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train · 224 rows

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
0	model.layers.0.mlp.down_proj	0.078037	4,096	14,336	3.5	4.053136	-8.624209	1.546217	true	0.007451	dense	-8.422872	-0.942671	-2.127786	64	0.114112	4,096	21	4,032	1	0.666249	0.007451	15.314962	success	0.086319	0.000001		4,032	0.007451	0.001594
1	model.layers.0.mlp.gate_proj	0.074845	4,096	14,336	3.5	3.074121	-6.048194	1.523045	true	0.010778	dense	-5.992284	-1.043336	-1.967455	64	0.090503	4,096	13	4,032	1	0.575258	0.010778	8.39689	success	0.103818	0.000001		4,032	0.010778	0.001346
2	model.layers.0.mlp.up_proj	0.073709	4,096	14,336	3.5	2.963981	-5.587149	1.50815	true	0.013031	dense	-5.539123	-1.029696	-1.885015	64	0.093391	4,096	18	4,032	1	0.462915	0.013031	7.166698	success	0.114154	0.000001		4,032	0.013031	0.001169
3	model.layers.0.self_attn.k_proj	0.041871	1,024	4,096	4	3.660928	-8.275696	1.091316	true	0.005489	dense	-8.234427	-1.295308	-2.260546	64	0.050663	1,024	34	960	1	0.456345	0.005489	9.230771	success	0.074084	0.000001		960	0.005489	0.000629
4	model.layers.0.self_attn.o_proj	0.075064	4,096	4,096	1	2.545702	-4.788104	1.446955	true	0.013157	dense	-4.725399	-1.189854	-1.880858	64	0.064587	4,096	19	4,032	1	0.354608	0.013157	4.90913	success	0.114702	0		4,032	0.013157	0.00069
5	model.layers.0.self_attn.q_proj	0.063552	4,096	4,096	1	3.702849	-8.79926	1.540747	true	0.004204	dense	-8.706662	-1.264196	-2.376349	64	0.054426	4,096	41	4,032	1	0.422114	0.004204	12.9465	success	0.064837	0		4,032	0.004204	0.000649
6	model.layers.0.self_attn.v_proj	0.065128	1,024	4,096	4	4.518371	-11.075607	1.074268	true	0.003538	dense	-11.073485	-1.633022	-2.451239	64	0.02328	1,024	64	960	1	0.439796	0.003538	6.579869	success	0.059481	0.000001		960	0.003538	0.000235
7	model.layers.1.mlp.down_proj	0.120789	4,096	14,336	3.5	3.760372	-8.12376	1.553696	true	0.006913	dense	-8.030754	-0.996069	-2.160361	64	0.100909	4,096	7	4,032	1	1.043323	0.006913	14.59795	success	0.083142	0.000001		4,032	0.006913	0.001736
8	model.layers.1.mlp.gate_proj	0.101213	4,096	14,336	3.5	3.073197	-6.50478	1.540912	true	0.007645	dense	-6.342643	-1.041639	-2.116617	64	0.090858	4,096	9	4,032	1	0.691066	0.007645	11.884425	success	0.087436	0.000001		4,032	0.007645	0.001464
9	model.layers.1.mlp.up_proj	0.120154	4,096	14,336	3.5	3.501113	-7.287698	1.536073	true	0.008288	dense	-7.149562	-1.016781	-2.081537	64	0.09621	4,096	15	4,032	1	0.645785	0.008288	11.607965	success	0.09104	0.000001		4,032	0.008288	0.001366
10	model.layers.1.self_attn.k_proj	0.056722	1,024	4,096	4	4.463136	-10.295389	1.102708	true	0.004934	dense	-10.254933	-1.28201	-2.306761	64	0.052238	1,024	62	960	1	0.439819	0.004934	10.586463	success	0.070246	0.000001		960	0.004934	0.00056
11	model.layers.1.self_attn.o_proj	0.082948	4,096	4,096	1	2.788825	-6.187573	1.512383	true	0.006044	dense	-5.846718	-1.19272	-2.218702	64	0.064162	4,096	17	4,032	1	0.433854	0.006044	10.616527	success	0.077741	0		4,032	0.006044	0.000848
12	model.layers.1.self_attn.q_proj	0.051761	4,096	4,096	1	4.367304	-9.032353	1.518836	true	0.008547	dense	-9.028883	-1.188359	-2.068176	64	0.06481	4,096	64	4,032	1	0.420913	0.008547	7.582582	success	0.092451	0		4,032	0.008547	0.000665
13	model.layers.1.self_attn.v_proj	0.084882	1,024	4,096	4	6.50357	-18.628179	1.1217	true	0.001367	dense	-18.610157	-1.656919	-2.864301	64	0.022033	1,024	64	960	1	0.687946	0.001367	16.120611	success	0.03697	0.000001	under-trained	960	0.001367	0.000273
14	model.layers.2.mlp.down_proj	0.141108	4,096	14,336	3.5	4.986315	-11.807773	1.561366	true	0.004285	dense	-11.631251	-1.010099	-2.368036	64	0.097701	4,096	12	4,032	1	1.15075	0.004285	22.800112	success	0.065461	0.000001		4,032	0.004285	0.001526
15	model.layers.2.mlp.gate_proj	0.09412	4,096	14,336	3.5	3.715742	-7.997589	1.549306	true	0.007041	dense	-7.919346	-1.032961	-2.152353	64	0.092691	4,096	10	4,032	1	0.858793	0.007041	13.164119	success	0.083912	0.000001		4,032	0.007041	0.001451
16	model.layers.2.mlp.up_proj	0.088223	4,096	14,336	3.5	3.476825	-7.241272	1.543075	true	0.008266	dense	-7.155042	-1.013239	-2.082725	64	0.096998	4,096	12	4,032	1	0.714998	0.008266	11.735083	success	0.090915	0.000001		4,032	0.008266	0.001439
17	model.layers.2.self_attn.k_proj	0.059055	1,024	4,096	4	6.324751	-16.606587	1.124112	true	0.002368	dense	-16.570013	-1.3895	-2.625651	64	0.040785	1,024	64	960	1	0.665594	0.002368	17.224663	success	0.04866	0.000001	under-trained	960	0.002368	0.000507
18	model.layers.2.self_attn.o_proj	0.054473	4,096	4,096	1	3.100158	-7.058452	1.526014	true	0.005287	dense	-6.920864	-1.264247	-2.276804	64	0.054419	4,096	21	4,032	1	0.458292	0.005287	10.293361	success	0.072711	0		4,032	0.005287	0.0007
19	model.layers.2.self_attn.q_proj	0.085959	4,096	4,096	1	8.018122	-20.184861	1.553734	true	0.003038	dense	-20.184489	-1.360992	-2.517405	64	0.043552	4,096	64	4,032	1	0.877265	0.003038	14.335519	success	0.055119	0	under-trained	4,032	0.003038	0.000566
20	model.layers.2.self_attn.v_proj	0.09117	1,024	4,096	4	7.027676	-20.602752	1.12715	true	0.00117	dense	-20.565834	-1.62459	-2.931659	64	0.023736	1,024	64	960	1	0.753459	0.00117	20.280077	success	0.034211	0.000001	under-trained	960	0.00117	0.000304
21	model.layers.3.mlp.down_proj	0.08119	4,096	14,336	3.5	5.102273	-12.319074	1.563152	true	0.003851	dense	-12.153177	-1.034317	-2.414429	64	0.092402	4,096	10	4,032	1	1.297253	0.003851	23.994524	success	0.062056	0.000001		4,032	0.003851	0.001462
22	model.layers.3.mlp.gate_proj	0.10023	4,096	14,336	3.5	3.712471	-8.48617	1.556851	true	0.005178	dense	-8.305467	-1.050676	-2.285855	64	0.088987	4,096	8	4,032	1	0.959003	0.005178	17.186176	success	0.071957	0.000001		4,032	0.005178	0.001423
23	model.layers.3.mlp.up_proj	0.11905	4,096	14,336	3.5	3.594004	-8.02471	1.553261	true	0.005851	dense	-7.847661	-1.035492	-2.232805	64	0.092153	4,096	9	4,032	1	0.864668	0.005851	15.75117	success	0.076489	0.000001		4,032	0.005851	0.001451
24	model.layers.3.self_attn.k_proj	0.104859	1,024	4,096	4	5.604087	-12.085917	1.085087	true	0.006972	dense	-12.084052	-1.287998	-2.156626	64	0.051523	1,024	64	960	1	0.575511	0.006972	7.389718	success	0.0835	0.000001		960	0.006972	0.000571
25	model.layers.3.self_attn.o_proj	0.063017	4,096	4,096	1	4.106814	-10.249573	1.550359	true	0.003193	dense	-10.072092	-1.276134	-2.495748	64	0.05295	4,096	22	4,032	1	0.662375	0.003193	16.581116	success	0.05651	0		4,032	0.003193	0.000741
26	model.layers.3.self_attn.q_proj	0.067876	4,096	4,096	1	3.348291	-7.814138	1.538209	true	0.004637	dense	-7.730213	-1.295588	-2.333769	64	0.05063	4,096	12	4,032	1	0.677893	0.004637	10.918955	success	0.068095	0		4,032	0.004637	0.000785
27	model.layers.3.self_attn.v_proj	0.070333	1,024	4,096	4	5.224446	-15.4996	1.13189	true	0.00108	dense	-15.310787	-1.573987	-2.966745	64	0.026669	1,024	11	960	1	1.273718	0.00108	24.70347	success	0.032857	0.000001		960	0.00108	0.000431
28	model.layers.4.mlp.down_proj	0.103412	4,096	14,336	3.5	6.499501	-16.271618	1.564917	true	0.003137	dense	-16.07889	-1.03764	-2.503518	64	0.091698	4,096	13	4,032	1	1.525287	0.003137	29.233288	success	0.056007	0.000001	under-trained	4,032	0.003137	0.001422
29	model.layers.4.mlp.gate_proj	0.116253	4,096	14,336	3.5	3.795076	-8.701769	1.557888	true	0.005094	dense	-8.544298	-1.054941	-2.29291	64	0.088117	4,096	7	4,032	1	1.056439	0.005094	17.296932	success	0.071375	0.000001		4,032	0.005094	0.001453
30	model.layers.4.mlp.up_proj	0.12004	4,096	14,336	3.5	4.187209	-9.434501	1.55538	true	0.005582	dense	-9.328923	-1.033906	-2.253172	64	0.09249	4,096	12	4,032	1	0.920068	0.005582	16.567825	success	0.074716	0.000001		4,032	0.005582	0.001405
31	model.layers.4.self_attn.k_proj	0.06627	1,024	4,096	4	6.227436	-16.95982	1.127202	true	0.001891	dense	-16.916808	-1.442925	-2.723403	64	0.036064	1,024	64	960	1	0.653429	0.001891	19.075619	success	0.043481	0.000001	under-trained	960	0.001891	0.00045
32	model.layers.4.self_attn.o_proj	0.051627	4,096	4,096	1	4.323554	-10.8611	1.552673	true	0.003076	dense	-10.770511	-1.30265	-2.512077	64	0.049814	4,096	22	4,032	1	0.708584	0.003076	16.196711	success	0.055458	0		4,032	0.003076	0.000711
33	model.layers.4.self_attn.q_proj	0.079045	4,096	4,096	1	7.006285	-18.277367	1.554457	true	0.002462	dense	-18.263869	-1.388304	-2.60871	64	0.040897	4,096	64	4,032	1	0.750786	0.002462	16.611397	success	0.049619	0	under-trained	4,032	0.002462	0.000519
34	model.layers.4.self_attn.v_proj	0.064339	1,024	4,096	4	8.255926	-25.286125	1.132694	true	0.000865	dense	-25.089855	-1.590087	-3.062785	64	0.025699	1,024	64	960	1	0.906991	0.000865	29.696016	success	0.029418	0.000001	under-trained	960	0.000865	0.000344
35	model.layers.5.mlp.down_proj	0.102415	4,096	14,336	3.5	6.801178	-17.267207	1.565843	true	0.002892	dense	-17.055313	-1.040575	-2.538856	64	0.09108	4,096	11	4,032	1	1.749121	0.002892	31.497822	success	0.053774	0.000001	under-trained	4,032	0.002892	0.001433
36	model.layers.5.mlp.gate_proj	0.101403	4,096	14,336	3.5	4.828013	-11.53821	1.561887	true	0.004075	dense	-11.414749	-1.061174	-2.389846	64	0.086861	4,096	9	4,032	1	1.276004	0.004075	21.314381	success	0.063838	0.000001		4,032	0.004075	0.00138
37	model.layers.5.mlp.up_proj	0.122957	4,096	14,336	3.5	4.840966	-11.489038	1.560318	true	0.004234	dense	-11.329233	-1.041366	-2.373294	64	0.090915	4,096	13	4,032	1	1.065292	0.004234	21.474775	success	0.065066	0.000001		4,032	0.004234	0.001391
38	model.layers.5.self_attn.k_proj	0.058986	1,024	4,096	4	6.511588	-17.164931	1.124793	true	0.002312	dense	-17.146604	-1.41215	-2.636059	64	0.038712	1,024	64	960	1	0.688948	0.002312	16.745928	success	0.048081	0.000001	under-trained	960	0.002312	0.000485
39	model.layers.5.self_attn.o_proj	0.102708	4,096	4,096	1	6.50579	-18.101157	1.563011	true	0.001651	dense	-17.909787	-1.336704	-2.782315	64	0.046057	4,096	25	4,032	1	1.101158	0.001651	27.900465	success	0.04063	0	under-trained	4,032	0.001651	0.000678
40	model.layers.5.self_attn.q_proj	0.075607	4,096	4,096	1	8.9117	-24.09903	1.560718	true	0.001976	dense	-24.090758	-1.387967	-2.704201	64	0.040929	4,096	64	4,032	1	0.988963	0.001976	20.712568	success	0.044453	0	under-trained	4,032	0.001976	0.00055
41	model.layers.5.self_attn.v_proj	0.05698	1,024	4,096	4	10.334181	-32.260235	1.135119	true	0.000756	dense	-32.222351	-1.613308	-3.121702	64	0.024361	1,024	64	960	1	1.166773	0.000756	32.239906	success	0.027488	0.000001	under-trained	960	0.000756	0.000339
42	model.layers.6.mlp.down_proj	0.106362	4,096	14,336	3.5	6.931822	-17.470068	1.565562	true	0.003018	dense	-17.290337	-1.030035	-2.520271	64	0.093318	4,096	14	4,032	1	1.585346	0.003018	30.919691	success	0.054937	0.000001	under-trained	4,032	0.003018	0.001441
43	model.layers.6.mlp.gate_proj	0.089191	4,096	14,336	3.5	4.654741	-10.97667	1.560834	true	0.004384	dense	-10.851597	-1.049342	-2.35817	64	0.08926	4,096	11	4,032	1	1.101946	0.004384	20.362329	success	0.066209	0.000001		4,032	0.004384	0.001363
44	model.layers.6.mlp.up_proj	0.105811	4,096	14,336	3.5	4.32534	-10.156714	1.559256	true	0.004486	dense	-9.939353	-1.027995	-2.348189	64	0.093757	4,096	13	4,032	1	0.922283	0.004486	20.902269	success	0.066974	0.000001		4,032	0.004486	0.001421
45	model.layers.6.self_attn.k_proj	0.056873	1,024	4,096	4	6.693871	-17.802754	1.12456	true	0.00219	dense	-17.785555	-1.437849	-2.65956	64	0.036488	1,024	63	960	1	0.71736	0.00219	16.661371	success	0.046797	0.000001	under-trained	960	0.00219	0.000461
46	model.layers.6.self_attn.o_proj	0.103141	4,096	4,096	1	5.320054	-14.340628	1.559961	true	0.002016	dense	-14.170697	-1.334167	-2.69558	64	0.046327	4,096	20	4,032	1	0.965993	0.002016	22.983286	success	0.044896	0		4,032	0.002016	0.000693
47	model.layers.6.self_attn.q_proj	0.075063	4,096	4,096	1	8.53185	-22.660099	1.559597	true	0.002208	dense	-22.658375	-1.38822	-2.655942	64	0.040905	4,096	64	4,032	1	0.941481	0.002208	18.523449	success	0.046993	0	under-trained	4,032	0.002208	0.000545
48	model.layers.6.self_attn.v_proj	0.053575	1,024	4,096	4	10.10451	-32.271476	1.135456	true	0.00064	dense	-31.934859	-1.60524	-3.193769	64	0.024818	1,024	57	960	1	1.205922	0.00064	38.773029	success	0.0253	0.000001	under-trained	960	0.00064	0.000349
49	model.layers.7.mlp.down_proj	0.131502	4,096	14,336	3.5	6.106007	-15.723402	1.566253	true	0.00266	dense	-15.247479	-1.027381	-2.575071	64	0.09389	4,096	7	4,032	1	1.929889	0.00266	35.293121	success	0.051578	0.000001	under-trained	4,032	0.00266	0.001575
50	model.layers.7.mlp.gate_proj	0.092991	4,096	14,336	3.5	4.66407	-11.037661	1.561423	true	0.0043	dense	-10.888869	-1.039225	-2.36653	64	0.091364	4,096	9	4,032	1	1.221357	0.0043	21.247375	success	0.065575	0.000001		4,032	0.0043	0.001464
51	model.layers.7.mlp.up_proj	0.083526	4,096	14,336	3.5	4.418851	-10.374051	1.559826	true	0.004491	dense	-10.158229	-1.018919	-2.347681	64	0.095737	4,096	12	4,032	1	0.986937	0.004491	21.318748	success	0.067013	0.000001		4,032	0.004491	0.001482
52	model.layers.7.self_attn.k_proj	0.092425	1,024	4,096	4	6.301261	-18.606098	1.133596	true	0.001115	dense	-18.203055	-1.425027	-2.952758	64	0.037581	1,024	47	960	1	0.773268	0.001115	33.707863	success	0.03339	0.000001	under-trained	960	0.001115	0.00051
53	model.layers.7.self_attn.o_proj	0.075342	4,096	4,096	1	9.002145	-25.429427	1.564116	true	0.001497	dense	-25.246398	-1.327605	-2.824819	64	0.047032	4,096	64	4,032	1	1.000268	0.001497	31.42049	success	0.038689	0	under-trained	4,032	0.001497	0.000639
54	model.layers.7.self_attn.q_proj	0.067324	4,096	4,096	1	8.272918	-22.371443	1.560991	true	0.001976	dense	-22.349378	-1.366129	-2.704178	64	0.04304	4,096	64	4,032	1	0.909115	0.001976	21.779566	success	0.044454	0	under-trained	4,032	0.001976	0.000572
55	model.layers.7.self_attn.v_proj	0.035828	1,024	4,096	4	11.606042	-36.820088	1.135943	true	0.000672	dense	-36.715384	-1.592729	-3.172493	64	0.025543	1,024	52	960	1	1.470793	0.000672	37.998268	success	0.025927	0.000001	under-trained	960	0.000672	0.000369
56	model.layers.8.mlp.down_proj	0.143326	4,096	14,336	3.5	7.349975	-18.750527	1.565933	true	0.002811	dense	-18.478513	-1.021602	-2.551101	64	0.095148	4,096	14	4,032	1	1.697102	0.002811	33.845333	success	0.053021	0.000001	under-trained	4,032	0.002811	0.001474
57	model.layers.8.mlp.gate_proj	0.096562	4,096	14,336	3.5	4.282198	-9.903676	1.559676	true	0.004867	dense	-9.748083	-1.023318	-2.312756	64	0.094772	4,096	9	4,032	1	1.094066	0.004867	19.473211	success	0.069763	0.000001		4,032	0.004867	0.00151
58	model.layers.8.mlp.up_proj	0.101449	4,096	14,336	3.5	4.470252	-10.296513	1.558773	true	0.004973	dense	-10.135558	-1.003884	-2.30334	64	0.09911	4,096	13	4,032	1	0.962475	0.004973	19.927673	success	0.070523	0.000001		4,032	0.004973	0.001524
59	model.layers.8.self_attn.k_proj	0.08686	1,024	4,096	4	6.646015	-16.279518	1.114718	true	0.003552	dense	-16.2774	-1.380645	-2.449516	64	0.041625	1,024	64	960	1	0.705752	0.003552	11.718461	success	0.059599	0.000001	under-trained	960	0.003552	0.000513
60	model.layers.8.self_attn.o_proj	0.068692	4,096	4,096	1	5.494895	-14.968555	1.562716	true	0.001888	dense	-14.748427	-1.30508	-2.724084	64	0.049536	4,096	13	4,032	1	1.24666	0.001888	26.242395	success	0.043447	0		4,032	0.001888	0.000804
61	model.layers.8.self_attn.q_proj	0.089713	4,096	4,096	1	7.238111	-17.969642	1.553421	true	0.003291	dense	-17.967233	-1.307936	-2.482643	64	0.049211	4,096	64	4,032	1	0.779764	0.003291	14.952259	success	0.057369	0	under-trained	4,032	0.003291	0.000627
62	model.layers.8.self_attn.v_proj	0.039211	1,024	4,096	4	10.635006	-33.443697	1.135642	true	0.000717	dense	-33.337394	-1.584424	-3.144681	64	0.026036	1,024	53	960	1	1.32347	0.000717	36.329201	success	0.026771	0.000001	under-trained	960	0.000717	0.000372
63	model.layers.9.mlp.down_proj	0.128309	4,096	14,336	3.5	8.653824	-22.723533	1.566809	true	0.002367	dense	-22.262528	-1.019453	-2.625837	64	0.09562	4,096	15	4,032	1	1.976209	0.002367	40.400311	success	0.04865	0.000001	under-trained	4,032	0.002367	0.001492
64	model.layers.9.mlp.gate_proj	0.08722	4,096	14,336	3.5	4.630853	-10.738622	1.560123	true	0.004798	dense	-10.615177	-1.01836	-2.318929	64	0.095861	4,096	10	4,032	1	1.148177	0.004798	19.978786	success	0.069268	0.000001		4,032	0.004798	0.001535
65	model.layers.9.mlp.up_proj	0.095441	4,096	14,336	3.5	4.509581	-10.436652	1.559562	true	0.004849	dense	-10.254104	-0.994814	-2.314328	64	0.101201	4,096	11	4,032	1	1.058179	0.004849	20.869593	success	0.069636	0.000001		4,032	0.004849	0.001637
66	model.layers.9.self_attn.k_proj	0.083743	1,024	4,096	4	11.978332	-36.619759	1.136268	true	0.000877	dense	-36.102986	-1.390942	-3.057167	64	0.04065	1,024	31	960	1	1.971767	0.000877	46.368629	success	0.029609	0.000001	under-trained	960	0.000877	0.000628
67	model.layers.9.self_attn.o_proj	0.063917	4,096	4,096	1	9.052659	-25.969677	1.56488	true	0.001353	dense	-25.562036	-1.315855	-2.868735	64	0.048322	4,096	64	4,032	1	1.006582	0.001353	35.717358	success	0.036782	0	under-trained	4,032	0.001353	0.000658
68	model.layers.9.self_attn.q_proj	0.068104	4,096	4,096	1	11.947367	-34.271361	1.566557	true	0.001354	dense	-34.250902	-1.33759	-2.868528	64	0.045963	4,096	48	4,032	1	1.580116	0.001354	33.957748	success	0.036791	0	under-trained	4,032	0.001354	0.00067
69	model.layers.9.self_attn.v_proj	0.036851	1,024	4,096	4	11.726856	-37.617797	1.136089	true	0.00062	dense	-37.503763	-1.617514	-3.207833	64	0.024126	1,024	43	960	1	1.63583	0.00062	38.933083	success	0.024893	0.000001	under-trained	960	0.00062	0.000355
70	model.layers.10.mlp.down_proj	0.13738	4,096	14,336	3.5	6.860931	-17.709316	1.565695	true	0.002623	dense	-17.151487	-1.01245	-2.581182	64	0.097174	4,096	15	4,032	1	1.513286	0.002623	37.04528	success	0.051216	0.000001	under-trained	4,032	0.002623	0.0015
71	model.layers.10.mlp.gate_proj	0.083743	4,096	14,336	3.5	3.814121	-8.29112	1.553266	true	0.006702	dense	-8.192316	-1.002268	-2.173796	64	0.099479	4,096	10	4,032	1	0.889903	0.006702	14.843208	success	0.081866	0.000001		4,032	0.006702	0.001555
72	model.layers.10.mlp.up_proj	0.083849	4,096	14,336	3.5	4.076868	-8.950159	1.554181	true	0.006377	dense	-8.837687	-0.985078	-2.195352	64	0.103496	4,096	13	4,032	1	0.85337	0.006377	16.228313	success	0.079859	0.000001		4,032	0.006377	0.001591
73	model.layers.10.self_attn.k_proj	0.056769	1,024	4,096	4	7.818972	-21.698837	1.132445	true	0.001678	dense	-21.653366	-1.368847	-2.775152	64	0.042771	1,024	58	960	1	0.895375	0.001678	25.486191	success	0.040966	0.000001	under-trained	960	0.001678	0.000576
74	model.layers.10.self_attn.o_proj	0.070628	4,096	4,096	1	8.901525	-24.73618	1.56414	true	0.001664	dense	-24.647737	-1.30816	-2.77887	64	0.049186	4,096	64	4,032	1	0.987691	0.001664	29.560369	success	0.040791	0	under-trained	4,032	0.001664	0.000667
75	model.layers.10.self_attn.q_proj	0.091471	4,096	4,096	1	9.544777	-25.029251	1.561299	true	0.002386	dense	-25.027851	-1.31183	-2.622298	64	0.048772	4,096	64	4,032	1	1.068097	0.002386	20.439404	success	0.048848	0	under-trained	4,032	0.002386	0.000663
76	model.layers.10.self_attn.v_proj	0.039781	1,024	4,096	4	13.460733	-43.727946	1.136434	true	0.000564	dense	-43.467368	-1.606999	-3.248556	64	0.024717	1,024	34	960	1	2.136998	0.000564	43.808399	success	0.023753	0.000001	under-trained	960	0.000564	0.000377
77	model.layers.11.mlp.down_proj	0.084076	4,096	14,336	3.5	8.331583	-21.69929	1.566558	true	0.002486	dense	-21.266779	-1.013571	-2.604462	64	0.096923	4,096	16	4,032	1	1.832896	0.002486	38.984375	success	0.049862	0.000001	under-trained	4,032	0.002486	0.00151
78	model.layers.11.mlp.gate_proj	0.124518	4,096	14,336	3.5	3.566869	-7.808087	1.554186	true	0.006471	dense	-7.641942	-0.990355	-2.189059	64	0.102246	4,096	8	4,032	1	0.907525	0.006471	15.801709	success	0.08044	0.000001		4,032	0.006471	0.001697
79	model.layers.11.mlp.up_proj	0.105866	4,096	14,336	3.5	4.111511	-9.150791	1.555739	true	0.005948	dense	-9.000263	-0.978656	-2.225652	64	0.105037	4,096	12	4,032	1	0.898216	0.005948	17.660204	success	0.077121	0.000001		4,032	0.005948	0.001658
80	model.layers.11.self_attn.k_proj	0.076034	1,024	4,096	4	6.886649	-17.54321	1.125219	true	0.002835	dense	-17.53927	-1.338794	-2.547423	64	0.045836	1,024	64	960	1	0.735831	0.002835	16.166996	success	0.053246	0.000001	under-trained	960	0.002835	0.000583
81	model.layers.11.self_attn.o_proj	0.082475	4,096	4,096	1	9.621523	-27.295947	1.564701	true	0.001456	dense	-27.014932	-1.307915	-2.836967	64	0.049214	4,096	64	4,032	1	1.07769	0.001456	33.810543	success	0.038152	0	under-trained	4,032	0.001456	0.000676
82	model.layers.11.self_attn.q_proj	0.092576	4,096	4,096	1	3.737231	-9.223967	1.553536	true	0.003403	dense	-9.073385	-1.267686	-2.468129	64	0.05399	4,096	10	4,032	1	0.865588	0.003403	15.865086	success	0.058336	0		4,032	0.003403	0.00086
83	model.layers.11.self_attn.v_proj	0.045068	1,024	4,096	4	12.227346	-39.194857	1.136222	true	0.000623	dense	-38.929056	-1.581387	-3.205508	64	0.026219	1,024	40	960	1	1.775199	0.000623	42.08437	success	0.02496	0.000001	under-trained	960	0.000623	0.00039
84	model.layers.12.mlp.down_proj	0.071737	4,096	14,336	3.5	10.463299	-27.652009	1.567254	true	0.002276	dense	-27.278975	-1.01537	-2.642762	64	0.096523	4,096	17	4,032	1	2.295187	0.002276	42.402534	success	0.047711	0.000001	under-trained	4,032	0.002276	0.001505
85	model.layers.12.mlp.gate_proj	0.093378	4,096	14,336	3.5	3.726353	-8.2903	1.556028	true	0.00596	dense	-8.120935	-0.997856	-2.224776	64	0.100495	4,096	8	4,032	1	0.963911	0.00596	16.8624	success	0.077199	0.000001		4,032	0.00596	0.001679
86	model.layers.12.mlp.up_proj	0.084262	4,096	14,336	3.5	4.286353	-9.666749	1.557471	true	0.005556	dense	-9.516003	-0.984565	-2.255239	64	0.103618	4,096	11	4,032	1	0.990873	0.005556	18.64978	success	0.074538	0.000001		4,032	0.005556	0.001669
87	model.layers.12.self_attn.k_proj	0.048592	1,024	4,096	4	5.293701	-15.09437	1.131777	true	0.001408	dense	-14.339401	-1.297373	-2.851383	64	0.050423	1,024	64	960	1	0.536713	0.001408	35.810429	success	0.037524	0.000001		960	0.001408	0.00061
88	model.layers.12.self_attn.o_proj	0.036461	4,096	4,096	1	10.498903	-30.738891	1.566372	true	0.001181	dense	-30.349195	-1.325973	-2.927819	64	0.047209	4,096	64	4,032	1	1.187363	0.001181	39.980358	success	0.034363	0	under-trained	4,032	0.001181	0.000659
89	model.layers.12.self_attn.q_proj	0.059794	4,096	4,096	1	10.446452	-27.443894	1.562977	true	0.00236	dense	-27.443376	-1.285311	-2.627102	64	0.051843	4,096	62	4,032	1	1.199701	0.00236	21.968027	success	0.048579	0	under-trained	4,032	0.00236	0.000719
90	model.layers.12.self_attn.v_proj	0.056912	1,024	4,096	4	14.830225	-48.769316	1.136817	true	0.000515	dense	-48.376759	-1.608922	-3.288508	64	0.024608	1,024	40	960	1	2.186751	0.000515	47.817432	success	0.022685	0.000001	under-trained	960	0.000515	0.000371
91	model.layers.13.mlp.down_proj	0.101172	4,096	14,336	3.5	9.722754	-25.602905	1.566878	true	0.002326	dense	-25.09933	-1.007937	-2.633298	64	0.098189	4,096	21	4,032	1	1.903461	0.002326	42.204708	success	0.048234	0.000001	under-trained	4,032	0.002326	0.001502
92	model.layers.13.mlp.gate_proj	0.076844	4,096	14,336	3.5	4.195623	-9.25822	1.555494	true	0.006214	dense	-9.17138	-0.996401	-2.206638	64	0.100832	4,096	12	4,032	1	0.922497	0.006214	16.226952	success	0.078828	0.000001		4,032	0.006214	0.001561
93	model.layers.13.mlp.up_proj	0.072975	4,096	14,336	3.5	4.54178	-10.238768	1.558146	true	0.005567	dense	-10.13164	-0.983272	-2.254352	64	0.103927	4,096	12	4,032	1	1.022424	0.005567	18.667231	success	0.074615	0.000001		4,032	0.005567	0.001665
94	model.layers.13.self_attn.k_proj	0.074733	1,024	4,096	4	8.151952	-22.214526	1.131022	true	0.001883	dense	-22.195854	-1.377887	-2.725056	64	0.04189	1,024	63	960	1	0.901061	0.001883	22.241776	success	0.043398	0.000001	under-trained	960	0.001883	0.000559
95	model.layers.13.self_attn.o_proj	0.030219	4,096	4,096	1	10.243985	-29.651683	1.566539	true	0.001275	dense	-29.323853	-1.290212	-2.894546	64	0.051261	4,096	64	4,032	1	1.155498	0.001275	40.209957	success	0.035705	0	under-trained	4,032	0.001275	0.000714
96	model.layers.13.self_attn.q_proj	0.089999	4,096	4,096	1	9.241785	-23.352984	1.559237	true	0.002972	dense	-23.352611	-1.2781	-2.526891	64	0.052711	4,096	64	4,032	1	1.030223	0.002972	17.733349	success	0.05452	0	under-trained	4,032	0.002972	0.00071
97	model.layers.13.self_attn.v_proj	0.06204	1,024	4,096	4	17.463952	-57.035094	1.136875	true	0.000542	dense	-56.694075	-1.577319	-3.265876	64	0.026466	1,024	24	960	1	3.36069	0.000542	48.815338	success	0.023284	0.000001	under-trained	960	0.000542	0.000418
98	model.layers.14.mlp.down_proj	0.082979	4,096	14,336	3.5	11.637098	-31.044017	1.567351	true	0.002149	dense	-30.417835	-0.998153	-2.667677	64	0.100426	4,096	24	4,032	1	2.171288	0.002149	46.722298	success	0.046362	0.000001	under-trained	4,032	0.002149	0.001538
99	model.layers.14.mlp.gate_proj	0.106847	4,096	14,336	3.5	4.425835	-9.716215	1.556191	true	0.006378	dense	-9.659478	-0.990614	-2.19534	64	0.102185	4,096	9	4,032	1	1.141945	0.006378	16.022362	success	0.07986	0.000001		4,032	0.006378	0.001713

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