pytorch-image-models/results/results-imagenet-a-clean.csv

1	model	top1	top1_err	top5	top5_err	param_count	img_size	cropt_pct	interpolation
2	tf_efficientnet_l2_ns	98.550	1.450	99.820	0.180	480.31	800	0.960	bicubic
3	tf_efficientnet_l2_ns_475	98.500	1.500	99.830	0.170	480.31	475	0.936	bicubic
4	vit_large_patch16_384	98.220	1.780	99.800	0.200	304.72	384	1.000	bicubic
5	swin_large_patch4_window12_384	98.040	1.960	99.690	0.310	196.74	384	1.000	bicubic
6	tf_efficientnet_b7_ns	97.910	2.090	99.720	0.280	66.35	600	0.949	bicubic
7	swin_base_patch4_window12_384	97.890	2.110	99.710	0.290	87.90	384	1.000	bicubic
8	vit_large_r50_s32_384	97.860	2.140	99.670	0.330	329.09	384	1.000	bicubic
9	vit_base_patch16_384	97.840	2.160	99.670	0.330	86.86	384	1.000	bicubic
10	tf_efficientnetv2_l_in21ft1k	97.700	2.300	99.670	0.330	118.52	480	1.000	bicubic
11	swin_large_patch4_window7_224	97.650	2.350	99.580	0.420	196.53	224	0.900	bicubic
12	vit_large_patch16_224	97.640	2.360	99.590	0.410	304.33	224	0.900	bicubic
13	tf_efficientnet_b6_ns	97.630	2.370	99.580	0.420	43.04	528	0.942	bicubic
14	ig_resnext101_32x48d	97.620	2.380	99.700	0.300	828.41	224	0.875	bilinear
15	dm_nfnet_f6	97.600	2.400	99.550	0.450	438.36	576	0.956	bicubic
16	dm_nfnet_f4	97.580	2.420	99.510	0.490	316.07	512	0.951	bicubic
17	dm_nfnet_f5	97.540	2.460	99.570	0.430	377.21	544	0.954	bicubic
18	tf_efficientnet_b5_ns	97.500	2.500	99.630	0.370	30.39	456	0.934	bicubic
19	resnetv2_152x4_bitm	97.490	2.510	99.610	0.390	936.53	480	1.000	bilinear
20	cait_m48_448	97.480	2.520	99.550	0.450	356.46	448	1.000	bicubic
21	tf_efficientnetv2_m_in21ft1k	97.480	2.520	99.530	0.470	54.14	480	1.000	bicubic
22	cait_m36_384	97.400	2.600	99.510	0.490	271.22	384	1.000	bicubic
23	ig_resnext101_32x32d	97.360	2.640	99.680	0.320	468.53	224	0.875	bilinear
24	dm_nfnet_f3	97.350	2.650	99.560	0.440	254.92	416	0.940	bicubic
25	cait_s36_384	97.330	2.670	99.530	0.470	68.37	384	1.000	bicubic
26	tf_efficientnetv2_l	97.280	2.720	99.550	0.450	118.52	480	1.000	bicubic
27	swin_base_patch4_window7_224	97.250	2.750	99.530	0.470	87.77	224	0.900	bicubic
28	tf_efficientnet_b8	97.200	2.800	99.500	0.500	87.41	672	0.954	bicubic
29	swsl_resnext101_32x8d	97.200	2.800	99.570	0.430	88.79	224	0.875	bilinear
30	tf_efficientnet_b7_ap	97.200	2.800	99.540	0.460	66.35	600	0.949	bicubic
31	vit_base_r50_s16_384	97.180	2.820	99.560	0.440	98.95	384	1.000	bicubic
32	tf_efficientnetv2_m	97.140	2.860	99.410	0.590	54.14	480	1.000	bicubic
33	tf_efficientnet_b8_ap	97.110	2.890	99.660	0.340	87.41	672	0.954	bicubic
34	eca_nfnet_l2	97.090	2.910	99.510	0.490	56.72	384	1.000	bicubic
35	ecaresnet269d	97.080	2.920	99.470	0.530	102.09	352	1.000	bicubic
36	tf_efficientnet_b6_ap	97.080	2.920	99.620	0.380	43.04	528	0.942	bicubic
37	cait_s24_384	97.070	2.930	99.430	0.570	47.06	384	1.000	bicubic
38	dm_nfnet_f2	97.020	2.980	99.440	0.560	193.78	352	0.920	bicubic
39	resnetv2_152x2_bitm	97.010	2.990	99.590	0.410	236.34	448	1.000	bilinear
40	tf_efficientnet_b7	97.010	2.990	99.520	0.480	66.35	600	0.949	bicubic
41	resnetv2_101x3_bitm	96.990	3.010	99.490	0.510	387.93	448	1.000	bilinear
42	efficientnetv2_rw_m	96.980	3.020	99.540	0.460	53.24	416	1.000	bicubic
43	deit_base_distilled_patch16_384	96.960	3.040	99.480	0.520	87.63	384	1.000	bicubic
44	tf_efficientnet_b4_ns	96.950	3.050	99.580	0.420	19.34	380	0.922	bicubic
45	dm_nfnet_f1	96.920	3.080	99.410	0.590	132.63	320	0.910	bicubic
46	resnetrs420	96.910	3.090	99.460	0.540	191.89	416	1.000	bicubic
47	vit_base_patch16_224	96.880	3.120	99.530	0.470	86.57	224	0.900	bicubic
48	resnetv2_152x2_bit_teacher_384	96.830	3.170	99.450	0.550	236.34	384	1.000	bicubic
49	ig_resnext101_32x16d	96.820	3.180	99.590	0.410	194.03	224	0.875	bilinear
50	vit_large_r50_s32_224	96.790	3.210	99.350	0.650	328.99	224	0.900	bicubic
51	seresnet152d	96.770	3.230	99.450	0.550	66.84	320	1.000	bicubic
52	resnetrs350	96.760	3.240	99.370	0.630	163.96	384	1.000	bicubic
53	tf_efficientnetv2_s_in21ft1k	96.730	3.270	99.420	0.580	21.46	384	1.000	bicubic
54	resnet200d	96.720	3.280	99.330	0.670	64.69	320	1.000	bicubic
55	resnetv2_50x3_bitm	96.710	3.290	99.550	0.450	217.32	448	1.000	bilinear
56	eca_nfnet_l1	96.700	3.300	99.290	0.710	41.41	320	1.000	bicubic
57	vit_small_patch16_384	96.700	3.300	99.480	0.520	22.20	384	1.000	bicubic
58	resnetrs270	96.690	3.310	99.350	0.650	129.86	352	1.000	bicubic
59	pit_b_distilled_224	96.680	3.320	99.350	0.650	74.79	224	0.900	bicubic
60	tf_efficientnet_b5_ap	96.680	3.320	99.460	0.540	30.39	456	0.934	bicubic
61	vit_small_r26_s32_384	96.680	3.320	99.570	0.430	36.47	384	1.000	bicubic
62	tf_efficientnet_b6	96.670	3.330	99.370	0.630	43.04	528	0.942	bicubic
63	resmlp_big_24_224_in22ft1k	96.620	3.380	99.510	0.490	129.14	224	0.875	bicubic
64	resnest200e	96.610	3.390	99.350	0.650	70.20	320	0.909	bicubic
65	swsl_resnext101_32x16d	96.600	3.400	99.520	0.480	194.03	224	0.875	bilinear
66	resnetrs152	96.580	3.420	99.240	0.760	86.62	320	1.000	bicubic
67	cait_xs24_384	96.550	3.450	99.420	0.580	26.67	384	1.000	bicubic
68	efficientnetv2_rw_s	96.540	3.460	99.360	0.640	23.94	384	1.000	bicubic
69	resnetrs200	96.530	3.470	99.350	0.650	93.21	320	1.000	bicubic
70	resnest269e	96.520	3.480	99.350	0.650	110.93	416	0.928	bicubic
71	vit_base_patch32_384	96.490	3.510	99.410	0.590	88.30	384	1.000	bicubic
72	vit_base_patch16_224_miil	96.460	3.540	99.300	0.700	86.54	224	0.875	bilinear
73	resmlp_big_24_distilled_224	96.450	3.550	99.310	0.690	129.14	224	0.875	bicubic
74	swsl_resnext101_32x4d	96.420	3.580	99.470	0.530	44.18	224	0.875	bilinear
75	tf_efficientnet_b3_ns	96.390	3.610	99.350	0.650	12.23	300	0.904	bicubic
76	cait_s24_224	96.380	3.620	99.150	0.850	46.92	224	1.000	bicubic
77	resnet152d	96.360	3.640	99.390	0.610	60.21	320	1.000	bicubic
78	regnety_160	96.350	3.650	99.330	0.670	83.59	288	1.000	bicubic
79	tf_efficientnet_b5	96.350	3.650	99.310	0.690	30.39	456	0.934	bicubic
80	tf_efficientnetv2_s	96.340	3.660	99.200	0.800	21.46	384	1.000	bicubic
81	ig_resnext101_32x8d	96.320	3.680	99.430	0.570	88.79	224	0.875	bilinear
82	resnet101d	96.290	3.710	99.230	0.770	44.57	320	1.000	bicubic
83	twins_svt_large	96.270	3.730	99.170	0.830	99.27	224	0.900	bicubic
84	tf_efficientnet_b4_ap	96.160	3.840	99.280	0.720	19.34	380	0.922	bicubic
85	twins_svt_base	96.160	3.840	99.060	0.940	56.07	224	0.900	bicubic
86	deit_base_patch16_384	96.150	3.850	99.140	0.860	86.86	384	1.000	bicubic
87	dm_nfnet_f0	96.150	3.850	99.250	0.750	71.49	256	0.900	bicubic
88	efficientnet_b4	96.150	3.850	99.200	0.800	19.34	384	1.000	bicubic
89	twins_pcpvt_large	96.150	3.850	99.180	0.820	60.99	224	0.900	bicubic
90	resnetv2_50x1_bit_distilled	96.130	3.870	99.280	0.720	25.55	224	0.875	bicubic
91	nfnet_l0	96.120	3.880	99.240	0.760	35.07	288	1.000	bicubic
92	resnetv2_152x2_bit_teacher	96.100	3.900	99.280	0.720	236.34	224	0.875	bicubic
93	resnetv2_101x1_bitm	96.100	3.900	99.280	0.720	44.54	448	1.000	bilinear
94	deit_base_distilled_patch16_224	96.090	3.910	99.190	0.810	87.34	224	0.900	bicubic
95	regnety_032	95.970	4.030	99.190	0.810	19.44	288	1.000	bicubic
96	tresnet_xl_448	95.970	4.030	99.130	0.870	78.44	448	0.875	bilinear
97	eca_nfnet_l0	95.950	4.050	99.210	0.790	24.14	288	1.000	bicubic
98	swin_small_patch4_window7_224	95.910	4.090	99.020	0.980	49.61	224	0.900	bicubic
99	tf_efficientnet_b4	95.900	4.100	99.170	0.830	19.34	380	0.922	bicubic
100	swsl_resnext50_32x4d	95.870	4.130	99.250	0.750	25.03	224	0.875	bilinear
101	resnest101e	95.860	4.140	99.210	0.790	48.28	256	0.875	bilinear
102	resnet51q	95.860	4.140	99.120	0.880	35.70	288	1.000	bilinear
103	tresnet_l_448	95.860	4.140	99.120	0.880	55.99	448	0.875	bilinear
104	cait_xxs36_384	95.850	4.150	99.090	0.910	17.37	384	1.000	bicubic
105	vit_large_patch32_384	95.830	4.170	99.150	0.850	306.63	384	1.000	bicubic
106	ssl_resnext101_32x16d	95.800	4.200	99.180	0.820	194.03	224	0.875	bilinear
107	twins_pcpvt_base	95.790	4.210	99.130	0.870	43.83	224	0.900	bicubic
108	tf_efficientnet_b2_ns	95.770	4.230	99.120	0.880	9.11	260	0.890	bicubic
109	tresnet_m	95.720	4.280	99.030	0.970	31.39	224	0.875	bilinear
110	efficientnet_b3	95.710	4.290	99.040	0.960	12.23	320	1.000	bicubic
111	pnasnet5large	95.710	4.290	98.920	1.080	86.06	331	0.911	bicubic
112	nasnetalarge	95.680	4.320	98.930	1.070	88.75	331	0.911	bicubic
113	pit_b_224	95.640	4.360	98.660	1.340	73.76	224	0.900	bicubic
114	vit_small_r26_s32_224	95.630	4.370	99.190	0.810	36.43	224	0.900	bicubic
115	convit_base	95.550	4.450	98.870	1.130	86.54	224	0.875	bicubic
116	coat_lite_small	95.540	4.460	98.860	1.140	19.84	224	0.900	bicubic
117	ecaresnet101d	95.530	4.470	99.130	0.870	44.57	224	0.875	bicubic
118	levit_384	95.530	4.470	99.050	0.950	39.13	224	0.900	bicubic
119	ecaresnet50t	95.510	4.490	99.120	0.880	25.57	320	0.950	bicubic
120	visformer_small	95.490	4.510	98.900	1.100	40.22	224	0.900	bicubic
121	ssl_resnext101_32x8d	95.470	4.530	99.110	0.890	88.79	224	0.875	bilinear
122	deit_base_patch16_224	95.440	4.560	98.840	1.160	86.57	224	0.900	bicubic
123	ssl_resnext101_32x4d	95.440	4.560	99.130	0.870	44.18	224	0.875	bilinear
124	tresnet_xl	95.440	4.560	99.050	0.950	78.44	224	0.875	bilinear
125	resnetrs101	95.430	4.570	99.030	0.970	63.62	288	0.940	bicubic
126	swsl_resnet50	95.410	4.590	99.290	0.710	25.56	224	0.875	bilinear
127	vit_small_patch16_224	95.370	4.630	99.150	0.850	22.05	224	0.900	bicubic
128	tf_efficientnet_b3_ap	95.320	4.680	98.900	1.100	12.23	300	0.904	bicubic
129	mixer_b16_224_miil	95.300	4.700	98.880	1.120	59.88	224	0.875	bilinear
130	tresnet_l	95.290	4.710	99.010	0.990	55.99	224	0.875	bilinear
131	cait_xxs24_384	95.260	4.740	98.960	1.040	12.03	384	1.000	bicubic
132	pit_s_distilled_224	95.240	4.760	99.050	0.950	24.04	224	0.900	bicubic
133	twins_pcpvt_small	95.210	4.790	98.880	1.120	24.11	224	0.900	bicubic
134	convit_small	95.200	4.800	98.900	1.100	27.78	224	0.875	bicubic
135	twins_svt_small	95.200	4.800	98.880	1.120	24.06	224	0.900	bicubic
136	tf_efficientnet_b1_ns	95.170	4.830	99.110	0.890	7.79	240	0.882	bicubic
137	tf_efficientnetv2_b3	95.160	4.840	98.820	1.180	14.36	300	0.904	bicubic
138	swin_tiny_patch4_window7_224	95.140	4.860	98.850	1.150	28.29	224	0.900	bicubic
139	efficientnet_el	95.120	4.880	98.990	1.010	10.59	300	0.904	bicubic
140	gernet_l	95.090	4.910	98.900	1.100	31.08	256	0.875	bilinear
141	ecaresnet101d_pruned	95.080	4.920	98.980	1.020	24.88	224	0.875	bicubic
142	wide_resnet50_2	95.080	4.920	98.970	1.030	68.88	224	0.875	bicubic
143	legacy_senet154	95.070	4.930	98.830	1.170	115.09	224	0.875	bilinear
144	vit_small_patch32_384	95.050	4.950	98.990	1.010	22.92	384	1.000	bicubic
145	seresnext50_32x4d	95.040	4.960	98.880	1.120	27.56	224	0.875	bicubic
146	tnt_s_patch16_224	95.040	4.960	98.830	1.170	23.76	224	0.900	bicubic
147	gluon_resnet152_v1s	95.040	4.960	98.930	1.070	60.32	224	0.875	bicubic
148	levit_256	95.010	4.990	98.890	1.110	18.89	224	0.900	bicubic
149	resnetv2_50x1_bitm	95.010	4.990	99.060	0.940	25.55	448	1.000	bilinear
150	tf_efficientnet_b3	95.010	4.990	98.910	1.090	12.23	300	0.904	bicubic
151	vit_base_patch32_224	95.000	5.000	99.030	0.970	88.22	224	0.900	bicubic
152	tresnet_m_448	94.990	5.010	98.980	1.020	31.39	448	0.875	bilinear
153	coat_mini	94.970	5.030	98.780	1.220	10.34	224	0.900	bicubic
154	resnest50d_4s2x40d	94.960	5.040	99.070	0.930	30.42	224	0.875	bicubic
155	rexnet_200	94.940	5.060	99.010	0.990	16.37	224	0.875	bicubic
156	gluon_seresnext101_64x4d	94.930	5.070	98.830	1.170	88.23	224	0.875	bicubic
157	gluon_senet154	94.920	5.080	98.760	1.240	115.09	224	0.875	bicubic
158	gluon_seresnext101_32x4d	94.920	5.080	98.810	1.190	48.96	224	0.875	bicubic
159	tf_efficientnet_lite4	94.890	5.110	99.020	0.980	13.01	380	0.920	bilinear
160	resmlp_36_distilled_224	94.890	5.110	98.850	1.150	44.69	224	0.875	bicubic
161	ssl_resnext50_32x4d	94.870	5.130	98.880	1.120	25.03	224	0.875	bilinear
162	resnest50d	94.830	5.170	98.880	1.120	27.48	224	0.875	bilinear
163	ecaresnetlight	94.770	5.230	98.800	1.200	30.16	224	0.875	bicubic
164	resnest50d_1s4x24d	94.750	5.250	98.980	1.020	25.68	224	0.875	bicubic
165	gluon_resnet152_v1d	94.740	5.260	98.740	1.260	60.21	224	0.875	bicubic
166	gluon_resnet101_v1s	94.720	5.280	98.820	1.180	44.67	224	0.875	bicubic
167	deit_small_distilled_patch16_224	94.710	5.290	99.030	0.970	22.44	224	0.900	bicubic
168	gluon_resnext101_64x4d	94.670	5.330	98.650	1.350	83.46	224	0.875	bicubic
169	cspdarknet53	94.660	5.340	98.800	1.200	27.64	256	0.887	bilinear
170	resmlp_big_24_224	94.660	5.340	98.480	1.520	129.14	224	0.875	bicubic
171	ecaresnet50d	94.630	5.370	98.890	1.110	25.58	224	0.875	bicubic
172	efficientnet_b3_pruned	94.630	5.370	98.760	1.240	9.86	300	0.904	bicubic
173	gernet_m	94.620	5.380	98.860	1.140	21.14	224	0.875	bilinear
174	efficientnet_b2	94.610	5.390	98.710	1.290	9.11	288	1.000	bicubic
175	pit_s_224	94.590	5.410	98.710	1.290	23.46	224	0.900	bicubic
176	repvgg_b3	94.570	5.430	98.780	1.220	123.09	224	0.875	bilinear
177	nf_resnet50	94.560	5.440	98.790	1.210	25.56	288	0.940	bicubic
178	seresnet50	94.550	5.450	98.750	1.250	28.09	224	0.875	bicubic
179	inception_resnet_v2	94.540	5.460	98.790	1.210	55.84	299	0.897	bicubic
180	regnety_320	94.540	5.460	98.850	1.150	145.05	224	0.875	bicubic
181	gluon_resnext101_32x4d	94.530	5.470	98.630	1.370	44.18	224	0.875	bicubic
182	repvgg_b3g4	94.520	5.480	98.970	1.030	83.83	224	0.875	bilinear
183	tf_efficientnet_b2_ap	94.490	5.510	98.620	1.380	9.11	260	0.890	bicubic
184	regnety_120	94.480	5.520	98.810	1.190	51.82	224	0.875	bicubic
185	rexnet_150	94.480	5.520	98.790	1.210	9.73	224	0.875	bicubic
186	cspresnext50	94.480	5.520	98.680	1.320	20.57	224	0.875	bilinear
187	resmlp_24_distilled_224	94.460	5.540	98.770	1.230	30.02	224	0.875	bicubic
188	regnetx_320	94.460	5.540	98.740	1.260	107.81	224	0.875	bicubic
189	ssl_resnet50	94.450	5.550	98.920	1.080	25.56	224	0.875	bilinear
190	tf_efficientnetv2_b2	94.420	5.580	98.570	1.430	10.10	260	0.890	bicubic
191	tf_efficientnet_el	94.410	5.590	98.710	1.290	10.59	300	0.904	bicubic
192	deit_small_patch16_224	94.400	5.600	98.690	1.310	22.05	224	0.900	bicubic
193	efficientnet_el_pruned	94.400	5.600	98.740	1.260	10.59	300	0.904	bicubic
194	inception_v4	94.380	5.620	98.580	1.420	42.68	299	0.875	bicubic
195	legacy_seresnext101_32x4d	94.370	5.630	98.650	1.350	48.96	224	0.875	bilinear
196	tf_efficientnet_b2	94.360	5.640	98.610	1.390	9.11	260	0.890	bicubic
197	gluon_seresnext50_32x4d	94.340	5.660	98.610	1.390	27.56	224	0.875	bicubic
198	resnetrs50	94.310	5.690	98.640	1.360	35.69	224	0.910	bicubic
199	dpn107	94.310	5.690	98.480	1.520	86.92	224	0.875	bicubic
200	ecaresnet26t	94.310	5.690	98.720	1.280	16.01	320	0.950	bicubic
201	xception71	94.280	5.720	98.640	1.360	42.34	299	0.903	bicubic
202	cait_xxs36_224	94.260	5.740	98.720	1.280	17.30	224	1.000	bicubic
203	gluon_xception65	94.260	5.740	98.570	1.430	39.92	299	0.903	bicubic
204	resnet50d	94.260	5.740	98.720	1.280	25.58	224	0.875	bicubic
205	skresnext50_32x4d	94.260	5.740	98.460	1.540	27.48	224	0.875	bicubic
206	regnetx_120	94.240	5.760	98.650	1.350	46.11	224	0.875	bicubic
207	dpn92	94.230	5.770	98.730	1.270	37.67	224	0.875	bicubic
208	ecaresnet50d_pruned	94.220	5.780	98.730	1.270	19.94	224	0.875	bicubic
209	gluon_resnet101_v1d	94.220	5.780	98.550	1.450	44.57	224	0.875	bicubic
210	tf_efficientnet_lite3	94.200	5.800	98.640	1.360	8.20	300	0.904	bilinear
211	resmlp_36_224	94.190	5.810	98.660	1.340	44.69	224	0.875	bicubic
212	mixnet_xl	94.190	5.810	98.340	1.660	11.90	224	0.875	bicubic
213	resnext50d_32x4d	94.180	5.820	98.570	1.430	25.05	224	0.875	bicubic
214	levit_192	94.170	5.830	98.540	1.460	10.95	224	0.900	bicubic
215	regnety_080	94.170	5.830	98.680	1.320	39.18	224	0.875	bicubic
216	ens_adv_inception_resnet_v2	94.160	5.840	98.600	1.400	55.84	299	0.897	bicubic
217	gluon_resnet152_v1c	94.160	5.840	98.640	1.360	60.21	224	0.875	bicubic
218	regnety_064	94.150	5.850	98.730	1.270	30.58	224	0.875	bicubic
219	efficientnet_b2_pruned	94.140	5.860	98.530	1.470	8.31	260	0.890	bicubic
220	dpn98	94.130	5.870	98.570	1.430	61.57	224	0.875	bicubic
221	nf_regnet_b1	94.120	5.880	98.630	1.370	10.22	288	0.900	bicubic
222	regnetx_160	94.120	5.880	98.750	1.250	54.28	224	0.875	bicubic
223	resnext50_32x4d	94.100	5.900	98.350	1.650	25.03	224	0.875	bicubic
224	ese_vovnet39b	94.090	5.910	98.660	1.340	24.57	224	0.875	bicubic
225	gluon_resnet152_v1b	94.080	5.920	98.450	1.550	60.19	224	0.875	bicubic
226	coat_lite_mini	94.060	5.940	98.560	1.440	11.01	224	0.900	bicubic
227	resmlp_24_224	94.020	5.980	98.330	1.670	30.02	224	0.875	bicubic
228	dpn131	94.010	5.990	98.720	1.280	79.25	224	0.875	bicubic
229	hrnet_w64	94.010	5.990	98.610	1.390	128.06	224	0.875	bilinear
230	resnetblur50	93.960	6.040	98.590	1.410	25.56	224	0.875	bicubic
231	dla102x2	93.950	6.050	98.490	1.510	41.28	224	0.875	bilinear
232	tf_efficientnetv2_b1	93.940	6.060	98.620	1.380	8.14	240	0.882	bicubic
233	hrnet_w48	93.920	6.080	98.610	1.390	77.47	224	0.875	bilinear
234	rexnet_130	93.900	6.100	98.400	1.600	7.56	224	0.875	bicubic
235	tf_efficientnet_cc_b1_8e	93.900	6.100	98.260	1.740	39.72	240	0.882	bicubic
236	regnetx_064	93.890	6.110	98.630	1.370	26.21	224	0.875	bicubic
237	regnetx_080	93.870	6.130	98.520	1.480	39.57	224	0.875	bicubic
238	repvgg_b2g4	93.860	6.140	98.590	1.410	61.76	224	0.875	bilinear
239	regnety_040	93.860	6.140	98.650	1.350	20.65	224	0.875	bicubic
240	efficientnet_em	93.840	6.160	98.810	1.190	6.90	240	0.882	bicubic
241	resnext101_32x8d	93.830	6.170	98.580	1.420	88.79	224	0.875	bilinear
242	gluon_resnext50_32x4d	93.810	6.190	98.410	1.590	25.03	224	0.875	bicubic
243	pit_xs_distilled_224	93.810	6.190	98.670	1.330	11.00	224	0.900	bicubic
244	resnet50	93.810	6.190	98.390	1.610	25.56	224	0.875	bicubic
245	gluon_resnet50_v1d	93.770	6.230	98.390	1.610	25.58	224	0.875	bicubic
246	xception65	93.760	6.240	98.370	1.630	39.92	299	0.903	bicubic
247	gluon_resnet101_v1b	93.750	6.250	98.380	1.620	44.55	224	0.875	bicubic
248	res2net101_26w_4s	93.750	6.250	98.310	1.690	45.21	224	0.875	bilinear
249	cspresnet50	93.740	6.260	98.640	1.360	21.62	256	0.887	bilinear
250	legacy_seresnext50_32x4d	93.730	6.270	98.580	1.420	27.56	224	0.875	bilinear
251	wide_resnet101_2	93.720	6.280	98.540	1.460	126.89	224	0.875	bilinear
252	tf_efficientnet_b1_ap	93.690	6.310	98.360	1.640	7.79	240	0.882	bicubic
253	dpn68b	93.690	6.310	98.510	1.490	12.61	224	0.875	bicubic
254	gluon_resnet101_v1c	93.670	6.330	98.420	1.580	44.57	224	0.875	bicubic
255	vit_tiny_patch16_384	93.650	6.350	98.600	1.400	5.79	384	1.000	bicubic
256	tf_efficientnet_b0_ns	93.630	6.370	98.640	1.360	5.29	224	0.875	bicubic
257	gluon_resnet50_v1s	93.620	6.380	98.460	1.540	25.68	224	0.875	bicubic
258	cait_xxs24_224	93.600	6.400	98.440	1.560	11.96	224	1.000	bicubic
259	coat_tiny	93.590	6.410	98.430	1.570	5.50	224	0.900	bicubic
260	regnetx_040	93.560	6.440	98.540	1.460	22.12	224	0.875	bicubic
261	hrnet_w44	93.550	6.450	98.700	1.300	67.06	224	0.875	bilinear
262	res2net50_26w_8s	93.540	6.460	98.260	1.740	48.40	224	0.875	bilinear
263	hrnet_w32	93.530	6.470	98.450	1.550	41.23	224	0.875	bilinear
264	dla102x	93.520	6.480	98.510	1.490	26.31	224	0.875	bilinear
265	repvgg_b2	93.500	6.500	98.730	1.270	89.02	224	0.875	bilinear
266	tf_efficientnet_b1	93.500	6.500	98.360	1.640	7.79	240	0.882	bicubic
267	hrnet_w40	93.490	6.510	98.580	1.420	57.56	224	0.875	bilinear
268	gluon_inception_v3	93.460	6.540	98.570	1.430	23.83	299	0.875	bicubic
269	xception	93.460	6.540	98.530	1.470	22.86	299	0.897	bicubic
270	mixnet_l	93.450	6.550	98.220	1.780	7.33	224	0.875	bicubic
271	xception41	93.430	6.570	98.430	1.570	26.97	299	0.903	bicubic
272	res2net50_26w_6s	93.410	6.590	98.280	1.720	37.05	224	0.875	bilinear
273	legacy_seresnet152	93.400	6.600	98.350	1.650	66.82	224	0.875	bilinear
274	dla169	93.340	6.660	98.600	1.400	53.39	224	0.875	bilinear
275	levit_128	93.340	6.660	98.380	1.620	9.21	224	0.900	bicubic
276	repvgg_b1	93.330	6.670	98.510	1.490	57.42	224	0.875	bilinear
277	resnest26d	93.330	6.670	98.630	1.370	17.07	224	0.875	bilinear
278	tf_inception_v3	93.320	6.680	98.030	1.970	23.83	299	0.875	bicubic
279	tf_mixnet_l	93.310	6.690	98.030	1.970	7.33	224	0.875	bicubic
280	selecsls60b	93.300	6.700	98.280	1.720	32.77	224	0.875	bicubic
281	tv_resnet152	93.300	6.700	98.390	1.610	60.19	224	0.875	bilinear
282	legacy_seresnet101	93.280	6.720	98.510	1.490	49.33	224	0.875	bilinear
283	efficientnet_b1	93.250	6.750	98.290	1.710	7.79	256	1.000	bicubic
284	coat_lite_tiny	93.240	6.760	98.260	1.740	5.72	224	0.900	bicubic
285	hrnet_w30	93.200	6.800	98.410	1.590	37.71	224	0.875	bilinear
286	dla60_res2net	93.180	6.820	98.420	1.580	20.85	224	0.875	bilinear
287	dla60_res2next	93.180	6.820	98.410	1.590	17.03	224	0.875	bilinear
288	efficientnet_es	93.140	6.860	98.420	1.580	5.44	224	0.875	bicubic
289	dla60x	93.120	6.880	98.510	1.490	17.35	224	0.875	bilinear
290	regnetx_032	93.120	6.880	98.390	1.610	15.30	224	0.875	bicubic
291	tf_efficientnetv2_b0	93.110	6.890	98.390	1.610	7.14	224	0.875	bicubic
292	pit_xs_224	93.110	6.890	98.310	1.690	10.62	224	0.900	bicubic
293	dla102	93.060	6.940	98.540	1.460	33.27	224	0.875	bilinear
294	gluon_resnet50_v1c	93.030	6.970	98.390	1.610	25.58	224	0.875	bicubic
295	regnety_016	93.030	6.970	98.360	1.640	11.20	224	0.875	bicubic
296	rexnet_100	93.030	6.970	98.190	1.810	4.80	224	0.875	bicubic
297	selecsls60	93.030	6.970	98.300	1.700	30.67	224	0.875	bicubic
298	repvgg_b1g4	92.980	7.020	98.430	1.570	39.97	224	0.875	bilinear
299	legacy_seresnet50	92.960	7.040	98.190	1.810	28.09	224	0.875	bilinear
300	hardcorenas_f	92.950	7.050	98.160	1.840	8.20	224	0.875	bilinear
301	tf_efficientnet_em	92.930	7.070	98.190	1.810	6.90	240	0.882	bicubic
302	adv_inception_v3	92.880	7.120	98.140	1.860	23.83	299	0.875	bicubic
303	res2next50	92.840	7.160	98.180	1.820	24.67	224	0.875	bilinear
304	tf_efficientnet_cc_b0_8e	92.830	7.170	98.180	1.820	24.01	224	0.875	bicubic
305	resmlp_12_distilled_224	92.830	7.170	98.140	1.860	15.35	224	0.875	bicubic
306	gmixer_24_224	92.830	7.170	97.880	2.120	24.72	224	0.875	bicubic
307	seresnext26t_32x4d	92.820	7.180	98.370	1.630	16.81	224	0.875	bicubic
308	tv_resnet101	92.810	7.190	98.250	1.750	44.55	224	0.875	bilinear
309	efficientnet_b1_pruned	92.770	7.230	98.040	1.960	6.33	240	0.882	bicubic
310	densenet201	92.750	7.250	98.230	1.770	20.01	224	0.875	bicubic
311	res2net50_14w_8s	92.740	7.260	98.180	1.820	25.06	224	0.875	bilinear
312	tv_resnext50_32x4d	92.740	7.260	98.270	1.730	25.03	224	0.875	bilinear
313	inception_v3	92.720	7.280	97.970	2.030	23.83	299	0.875	bicubic
314	seresnext26d_32x4d	92.700	7.300	98.150	1.850	16.81	224	0.875	bicubic
315	efficientnet_b0	92.690	7.310	98.070	1.930	5.29	224	0.875	bicubic
316	resnet34d	92.680	7.320	98.310	1.690	21.82	224	0.875	bicubic
317	tf_efficientnet_lite2	92.650	7.350	98.230	1.770	6.09	260	0.890	bicubic
318	legacy_seresnext26_32x4d	92.640	7.360	98.130	1.870	16.79	224	0.875	bicubic
319	tf_efficientnet_lite1	92.620	7.380	98.080	1.920	5.42	240	0.882	bicubic
320	tf_efficientnet_cc_b0_4e	92.590	7.410	98.080	1.920	13.31	224	0.875	bicubic
321	hardcorenas_e	92.570	7.430	98.110	1.890	8.07	224	0.875	bilinear
322	res2net50_48w_2s	92.550	7.450	98.080	1.920	25.29	224	0.875	bilinear
323	gluon_resnet50_v1b	92.540	7.460	98.170	1.830	25.56	224	0.875	bicubic
324	densenet161	92.500	7.500	98.290	1.710	28.68	224	0.875	bicubic
325	res2net50_26w_4s	92.500	7.500	98.060	1.940	25.70	224	0.875	bilinear
326	mixnet_m	92.430	7.570	97.870	2.130	5.01	224	0.875	bicubic
327	hardcorenas_d	92.400	7.600	98.070	1.930	7.50	224	0.875	bilinear
328	mobilenetv2_120d	92.400	7.600	98.050	1.950	5.83	224	0.875	bicubic
329	skresnet34	92.390	7.610	98.150	1.850	22.28	224	0.875	bicubic
330	tf_mixnet_m	92.330	7.670	97.890	2.110	5.01	224	0.875	bicubic
331	hrnet_w18	92.320	7.680	98.240	1.760	21.30	224	0.875	bilinear
332	ese_vovnet19b_dw	92.290	7.710	98.090	1.910	6.54	224	0.875	bicubic
333	selecsls42b	92.280	7.720	98.150	1.850	32.46	224	0.875	bicubic
334	mobilenetv3_large_100_miil	92.260	7.740	97.640	2.360	5.48	224	0.875	bilinear
335	tf_efficientnet_b0	92.250	7.750	98.000	2.000	5.29	224	0.875	bicubic
336	dla60	92.230	7.770	98.110	1.890	22.04	224	0.875	bilinear
337	resmlp_12_224	92.210	7.790	98.160	1.840	15.35	224	0.875	bicubic
338	tf_efficientnet_b0_ap	92.200	7.800	98.020	1.980	5.29	224	0.875	bicubic
339	regnetx_016	92.170	7.830	98.210	1.790	9.19	224	0.875	bicubic
340	gernet_s	92.140	7.860	98.190	1.810	8.17	224	0.875	bilinear
341	resnet26d	92.070	7.930	97.960	2.040	16.01	224	0.875	bicubic
342	vit_small_patch32_224	92.040	7.960	98.230	1.770	22.88	224	0.900	bicubic
343	vit_tiny_r_s16_p8_384	92.040	7.960	98.290	1.710	6.36	384	1.000	bicubic
344	hardcorenas_c	92.020	7.980	97.840	2.160	5.52	224	0.875	bilinear
345	dpn68	92.010	7.990	98.050	1.950	12.61	224	0.875	bicubic
346	tf_efficientnet_es	91.980	8.020	97.860	2.140	5.44	224	0.875	bicubic
347	levit_128s	91.970	8.030	98.060	1.940	7.78	224	0.900	bicubic
348	repvgg_a2	91.940	8.060	98.150	1.850	28.21	224	0.875	bilinear
349	densenet169	91.930	8.070	98.100	1.900	14.15	224	0.875	bicubic
350	densenetblur121d	91.910	8.090	98.070	1.930	8.00	224	0.875	bicubic
351	tv_resnet50	91.880	8.120	98.040	1.960	25.56	224	0.875	bilinear
352	mixer_b16_224	91.870	8.130	97.250	2.750	59.88	224	0.875	bicubic
353	mixnet_s	91.830	8.170	97.690	2.310	4.13	224	0.875	bicubic
354	mobilenetv2_140	91.830	8.170	97.860	2.140	6.11	224	0.875	bicubic
355	hardcorenas_b	91.770	8.230	97.780	2.220	5.18	224	0.875	bilinear
356	vit_tiny_patch16_224	91.760	8.240	98.040	1.960	5.72	224	0.900	bicubic
357	regnety_008	91.750	8.250	98.180	1.820	6.26	224	0.875	bicubic
358	resnest14d	91.720	8.280	97.870	2.130	10.61	224	0.875	bilinear
359	densenet121	91.570	8.430	98.030	1.970	7.98	224	0.875	bicubic
360	tf_mixnet_s	91.510	8.490	97.620	2.380	4.13	224	0.875	bicubic
361	repvgg_b0	91.430	8.570	97.990	2.010	15.82	224	0.875	bilinear
362	regnety_006	91.370	8.630	97.710	2.290	6.06	224	0.875	bicubic
363	hardcorenas_a	91.350	8.650	97.860	2.140	5.26	224	0.875	bilinear
364	mobilenetv3_large_100	91.320	8.680	97.710	2.290	5.48	224	0.875	bicubic
365	semnasnet_100	91.280	8.720	97.560	2.440	3.89	224	0.875	bicubic
366	tf_mobilenetv3_large_100	91.240	8.760	97.660	2.340	5.48	224	0.875	bilinear
367	mobilenetv3_rw	91.210	8.790	97.660	2.340	5.48	224	0.875	bicubic
368	hrnet_w18_small_v2	91.190	8.810	97.900	2.100	15.60	224	0.875	bilinear
369	efficientnet_es_pruned	91.180	8.820	97.750	2.250	5.44	224	0.875	bicubic
370	efficientnet_lite0	91.140	8.860	97.630	2.370	4.65	224	0.875	bicubic
371	resnet34	91.130	8.870	97.620	2.380	21.80	224	0.875	bilinear
372	resnet26	91.110	8.890	97.740	2.260	16.00	224	0.875	bicubic
373	regnetx_008	91.050	8.950	97.710	2.290	7.26	224	0.875	bicubic
374	tf_efficientnet_lite0	91.040	8.960	97.590	2.410	4.65	224	0.875	bicubic
375	gluon_resnet34_v1b	90.960	9.040	97.630	2.370	21.80	224	0.875	bicubic
376	mobilenetv2_110d	90.950	9.050	97.550	2.450	4.52	224	0.875	bicubic
377	pit_ti_distilled_224	90.900	9.100	97.700	2.300	5.10	224	0.900	bicubic
378	legacy_seresnet34	90.890	9.110	97.580	2.420	21.96	224	0.875	bilinear
379	tv_densenet121	90.890	9.110	97.710	2.290	7.98	224	0.875	bicubic
380	dla34	90.760	9.240	97.660	2.340	15.74	224	0.875	bilinear
381	deit_tiny_distilled_patch16_224	90.700	9.300	97.570	2.430	5.91	224	0.900	bicubic
382	fbnetc_100	90.700	9.300	97.210	2.790	5.57	224	0.875	bilinear
383	swsl_resnet18	90.690	9.310	97.700	2.300	11.69	224	0.875	bilinear
384	convit_tiny	90.630	9.370	97.740	2.260	5.71	224	0.875	bicubic
385	mnasnet_100	90.510	9.490	97.470	2.530	4.38	224	0.875	bicubic
386	regnety_004	90.500	9.500	97.540	2.460	4.34	224	0.875	bicubic
387	regnetx_006	90.350	9.650	97.430	2.570	6.20	224	0.875	bicubic
388	spnasnet_100	90.350	9.650	97.190	2.810	4.42	224	0.875	bilinear
389	ssl_resnet18	90.220	9.780	97.550	2.450	11.69	224	0.875	bilinear
390	vgg16_bn	90.090	9.910	97.370	2.630	138.37	224	0.875	bilinear
391	vgg19_bn	90.080	9.920	97.580	2.420	143.68	224	0.875	bilinear
392	ghostnet_100	90.020	9.980	97.370	2.630	5.18	224	0.875	bilinear
393	pit_ti_224	89.940	10.060	97.450	2.550	4.85	224	0.900	bicubic
394	tv_resnet34	89.940	10.060	97.340	2.660	21.80	224	0.875	bilinear
395	tf_mobilenetv3_large_075	89.680	10.320	97.210	2.790	3.99	224	0.875	bilinear
396	deit_tiny_patch16_224	89.670	10.330	97.450	2.550	5.72	224	0.900	bicubic
397	skresnet18	89.660	10.340	97.230	2.770	11.96	224	0.875	bicubic
398	mobilenetv2_100	89.600	10.400	97.140	2.860	3.50	224	0.875	bicubic
399	resnet18d	89.280	10.720	97.150	2.850	11.71	224	0.875	bicubic
400	vit_tiny_r_s16_p8_224	89.170	10.830	97.230	2.770	6.34	224	0.900	bicubic
401	hrnet_w18_small	89.050	10.950	97.110	2.890	13.19	224	0.875	bilinear
402	vgg19	89.040	10.960	96.870	3.130	143.67	224	0.875	bilinear
403	tf_mobilenetv3_large_minimal_100	88.970	11.030	96.860	3.140	3.92	224	0.875	bilinear
404	regnetx_004	88.900	11.100	97.120	2.880	5.16	224	0.875	bicubic
405	legacy_seresnet18	88.880	11.120	96.980	3.020	11.78	224	0.875	bicubic
406	vgg13_bn	88.760	11.240	96.970	3.030	133.05	224	0.875	bilinear
407	vgg16	88.550	11.450	96.790	3.210	138.36	224	0.875	bilinear
408	gluon_resnet18_v1b	88.400	11.600	96.680	3.320	11.69	224	0.875	bicubic
409	vgg11_bn	87.500	12.500	96.820	3.180	132.87	224	0.875	bilinear
410	resnet18	87.390	12.610	96.290	3.710	11.69	224	0.875	bilinear
411	regnety_002	87.380	12.620	96.590	3.410	3.16	224	0.875	bicubic
412	mixer_l16_224	87.150	12.850	93.520	6.480	208.20	224	0.875	bicubic
413	vgg13	87.050	12.950	96.320	3.680	133.05	224	0.875	bilinear
414	vgg11	86.550	13.450	96.280	3.720	132.86	224	0.875	bilinear
415	dla60x_c	86.290	13.710	96.160	3.840	1.32	224	0.875	bilinear
416	regnetx_002	86.190	13.810	95.980	4.020	2.68	224	0.875	bicubic
417	tf_mobilenetv3_small_100	85.190	14.810	95.770	4.230	2.54	224	0.875	bilinear
418	dla46x_c	84.250	15.750	95.270	4.730	1.07	224	0.875	bilinear
419	dla46_c	83.650	16.350	94.920	5.080	1.30	224	0.875	bilinear
420	tf_mobilenetv3_small_075	83.520	16.480	94.790	5.210	2.04	224	0.875	bilinear
421	tf_mobilenetv3_small_minimal_100	81.380	18.620	93.670	6.330	2.04	224	0.875	bilinear