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alphas2

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train · 224 rows

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
200	model.layers.28.self_attn.o_proj	0.097805	4,096	4,096	1	13.500109	-36.692384	1.566192	true	0.001915	dense	-36.688367	-1.222852	-2.717932	64	0.059862	4,096	64	4,032	1	1.562514	0.001915	31.266609	success	0.043756	0	under-trained	4,032	0.001915	0.000857
201	model.layers.28.self_attn.q_proj	0.032679	4,096	4,096	1	8.820552	-23.808232	1.564349	true	0.001999	dense	-23.786964	-1.270111	-2.699177	64	0.05369	4,096	63	4,032	1	0.985297	0.001999	26.857561	success	0.044711	0	under-trained	4,032	0.001999	0.000729
202	model.layers.28.self_attn.v_proj	0.05884	1,024	4,096	4	26.562079	-80.719735	1.137033	true	0.000914	dense	-80.605992	-1.336471	-3.038909	64	0.046082	1,024	15	960	1	6.600101	0.000914	50.400822	success	0.030237	0.000001	under-trained	960	0.000914	0.000756
203	model.layers.29.mlp.down_proj	0.116928	4,096	14,336	3.5	5.635298	-12.798872	1.563257	true	0.005356	dense	-12.7392	-0.926453	-2.271197	64	0.118453	4,096	8	4,032	1	1.638825	0.005356	22.117905	success	0.073182	0.000001		4,032	0.005356	0.001893
204	model.layers.29.mlp.gate_proj	0.095314	4,096	14,336	3.5	5.709415	-11.900639	1.558272	true	0.008234	dense	-11.889177	-0.86286	-2.084388	64	0.137132	4,096	14	4,032	1	1.258644	0.008234	16.654388	success	0.090741	0.000001		4,032	0.008234	0.002101
205	model.layers.29.mlp.up_proj	0.089241	4,096	14,336	3.5	5.499295	-12.090405	1.560934	true	0.006331	dense	-12.041353	-0.894798	-2.198537	64	0.12741	4,096	15	4,032	1	1.161713	0.006331	20.125153	success	0.079567	0.000001		4,032	0.006331	0.001928
206	model.layers.29.self_attn.k_proj	0.047418	1,024	4,096	4	8.436308	-25.361052	1.135113	true	0.000986	dense	-24.77831	-1.396343	-3.006179	64	0.040147	1,024	57	960	1	0.984963	0.000986	40.722656	success	0.031399	0.000001	under-trained	960	0.000986	0.000552
207	model.layers.29.self_attn.o_proj	0.112862	4,096	4,096	1	12.550207	-31.941633	1.563841	true	0.00285	dense	-31.941213	-1.169205	-2.545108	64	0.067732	4,096	64	4,032	1	1.443776	0.00285	23.763067	success	0.053388	0	under-trained	4,032	0.00285	0.000957
208	model.layers.29.self_attn.q_proj	0.031023	4,096	4,096	1	8.850884	-24.35266	1.564856	true	0.001772	dense	-24.327975	-1.301656	-2.751438	64	0.049928	4,096	61	4,032	1	1.005203	0.001772	28.169666	success	0.0421	0	under-trained	4,032	0.001772	0.000683
209	model.layers.29.self_attn.v_proj	0.082863	1,024	4,096	4	25.604042	-76.527974	1.137019	true	0.001026	dense	-76.441977	-1.29374	-2.988902	64	0.050846	1,024	16	960	1	6.15101	0.001026	49.56353	success	0.032029	0.000001	under-trained	960	0.001026	0.000831
210	model.layers.30.mlp.down_proj	0.121525	4,096	14,336	3.5	4.095597	-8.869663	1.558633	true	0.006829	dense	-8.754653	-0.922824	-2.165658	64	0.119447	4,096	7	4,032	1	1.170026	0.006829	17.491791	success	0.082636	0.000001		4,032	0.006829	0.00197
211	model.layers.30.mlp.gate_proj	0.095954	4,096	14,336	3.5	5.390292	-10.79068	1.555076	true	0.009957	dense	-10.781551	-0.834772	-2.001873	64	0.146295	4,096	16	4,032	1	1.097573	0.009957	14.692684	success	0.099785	0.000001		4,032	0.009957	0.002176
212	model.layers.30.mlp.up_proj	0.094755	4,096	14,336	3.5	4.092898	-8.543034	1.556608	true	0.008179	dense	-8.448714	-0.872864	-2.087282	64	0.13401	4,096	9	4,032	1	1.030966	0.008179	16.383945	success	0.09044	0.000001		4,032	0.008179	0.002164
213	model.layers.30.self_attn.k_proj	0.033068	1,024	4,096	4	8.648706	-25.553527	1.134789	true	0.00111	dense	-25.127229	-1.372152	-2.954607	64	0.042447	1,024	41	960	1	1.194527	0.00111	38.234444	success	0.033319	0.000001	under-trained	960	0.00111	0.000615
214	model.layers.30.self_attn.o_proj	0.148381	4,096	4,096	1	3.666627	-9.161233	1.558121	true	0.003173	dense	-8.763318	-1.17302	-2.498545	64	0.06714	4,096	9	4,032	1	0.888876	0.003173	21.160452	success	0.056328	0		4,032	0.003173	0.001034
215	model.layers.30.self_attn.q_proj	0.028241	4,096	4,096	1	8.020482	-20.355868	1.561349	true	0.002897	dense	-20.352326	-1.227622	-2.537986	64	0.059208	4,096	63	4,032	1	0.884498	0.002897	20.434505	success	0.053828	0	under-trained	4,032	0.002897	0.000786
216	model.layers.30.self_attn.v_proj	0.09179	1,024	4,096	4	32.460629	-97.711113	1.137061	true	0.000977	dense	-97.642366	-1.301774	-3.010142	64	0.049914	1,024	10	960	1	9.948724	0.000977	51.093761	success	0.031256	0.000001	under-trained	960	0.000977	0.000839
217	model.layers.31.mlp.down_proj	0.125934	4,096	14,336	3.5	3.571153	-7.375295	1.537734	true	0.008605	dense	-6.966406	-0.87753	-2.065242	64	0.132578	4,096	19	4,032	1	0.589863	0.008605	15.406788	success	0.092764	0.000001		4,032	0.008605	0.001777
218	model.layers.31.mlp.gate_proj	0.091779	4,096	14,336	3.5	4.415988	-8.811718	1.555982	true	0.010106	dense	-8.763337	-0.804311	-1.995413	64	0.156924	4,096	10	4,032	1	1.08023	0.010106	15.527523	success	0.10053	0.000001		4,032	0.010106	0.002479
219	model.layers.31.mlp.up_proj	0.086961	4,096	14,336	3.5	4.211193	-8.774598	1.557385	true	0.008248	dense	-8.662626	-0.843593	-2.083637	64	0.143353	4,096	10	4,032	1	1.015468	0.008248	17.379765	success	0.09082	0.000001		4,032	0.008248	0.00225
220	model.layers.31.self_attn.k_proj	0.028935	1,024	4,096	4	8.169591	-23.565732	1.134226	true	0.001304	dense	-23.368861	-1.361035	-2.884567	64	0.043548	1,024	40	960	1	1.133612	0.001304	33.383484	success	0.036117	0.000001	under-trained	960	0.001304	0.000628
221	model.layers.31.self_attn.o_proj	0.135698	4,096	4,096	1	10.803733	-25.741085	1.557611	true	0.004144	dense	-25.740958	-1.164674	-2.38261	64	0.068442	4,096	64	4,032	1	1.225467	0.004144	16.517179	success	0.064372	0	under-trained	4,032	0.004144	0.000936
222	model.layers.31.self_attn.q_proj	0.079925	4,096	4,096	1	7.315148	-18.390798	1.559154	true	0.003061	dense	-18.376024	-1.221106	-2.514071	64	0.060103	4,096	64	4,032	1	0.789393	0.003061	19.63199	success	0.055331	0	under-trained	4,032	0.003061	0.000778
223	model.layers.31.self_attn.v_proj	0.070425	1,024	4,096	4	17.833163	-53.131643	1.136837	true	0.001049	dense	-52.768134	-1.29625	-2.979373	64	0.050553	1,024	24	960	1	3.436055	0.001049	48.208412	success	0.032383	0.000001	under-trained	960	0.001049	0.000799

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