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train · 224 rows

layer_id int64 0 223	name stringlengths 26 32	D float64 0.03 0.12	M int64 1.02k 4.1k	N int64 4.1k 14.3k	Q float64 1 4	alpha float64 2.98 23.9	alpha_weighted float64 -65.71 -6.41	entropy float64 1.11 1.57	has_esd bool 1 class	lambda_max float32 0 0.02	layer_type stringclasses 1 value	log_alpha_norm float64 -64.96 -5.95	log_norm float32 -1.43 -0.48	log_spectral_norm float32 -2.81 -1.77	matrix_rank int64 64 64	norm float32 0.04 0.33	num_evals int64 1.02k 4.1k	num_pl_spikes int64 10 64	rank_loss int64 960 4.03k	rf int64 1 1	sigma float64 0.25 5.88	spectral_norm float32 0 0.02	stable_rank float32 7.52 56.2	status stringclasses 1 value	sv_max float64 0.04 0.13	sv_min float64 0 0	warning stringclasses 2 values	weak_rank_loss int64 960 4.03k	xmax float64 0 0.02	xmin float64 0 0
0	model.layers.0.mlp.down_proj	0.044372	4,096	14,336	3.5	8.365172	-19.331526	1.565136	true	0.004887	dense	-18.927617	-0.749923	-2.310954	64	0.17786	4,096	64	4,032	1	0.920646	0.004887	36.394131	success	0.069907	0.000001	under-trained	4,032	0.004887	0.002397
1	model.layers.0.mlp.gate_proj	0.044792	4,096	14,336	3.5	4.921705	-11.727318	1.558989	true	0.004142	dense	-11.388952	-0.983228	-2.382775	64	0.103937	4,096	27	4,032	1	0.754733	0.004142	25.092697	success	0.064359	0.000001		4,032	0.004142	0.001486
2	model.layers.0.mlp.up_proj	0.05879	4,096	14,336	3.5	5.270882	-12.216789	1.559112	true	0.004811	dense	-12.024244	-0.950149	-2.317788	64	0.112163	4,096	32	4,032	1	0.754992	0.004811	23.315189	success	0.069359	0.000001		4,032	0.004811	0.001558
3	model.layers.0.self_attn.k_proj	0.044862	1,024	4,096	4	3.967196	-10.618157	1.116284	true	0.002106	dense	-10.36955	-1.432019	-2.676489	64	0.036981	1,024	40	960	1	0.469155	0.002106	17.557785	success	0.045894	0.000001		960	0.002106	0.000457
4	model.layers.0.self_attn.o_proj	0.071946	4,096	4,096	1	3.15045	-6.414638	1.531436	true	0.009202	dense	-5.951533	-0.820385	-2.036102	64	0.151222	4,096	45	4,032	1	0.32057	0.009202	16.43302	success	0.095929	0		4,032	0.009202	0.001521
5	model.layers.0.self_attn.q_proj	0.035535	4,096	4,096	1	2.977482	-6.897628	1.521928	true	0.004824	dense	-6.518055	-1.191919	-2.316598	64	0.064281	4,096	64	4,032	1	0.247185	0.004824	13.325367	success	0.069455	0		4,032	0.004824	0.000518
6	model.layers.0.self_attn.v_proj	0.045686	1,024	4,096	4	3.300158	-8.03369	1.105158	true	0.003678	dense	-7.724496	-1.274459	-2.434335	64	0.053155	1,024	24	960	1	0.469518	0.003678	14.450284	success	0.06065	0.000001		960	0.003678	0.000702
7	model.layers.1.mlp.down_proj	0.075648	4,096	14,336	3.5	7.65575	-16.933677	1.565563	true	0.006139	dense	-16.84096	-0.733272	-2.21189	64	0.184811	4,096	13	4,032	1	1.845973	0.006139	30.103548	success	0.078353	0.000001	under-trained	4,032	0.006139	0.002963
8	model.layers.1.mlp.gate_proj	0.112535	4,096	14,336	3.5	3.981704	-8.683508	1.556923	true	0.006594	dense	-8.361143	-0.866137	-2.180852	64	0.136102	4,096	11	4,032	1	0.899018	0.006594	20.640265	success	0.081203	0.000001		4,032	0.006594	0.002157
9	model.layers.1.mlp.up_proj	0.058219	4,096	14,336	3.5	5.127727	-11.404952	1.561835	true	0.005968	dense	-11.187414	-0.83321	-2.224173	64	0.146822	4,096	13	4,032	1	1.144825	0.005968	24.601585	success	0.077253	0.000001		4,032	0.005968	0.002357
10	model.layers.1.self_attn.k_proj	0.043356	1,024	4,096	4	4.768239	-12.602271	1.124037	true	0.002275	dense	-12.498928	-1.378174	-2.642962	64	0.041863	1,024	56	960	1	0.503552	0.002275	18.398703	success	0.0477	0.000001		960	0.002275	0.000498
11	model.layers.1.self_attn.o_proj	0.053403	4,096	4,096	1	3.869334	-7.790337	1.546909	true	0.009697	dense	-7.571464	-0.793234	-2.013354	64	0.160978	4,096	32	4,032	1	0.507231	0.009697	16.600451	success	0.098474	0		4,032	0.009697	0.00206
12	model.layers.1.self_attn.q_proj	0.040165	4,096	4,096	1	4.360187	-10.607257	1.54881	true	0.003692	dense	-10.532897	-1.257076	-2.432753	64	0.055325	4,096	62	4,032	1	0.426744	0.003692	14.985688	success	0.060761	0		4,032	0.003692	0.000609
13	model.layers.1.self_attn.v_proj	0.029854	1,024	4,096	4	5.583189	-15.041438	1.130228	true	0.002023	dense	-14.569543	-1.219971	-2.694058	64	0.06026	1,024	53	960	1	0.629549	0.002023	29.791128	success	0.044975	0.000001		960	0.002023	0.000769
14	model.layers.2.mlp.down_proj	0.055346	4,096	14,336	3.5	15.095443	-34.764815	1.567153	true	0.004977	dense	-34.647397	-0.697174	-2.303001	64	0.200829	4,096	64	4,032	1	1.76193	0.004977	40.348392	success	0.07055	0.000001	under-trained	4,032	0.004977	0.002909
15	model.layers.2.mlp.gate_proj	0.069836	4,096	14,336	3.5	7.014292	-15.802	1.564927	true	0.005587	dense	-15.72346	-0.811401	-2.252829	64	0.154383	4,096	13	4,032	1	1.668065	0.005587	27.63302	success	0.074746	0.000001	under-trained	4,032	0.005587	0.002453
16	model.layers.2.mlp.up_proj	0.058174	4,096	14,336	3.5	6.622721	-14.627589	1.564325	true	0.006184	dense	-14.520681	-0.773311	-2.208698	64	0.168535	4,096	15	4,032	1	1.45178	0.006184	27.251282	success	0.078641	0.000001	under-trained	4,032	0.006184	0.002648
17	model.layers.2.self_attn.k_proj	0.059239	1,024	4,096	4	8.314302	-22.293065	1.133351	true	0.002083	dense	-22.094893	-1.15985	-2.681291	64	0.069207	1,024	15	960	1	1.888545	0.002083	33.223221	success	0.045641	0.000001	under-trained	960	0.002083	0.001193
18	model.layers.2.self_attn.o_proj	0.043211	4,096	4,096	1	4.301974	-9.517501	1.553272	true	0.006133	dense	-9.028854	-0.828736	-2.212357	64	0.148342	4,096	58	4,032	1	0.43357	0.006133	24.189142	success	0.078311	0		4,032	0.006133	0.001669
19	model.layers.2.self_attn.q_proj	0.036099	4,096	4,096	1	7.774757	-19.31455	1.563217	true	0.003279	dense	-19.277754	-1.073739	-2.484264	64	0.084384	4,096	43	4,032	1	1.033141	0.003279	25.735031	success	0.057262	0	under-trained	4,032	0.003279	0.001195
20	model.layers.2.self_attn.v_proj	0.039486	1,024	4,096	4	5.728909	-15.094938	1.131631	true	0.002318	dense	-14.438458	-1.097779	-2.634871	64	0.07984	1,024	62	960	1	0.600572	0.002318	34.442307	success	0.048146	0.000001		960	0.002318	0.000994
21	model.layers.3.mlp.down_proj	0.079373	4,096	14,336	3.5	15.131404	-33.785049	1.566826	true	0.005851	dense	-33.759555	-0.672238	-2.232777	64	0.212697	4,096	64	4,032	1	1.766426	0.005851	36.352871	success	0.076491	0.000001	under-trained	4,032	0.005851	0.003079
22	model.layers.3.mlp.gate_proj	0.089666	4,096	14,336	3.5	6.122937	-13.159611	1.563872	true	0.007092	dense	-13.073512	-0.752022	-2.149232	64	0.177002	4,096	10	4,032	1	1.620015	0.007092	24.958031	success	0.084214	0.000001	under-trained	4,032	0.007092	0.002905
23	model.layers.3.mlp.up_proj	0.097207	4,096	14,336	3.5	7.223045	-15.33708	1.56381	true	0.007527	dense	-15.292052	-0.716858	-2.123354	64	0.191929	4,096	19	4,032	1	1.427664	0.007527	25.497366	success	0.086761	0.000001	under-trained	4,032	0.007527	0.002949
24	model.layers.3.self_attn.k_proj	0.053499	1,024	4,096	4	6.338608	-17.415424	1.130776	true	0.001788	dense	-17.103588	-1.292547	-2.747516	64	0.050986	1,024	64	960	1	0.667326	0.001788	28.508137	success	0.04229	0.000001	under-trained	960	0.001788	0.000645
25	model.layers.3.self_attn.o_proj	0.031086	4,096	4,096	1	5.812814	-13.425333	1.561421	true	0.004902	dense	-13.015641	-0.83379	-2.30961	64	0.146626	4,096	62	4,032	1	0.611228	0.004902	29.910252	success	0.070016	0		4,032	0.004902	0.001826
26	model.layers.3.self_attn.q_proj	0.033947	4,096	4,096	1	5.52264	-13.971607	1.559661	true	0.002952	dense	-13.88557	-1.195202	-2.529878	64	0.063797	4,096	62	4,032	1	0.574376	0.002952	21.61108	success	0.054333	0		4,032	0.002952	0.000781
27	model.layers.3.self_attn.v_proj	0.031332	1,024	4,096	4	8.437461	-21.783879	1.1343	true	0.002619	dense	-21.660868	-1.074053	-2.581805	64	0.084323	1,024	43	960	1	1.134202	0.002619	32.192299	success	0.05118	0.000001	under-trained	960	0.002619	0.001206
28	model.layers.4.mlp.down_proj	0.076604	4,096	14,336	3.5	14.993147	-33.140575	1.566824	true	0.006161	dense	-33.082934	-0.636412	-2.210382	64	0.230987	4,096	64	4,032	1	1.749143	0.006161	37.494659	success	0.078489	0.000001	under-trained	4,032	0.006161	0.003341
29	model.layers.4.mlp.gate_proj	0.071158	4,096	14,336	3.5	5.423075	-11.23735	1.562094	true	0.00847	dense	-11.120026	-0.70997	-2.072136	64	0.194998	4,096	12	4,032	1	1.276832	0.00847	23.02322	success	0.092031	0.000001		4,032	0.00847	0.003126
30	model.layers.4.mlp.up_proj	0.058521	4,096	14,336	3.5	6.87642	-14.190751	1.562732	true	0.008636	dense	-14.10596	-0.656931	-2.063683	64	0.220328	4,096	29	4,032	1	1.091224	0.008636	25.512463	success	0.092931	0.000001	under-trained	4,032	0.008636	0.003203
31	model.layers.4.self_attn.k_proj	0.07151	1,024	4,096	4	8.27638	-22.574322	1.132434	true	0.001873	dense	-22.013693	-1.143497	-2.72756	64	0.071863	1,024	22	960	1	1.55133	0.001873	38.37632	success	0.043273	0.000001	under-trained	960	0.001873	0.001211
32	model.layers.4.self_attn.o_proj	0.039916	4,096	4,096	1	5.481292	-12.934991	1.561933	true	0.004367	dense	-12.256102	-0.825011	-2.359844	64	0.14962	4,096	62	4,032	1	0.569125	0.004367	34.263561	success	0.066081	0		4,032	0.004367	0.001837
33	model.layers.4.self_attn.q_proj	0.043186	4,096	4,096	1	7.05384	-17.32022	1.56158	true	0.003504	dense	-17.280596	-1.078193	-2.455431	64	0.083523	4,096	22	4,032	1	1.290683	0.003504	23.83625	success	0.059195	0	under-trained	4,032	0.003504	0.001334
34	model.layers.4.self_attn.v_proj	0.051123	1,024	4,096	4	8.01902	-21.363418	1.13487	true	0.002167	dense	-20.8389	-1.065824	-2.664093	64	0.085936	1,024	41	960	1	1.096187	0.002167	39.652363	success	0.046554	0.000001	under-trained	960	0.002167	0.001234
35	model.layers.5.mlp.down_proj	0.064079	4,096	14,336	3.5	15.944951	-34.872978	1.567136	true	0.0065	dense	-34.853326	-0.608785	-2.187086	64	0.246158	4,096	64	4,032	1	1.868119	0.0065	37.870461	success	0.080623	0.000001	under-trained	4,032	0.0065	0.003581
36	model.layers.5.mlp.gate_proj	0.096163	4,096	14,336	3.5	5.903078	-12.108724	1.562384	true	0.008887	dense	-12.002394	-0.671732	-2.051256	64	0.212945	4,096	16	4,032	1	1.225769	0.008887	23.96207	success	0.09427	0.000001		4,032	0.008887	0.003285
37	model.layers.5.mlp.up_proj	0.060143	4,096	14,336	3.5	6.366293	-12.982274	1.56298	true	0.009136	dense	-12.837507	-0.616751	-2.03922	64	0.241685	4,096	20	4,032	1	1.19994	0.009136	26.452679	success	0.095585	0.000001	under-trained	4,032	0.009136	0.003693
38	model.layers.5.self_attn.k_proj	0.042857	1,024	4,096	4	6.45947	-17.316833	1.133314	true	0.002085	dense	-16.710907	-1.118405	-2.680844	64	0.076137	1,024	59	960	1	0.710762	0.002085	36.512318	success	0.045664	0.000001	under-trained	960	0.002085	0.00099
39	model.layers.5.self_attn.o_proj	0.03663	4,096	4,096	1	7.81447	-19.20972	1.565988	true	0.003482	dense	-18.370583	-0.812658	-2.458224	64	0.153937	4,096	51	4,032	1	0.954217	0.003482	44.214661	success	0.059005	0	under-trained	4,032	0.003482	0.00213
40	model.layers.5.self_attn.q_proj	0.039347	4,096	4,096	1	7.181912	-17.746361	1.563375	true	0.003381	dense	-17.677551	-1.044679	-2.47098	64	0.090224	4,096	38	4,032	1	1.002839	0.003381	26.687077	success	0.058145	0	under-trained	4,032	0.003381	0.001293
41	model.layers.5.self_attn.v_proj	0.074037	1,024	4,096	4	9.685775	-26.449586	1.13634	true	0.001859	dense	-25.600858	-1.046485	-2.730766	64	0.089849	1,024	56	960	1	1.160686	0.001859	48.337158	success	0.043114	0.000001	under-trained	960	0.001859	0.001266
42	model.layers.6.mlp.down_proj	0.095639	4,096	14,336	3.5	14.635101	-31.146394	1.566578	true	0.007444	dense	-31.129475	-0.582811	-2.128198	64	0.26133	4,096	64	4,032	1	1.704388	0.007444	35.10651	success	0.086278	0.000001	under-trained	4,032	0.007444	0.00377
43	model.layers.6.mlp.gate_proj	0.069643	4,096	14,336	3.5	5.839907	-11.692018	1.561022	true	0.009952	dense	-11.543849	-0.621106	-2.00209	64	0.239273	4,096	26	4,032	1	0.949184	0.009952	24.042736	success	0.09976	0.000001		4,032	0.009952	0.003457
44	model.layers.6.mlp.up_proj	0.071441	4,096	14,336	3.5	5.83869	-11.695706	1.56181	true	0.009928	dense	-11.448427	-0.575978	-2.003139	64	0.265474	4,096	23	4,032	1	1.008937	0.009928	26.739985	success	0.099639	0.000001		4,032	0.009928	0.003958
45	model.layers.6.self_attn.k_proj	0.053588	1,024	4,096	4	6.589289	-17.636502	1.133221	true	0.002106	dense	-17.076734	-1.121298	-2.676541	64	0.075631	1,024	64	960	1	0.698661	0.002106	35.912281	success	0.045891	0.000001	under-trained	960	0.002106	0.000972
46	model.layers.6.self_attn.o_proj	0.028815	4,096	4,096	1	6.851371	-16.127938	1.564554	true	0.004426	dense	-15.613682	-0.798362	-2.353972	64	0.159088	4,096	64	4,032	1	0.731421	0.004426	35.942707	success	0.066529	0	under-trained	4,032	0.004426	0.002065
47	model.layers.6.self_attn.q_proj	0.045633	4,096	4,096	1	6.070915	-14.817944	1.562566	true	0.003624	dense	-14.683584	-1.024928	-2.440809	64	0.094422	4,096	64	4,032	1	0.633864	0.003624	26.054392	success	0.0602	0	under-trained	4,032	0.003624	0.001186
48	model.layers.6.self_attn.v_proj	0.04742	1,024	4,096	4	10.374022	-27.161139	1.135434	true	0.002409	dense	-26.936849	-1.031026	-2.618188	64	0.093105	1,024	20	960	1	2.096095	0.002409	38.65107	success	0.04908	0.000001	under-trained	960	0.002409	0.001501
49	model.layers.7.mlp.down_proj	0.063456	4,096	14,336	3.5	15.614345	-33.627184	1.567221	true	0.007021	dense	-33.590977	-0.559208	-2.153608	64	0.275926	4,096	64	4,032	1	1.826793	0.007021	39.300701	success	0.083791	0.000001	under-trained	4,032	0.007021	0.004009
50	model.layers.7.mlp.gate_proj	0.054805	4,096	14,336	3.5	5.579458	-11.013746	1.561041	true	0.010617	dense	-10.847327	-0.592793	-1.973981	64	0.255392	4,096	21	4,032	1	0.99932	0.010617	24.05406	success	0.103041	0.000001		4,032	0.010617	0.003834
51	model.layers.7.mlp.up_proj	0.063687	4,096	14,336	3.5	5.60456	-11.151875	1.562231	true	0.010238	dense	-10.824994	-0.543541	-1.989786	64	0.286062	4,096	19	4,032	1	1.056359	0.010238	27.941221	success	0.101183	0.000001		4,032	0.010238	0.004375
52	model.layers.7.self_attn.k_proj	0.095712	1,024	4,096	4	10.705249	-27.8816	1.133918	true	0.002486	dense	-27.546094	-1.011718	-2.604479	64	0.097338	1,024	18	960	1	2.287549	0.002486	39.152649	success	0.049861	0.000001	under-trained	960	0.002486	0.001678
53	model.layers.7.self_attn.o_proj	0.065757	4,096	4,096	1	11.30707	-27.335589	1.566889	true	0.003823	dense	-26.685796	-0.751225	-2.417566	64	0.177327	4,096	25	4,032	1	2.061414	0.003823	46.381084	success	0.061833	0	under-trained	4,032	0.003823	0.002786
54	model.layers.7.self_attn.q_proj	0.025897	4,096	4,096	1	7.524983	-17.814964	1.563334	true	0.004291	dense	-17.77534	-0.956906	-2.367442	64	0.110432	4,096	39	4,032	1	1.044834	0.004291	25.73575	success	0.065506	0	under-trained	4,032	0.004291	0.001579
55	model.layers.7.self_attn.v_proj	0.073396	1,024	4,096	4	15.267755	-41.123873	1.13667	true	0.002025	dense	-40.442663	-0.988075	-2.693511	64	0.102784	1,024	26	960	1	2.798137	0.002025	50.750072	success	0.045003	0.000001	under-trained	960	0.002025	0.001623
56	model.layers.8.mlp.down_proj	0.066821	4,096	14,336	3.5	14.244871	-30.541354	1.567048	true	0.007178	dense	-30.44064	-0.543448	-2.144025	64	0.286123	4,096	64	4,032	1	1.655609	0.007178	39.863625	success	0.08472	0.000001	under-trained	4,032	0.007178	0.004125
57	model.layers.8.mlp.gate_proj	0.057102	4,096	14,336	3.5	5.478192	-10.632148	1.56052	true	0.01146	dense	-10.447779	-0.562441	-1.940813	64	0.273879	4,096	22	4,032	1	0.954754	0.01146	23.898603	success	0.107052	0.000001		4,032	0.01146	0.00408
58	model.layers.8.mlp.up_proj	0.052789	4,096	14,336	3.5	5.877397	-11.587908	1.562137	true	0.010676	dense	-11.257199	-0.517431	-1.971605	64	0.303787	4,096	25	4,032	1	0.975479	0.010676	28.456011	success	0.103323	0.000001		4,032	0.010676	0.004476
59	model.layers.8.self_attn.k_proj	0.064081	1,024	4,096	4	6.659156	-17.477803	1.132918	true	0.002373	dense	-16.862688	-1.065404	-2.624627	64	0.086019	1,024	64	960	1	0.707395	0.002373	36.242973	success	0.048718	0.000001	under-trained	960	0.002373	0.001107
60	model.layers.8.self_attn.o_proj	0.050797	4,096	4,096	1	9.906003	-23.957714	1.566807	true	0.003815	dense	-23.247362	-0.75672	-2.418505	64	0.175098	4,096	39	4,032	1	1.426102	0.003815	45.897057	success	0.061766	0	under-trained	4,032	0.003815	0.002583
61	model.layers.8.self_attn.q_proj	0.064969	4,096	4,096	1	6.653043	-16.193501	1.563653	true	0.003681	dense	-16.003354	-0.962644	-2.433999	64	0.108982	4,096	40	4,032	1	0.893825	0.003681	29.604328	success	0.060674	0	under-trained	4,032	0.003681	0.001538
62	model.layers.8.self_attn.v_proj	0.035499	1,024	4,096	4	12.053037	-31.042204	1.135992	true	0.002658	dense	-30.961366	-0.991929	-2.575467	64	0.101876	1,024	28	960	1	2.088828	0.002658	38.329998	success	0.051554	0.000001	under-trained	960	0.002658	0.001577
63	model.layers.9.mlp.down_proj	0.044913	4,096	14,336	3.5	15.129803	-32.638446	1.567325	true	0.006963	dense	-32.531992	-0.537594	-2.157229	64	0.290005	4,096	64	4,032	1	1.766225	0.006963	41.651878	success	0.083442	0.000001	under-trained	4,032	0.006963	0.004205
64	model.layers.9.mlp.gate_proj	0.05434	4,096	14,336	3.5	5.696961	-11.08356	1.561272	true	0.011336	dense	-10.893989	-0.545201	-1.945521	64	0.28497	4,096	24	4,032	1	0.958763	0.011336	25.137403	success	0.106473	0.000001		4,032	0.011336	0.004224
65	model.layers.9.mlp.up_proj	0.043738	4,096	14,336	3.5	6.431358	-12.675255	1.562701	true	0.010694	dense	-12.390135	-0.503689	-1.970852	64	0.313553	4,096	37	4,032	1	0.89291	0.010694	29.319954	success	0.103413	0.000001	under-trained	4,032	0.010694	0.00438
66	model.layers.9.self_attn.k_proj	0.064809	1,024	4,096	4	6.66346	-16.885243	1.134151	true	0.002924	dense	-16.205545	-0.939375	-2.534005	64	0.114981	1,024	46	960	1	0.835032	0.002924	39.32151	success	0.054075	0.000001	under-trained	960	0.002924	0.001582
67	model.layers.9.self_attn.o_proj	0.044989	4,096	4,096	1	11.027726	-26.397476	1.567061	true	0.004039	dense	-25.734566	-0.722971	-2.393737	64	0.189247	4,096	37	4,032	1	1.648548	0.004039	46.85614	success	0.063552	0	under-trained	4,032	0.004039	0.002835
68	model.layers.9.self_attn.q_proj	0.041058	4,096	4,096	1	8.645273	-20.432758	1.564777	true	0.004331	dense	-20.36518	-0.882691	-2.36346	64	0.131011	4,096	27	4,032	1	1.471333	0.004331	30.253063	success	0.065807	0	under-trained	4,032	0.004331	0.002014
69	model.layers.9.self_attn.v_proj	0.048063	1,024	4,096	4	17.18794	-45.376271	1.136577	true	0.002291	dense	-45.223033	-0.980125	-2.640006	64	0.104683	1,024	18	960	1	3.815534	0.002291	45.696308	success	0.047863	0.000001	under-trained	960	0.002291	0.001711
70	model.layers.10.mlp.down_proj	0.057979	4,096	14,336	3.5	13.5763	-29.123454	1.56707	true	0.007159	dense	-28.963528	-0.534644	-2.145169	64	0.291982	4,096	64	4,032	1	1.572037	0.007159	40.787243	success	0.084609	0.000001	under-trained	4,032	0.007159	0.004192
71	model.layers.10.mlp.gate_proj	0.047552	4,096	14,336	3.5	5.482743	-10.2929	1.558314	true	0.013264	dense	-10.129917	-0.529934	-1.877327	64	0.295166	4,096	38	4,032	1	0.727197	0.013264	22.253223	success	0.115169	0.000001		4,032	0.013264	0.00397
72	model.layers.10.mlp.up_proj	0.054996	4,096	14,336	3.5	6.165837	-11.655581	1.559779	true	0.012872	dense	-11.462149	-0.498474	-1.890349	64	0.317341	4,096	51	4,032	1	0.723362	0.012872	24.653248	success	0.113456	0.000001	under-trained	4,032	0.012872	0.004137
73	model.layers.10.self_attn.k_proj	0.050952	1,024	4,096	4	6.928386	-17.629741	1.133472	true	0.002854	dense	-17.102107	-0.987223	-2.544567	64	0.102986	1,024	63	960	1	0.746906	0.002854	36.08643	success	0.053422	0.000001	under-trained	960	0.002854	0.001342
74	model.layers.10.self_attn.o_proj	0.039311	4,096	4,096	1	8.08292	-17.884937	1.564299	true	0.006128	dense	-17.605788	-0.702513	-2.212683	64	0.198375	4,096	60	4,032	1	0.914401	0.006128	32.37204	success	0.078281	0	under-trained	4,032	0.006128	0.002677
75	model.layers.10.self_attn.q_proj	0.060079	4,096	4,096	1	8.799813	-21.045494	1.564504	true	0.004059	dense	-20.972091	-0.900797	-2.391584	64	0.125662	4,096	23	4,032	1	1.626373	0.004059	30.95904	success	0.06371	0	under-trained	4,032	0.004059	0.002024
76	model.layers.10.self_attn.v_proj	0.044839	1,024	4,096	4	11.125341	-28.627597	1.135937	true	0.002672	dense	-28.327318	-0.957065	-2.573188	64	0.110391	1,024	38	960	1	1.642547	0.002672	41.316521	success	0.05169	0.000001	under-trained	960	0.002672	0.001649
77	model.layers.11.mlp.down_proj	0.056991	4,096	14,336	3.5	12.935681	-27.08163	1.566674	true	0.008062	dense	-27.024306	-0.530032	-2.09356	64	0.2951	4,096	64	4,032	1	1.49196	0.008062	36.604042	success	0.089788	0.000001	under-trained	4,032	0.008062	0.004213
78	model.layers.11.mlp.gate_proj	0.050258	4,096	14,336	3.5	5.273043	-10.023329	1.559382	true	0.012564	dense	-9.778413	-0.518389	-1.900863	64	0.303117	4,096	24	4,032	1	0.872231	0.012564	24.125341	success	0.11209	0.000001		4,032	0.012564	0.004489
79	model.layers.11.mlp.up_proj	0.044841	4,096	14,336	3.5	6.025806	-11.473937	1.560522	true	0.01247	dense	-11.245172	-0.493493	-1.904133	64	0.321001	4,096	43	4,032	1	0.766428	0.01247	25.741854	success	0.111669	0.000001	under-trained	4,032	0.01247	0.004309
80	model.layers.11.self_attn.k_proj	0.060456	1,024	4,096	4	6.757037	-17.235079	1.134413	true	0.002814	dense	-16.415399	-0.930107	-2.550686	64	0.117461	1,024	53	960	1	0.79079	0.002814	41.742561	success	0.053047	0.000001	under-trained	960	0.002814	0.001579
81	model.layers.11.self_attn.o_proj	0.032158	4,096	4,096	1	11.158902	-26.44295	1.567071	true	0.004269	dense	-26.008332	-0.724837	-2.369673	64	0.188435	4,096	41	4,032	1	1.586554	0.004269	44.140343	success	0.065338	0	under-trained	4,032	0.004269	0.002785
82	model.layers.11.self_attn.q_proj	0.045011	4,096	4,096	1	9.484317	-22.596014	1.565531	true	0.004145	dense	-22.532848	-0.872075	-2.382461	64	0.134253	4,096	24	4,032	1	1.731854	0.004145	32.388157	success	0.064383	0	under-trained	4,032	0.004145	0.002107
83	model.layers.11.self_attn.v_proj	0.101216	1,024	4,096	4	15.683077	-41.547668	1.136782	true	0.002243	dense	-40.842064	-0.936095	-2.649204	64	0.115852	1,024	26	960	1	2.879588	0.002243	51.654556	success	0.047359	0.000001	under-trained	960	0.002243	0.001827
84	model.layers.12.mlp.down_proj	0.032652	4,096	14,336	3.5	14.15541	-30.704631	1.567403	true	0.006775	dense	-30.458001	-0.529252	-2.169109	64	0.295629	4,096	64	4,032	1	1.644426	0.006775	43.637211	success	0.082309	0.000001	under-trained	4,032	0.006775	0.004265
85	model.layers.12.mlp.gate_proj	0.03655	4,096	14,336	3.5	5.6251	-10.731252	1.560177	true	0.012367	dense	-10.539884	-0.521513	-1.907744	64	0.300945	4,096	33	4,032	1	0.805127	0.012367	24.334984	success	0.111206	0.000001		4,032	0.012367	0.004206
86	model.layers.12.mlp.up_proj	0.043853	4,096	14,336	3.5	5.902476	-11.456355	1.562021	true	0.011457	dense	-11.172447	-0.496813	-1.94094	64	0.318557	4,096	29	4,032	1	0.910367	0.011457	27.805277	success	0.107036	0.000001		4,032	0.011457	0.004585
87	model.layers.12.self_attn.k_proj	0.090697	1,024	4,096	4	5.803976	-14.697743	1.134736	true	0.002935	dense	-13.539768	-0.862901	-2.532357	64	0.13712	1,024	64	960	1	0.600497	0.002935	46.715065	success	0.054178	0.000001		960	0.002935	0.00172
88	model.layers.12.self_attn.o_proj	0.072164	4,096	4,096	1	12.682624	-30.576485	1.567453	true	0.003882	dense	-29.915394	-0.720165	-2.410896	64	0.190474	4,096	37	4,032	1	1.920612	0.003882	49.060402	success	0.062309	0	under-trained	4,032	0.003882	0.002876
89	model.layers.12.self_attn.q_proj	0.055156	4,096	4,096	1	10.762409	-25.686382	1.566173	true	0.004105	dense	-25.603435	-0.833243	-2.386676	64	0.146811	4,096	19	4,032	1	2.23965	0.004105	35.762928	success	0.064071	0	under-trained	4,032	0.004105	0.00238
90	model.layers.12.self_attn.v_proj	0.11485	1,024	4,096	4	11.876877	-31.77564	1.13691	true	0.002111	dense	-30.658707	-0.940515	-2.675421	64	0.114679	1,024	52	960	1	1.508351	0.002111	54.313255	success	0.04595	0.000001	under-trained	960	0.002111	0.001665
91	model.layers.13.mlp.down_proj	0.036343	4,096	14,336	3.5	12.125812	-25.628331	1.566873	true	0.0077	dense	-25.49984	-0.521349	-2.113535	64	0.301058	4,096	64	4,032	1	1.390727	0.0077	39.100815	success	0.087747	0.000001	under-trained	4,032	0.0077	0.004275
92	model.layers.13.mlp.gate_proj	0.032849	4,096	14,336	3.5	5.366135	-10.105797	1.559179	true	0.013084	dense	-9.888976	-0.506566	-1.883254	64	0.311483	4,096	36	4,032	1	0.727689	0.013084	23.80612	success	0.114386	0.000001		4,032	0.013084	0.004238
93	model.layers.13.mlp.up_proj	0.037365	4,096	14,336	3.5	5.362235	-10.155244	1.560663	true	0.012769	dense	-9.899726	-0.488475	-1.893845	64	0.324732	4,096	26	4,032	1	0.855505	0.012769	25.431419	success	0.113	0.000001		4,032	0.012769	0.00471
94	model.layers.13.self_attn.k_proj	0.055607	1,024	4,096	4	7.153452	-18.283749	1.133874	true	0.00278	dense	-17.556995	-0.957891	-2.555934	64	0.110182	1,024	59	960	1	0.801111	0.00278	39.631744	success	0.052727	0.000001	under-trained	960	0.00278	0.001462
95	model.layers.13.self_attn.o_proj	0.040657	4,096	4,096	1	10.363712	-23.618383	1.566533	true	0.005261	dense	-23.320876	-0.681243	-2.27895	64	0.208332	4,096	46	4,032	1	1.380604	0.005261	39.601051	success	0.072531	0	under-trained	4,032	0.005261	0.003017
96	model.layers.13.self_attn.q_proj	0.046576	4,096	4,096	1	9.668471	-22.784899	1.565295	true	0.004399	dense	-22.73273	-0.851471	-2.356619	64	0.140776	4,096	20	4,032	1	1.938329	0.004399	31.999794	success	0.066327	0	under-trained	4,032	0.004399	0.002285
97	model.layers.13.self_attn.v_proj	0.069671	1,024	4,096	4	20.504022	-53.933001	1.136864	true	0.002342	dense	-53.52314	-0.922778	-2.630362	64	0.11946	1,024	19	960	1	4.47453	0.002342	51.001656	success	0.048397	0.000001	under-trained	960	0.002342	0.001942
98	model.layers.14.mlp.down_proj	0.032288	4,096	14,336	3.5	10.464349	-21.796519	1.566664	true	0.008262	dense	-21.630572	-0.50299	-2.082931	64	0.314058	4,096	34	4,032	1	1.623122	0.008262	38.013767	success	0.090894	0.000001	under-trained	4,032	0.008262	0.004672
99	model.layers.14.mlp.gate_proj	0.039619	4,096	14,336	3.5	5.266263	-9.813683	1.55907	true	0.013693	dense	-9.606431	-0.497325	-1.8635	64	0.318182	4,096	31	4,032	1	0.766243	0.013693	23.236776	success	0.117017	0.000001		4,032	0.013693	0.004443

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