.layers.11.self_attn.q_proj	0.114045	4,096	4,096	1	2.059657	-0.548258	1.242442	true	0.541765	dense	-0.326123	0.323086	-0.266189	64	2.104197	4,096	15	4,032	1	0.273602	0.541765	3.883963	success	0.736047	0		4,032	0.541765	0.032982
83	model.layers.11.self_attn.v_proj	0.147873	1,024	4,096	4	3.960762	-5.492393	0.924081	true	0.041049	dense	-5.30026	-0.525937	-1.386701	64	0.297895	1,024	6	960	1	1.208726	0.041049	7.257119	success	0.202605	0.000001		960	0.041049	0.016924
84	model.layers.12.mlp.down_proj	0.125361	4,096	14,336	3.5	2.72485	-0.227856	1.216594	true	0.824857	dense	-0.07467	0.52217	-0.083622	64	3.327895	4,096	8	4,032	1	0.609826	0.824857	4.034513	success	0.908216	0.000002		4,032	0.824857	0.150124
85	model.layers.12.mlp.gate_proj	0.095952	4,096	14,336	3.5	2.244348	0.681968	1.185655	true	2.013076	dense	0.908777	0.896029	0.30386	64	7.87098	4,096	12	4,032	1	0.359212	2.013076	3.909928	success	1.418829	0.000003		4,032	2.013076	0.200436
86	model.layers.12.mlp.up_proj	0.146924	4,096	14,336	3.5	3.119043	-0.502097	1.26141	true	0.690275	dense	0.031418	0.766576	-0.160978	64	5.842188	4,096	12	4,032	1	0.611715	0.690275	8.463566	success	0.830828	0.000003		4,032	0.690275	0.238178
87	model.layers.12.self_attn.k_proj	0.115202	1,024	4,096	4	2.16172	-2.125426	0.952411	true	0.103942	dense	-1.771345	-0.193855	-0.983211	64	0.639948	1,024	15	960	1	0.299955	0.103942	6.156802	success	0.3224	0.000001		960	0.103942	0.009599
88	model.layers.12.self_attn.o_proj	0.148559	4,096	4,096	1	2.553123	-2.006094	1.284288	true	0.163779	dense	-1.559166	0.076869	-0.785741	64	1.193628	4,096	15	4,032	1	0.401015	0.163779	7.288031	success	0.404696	0		4,032	0.163779	0.034577
89	model.layers.12.self_attn.q_proj	0.102668	4,096	4,096	1	2.82204	-0.916018	1.268871	true	0.473593	dense	-0.842054	0.266378	-0.324594	64	1.846624	4,096	10	4,032	1	0.57618	0.473593	3.899176	success	0.688181	0		4,032	0.473593	0.066412
90	model.layers.12.self_attn.v_proj	0.101775	1,024	4,096	4	3.908696	-5.604186	0.92975	true	0.036832	dense	-5.433726	-0.555715	-1.433774	64	0.278154	1,024	8	960	1	1.028379	0.036832	7.55195	success	0.191917	0.000001		960	0.036832	0.01297
91	model.layers.13.mlp.down_proj	0.135136	4,096	14,336	3.5	2.413927	-0.271754	1.229306	true	0.771654	dense	-0.027098	0.551078	-0.112578	64	3.556952	4,096	10	4,032	1	0.447123	0.771654	4.609519	success	0.878438	0.000002		4,032	0.771654	0.121258
92	model.layers.13.mlp.gate_proj	0.148227	4,096	14,336	3.5	2.047386	0.731107	1.174062	true	2.275584	dense	0.944523	0.91022	0.357093	64	8.13242	4,096	12	4,032	1	0.302354	2.275584	3.573773	success	1.508504	0.000003		4,032	2.275584	0.177543
93	model.layers.13.mlp.up_proj	0.11132	4,096	14,336	3.5	2.730719	0.30972	1.223642	true	1.298437	dense	0.518037	0.790919	0.113421	64	6.179018	4,096	9	4,032	1	0.576906	1.298437	4.758814	success	1.13949	0.000003		4,032	1.298437	0.255827
94	model.layers.13.self_attn.k_proj	0.123865	1,024	4,096	4	1.960272	-1.73244	0.939046	true	0.130685	dense	-1.496349	-0.200827	-0.883775	64	0.629757	1,024	17	960	1	0.2329	0.130685	4.818902	success	0.361503	0.000001	over-trained	960	0.130685	0.006992
95	model.layers.13.self_attn.o_proj	0.117118	4,096	4,096	1	4.00947	-3.650243	1.298894	true	0.122912	dense	-3.168431	0.065781	-0.910405	64	1.163539	4,096	10	4,032	1	0.951678	0.122912	9.466429	success	0.350588	0		4,032	0.122912	0.056796
96	model.layers.13.self_attn.q_proj	0.118379	4,096	4,096	1	2.351613	-0.668953	1.252137	true	0.519439	dense	-0.538434	0.294051	-0.284466	64	1.968116	4,096	12	4,032	1	0.390177	0.519439	3.78893	success	0.720721	0		4,032	0.519439	0.050464
97	model.layers.13.self_attn.v_proj	0.127578	1,024	4,096	4	2.728843	-3.822366	0.919005	true	0.039744	dense	-3.408978	-0.506694	-1.400728	64	0.311391	1,024	14	960	1	0.462053	0.039744	7.834901	success	0.199359	0.000002		960	0.039744	0.008851
98	model.layers.14.mlp.down_proj	0.096078	4,096	14,336	3.5	2.487171	-0.278566	1.233047	true	0.772678	dense	-0.100971	0.516764	-0.112001	64	3.286729	4,096	11	4,032	1	0.448399	0.772678	4.253684	success	0.879021	0.000002		4,032	0.772678	0.105146
99	model.layers.14.mlp.gate_proj	0.144604	4,096	14,336	3.5	2.241275	0.674673	1.195751	true	1.999962	dense	0.925215	0.924942	0.301022	64	8.412821	4,096	11	4,032	1	0.374258	1.999962	4.20649	success	1.4142	0.000003		4,032	1.999962	0.238612

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