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	swin_large_patch4_window12_384	98.040	1.960	99.690	0.310	196.74	384	1.000	bicubic
5	tf_efficientnet_b7_ns	97.910	2.090	99.720	0.280	66.35	600	0.949	bicubic
6	swin_base_patch4_window12_384	97.890	2.110	99.710	0.290	87.90	384	1.000	bicubic
7	dm_nfnet_f6	97.730	2.270	99.580	0.420	438.36	576	0.956	bicubic
8	tf_efficientnetv2_l_in21ft1k	97.700	2.300	99.670	0.330	118.52	480	1.000	bicubic
9	swin_large_patch4_window7_224	97.650	2.350	99.580	0.420	196.53	224	0.900	bicubic
10	tf_efficientnet_b6_ns	97.630	2.370	99.580	0.420	43.04	528	0.942	bicubic
11	ig_resnext101_32x48d	97.620	2.380	99.700	0.300	828.41	224	0.875	bilinear
12	dm_nfnet_f5	97.600	2.400	99.550	0.450	377.21	544	0.954	bicubic
13	dm_nfnet_f4	97.570	2.430	99.520	0.480	316.07	512	0.951	bicubic
14	tf_efficientnet_b5_ns	97.500	2.500	99.630	0.370	30.39	456	0.934	bicubic
15	resnetv2_152x4_bitm	97.490	2.510	99.600	0.400	936.53	480	1.000	bilinear
16	cait_m48_448	97.480	2.520	99.550	0.450	356.46	448	1.000	bicubic
17	tf_efficientnetv2_m_in21ft1k	97.480	2.520	99.530	0.470	54.14	480	1.000	bicubic
18	cait_m36_384	97.400	2.600	99.510	0.490	271.22	384	1.000	bicubic
19	dm_nfnet_f3	97.360	2.640	99.580	0.420	254.92	416	0.940	bicubic
20	ig_resnext101_32x32d	97.360	2.640	99.680	0.320	468.53	224	0.875	bilinear
21	cait_s36_384	97.330	2.670	99.530	0.470	68.37	384	1.000	bicubic
22	tf_efficientnetv2_l	97.280	2.720	99.550	0.450	118.52	480	1.000	bicubic
23	swin_base_patch4_window7_224	97.250	2.750	99.530	0.470	87.77	224	0.900	bicubic
24	tf_efficientnet_b8	97.200	2.800	99.500	0.500	87.41	672	0.954	bicubic
25	tf_efficientnet_b7_ap	97.200	2.800	99.540	0.460	66.35	600	0.949	bicubic
26	swsl_resnext101_32x8d	97.200	2.800	99.570	0.430	88.79	224	0.875	bilinear
27	vit_base_r50_s16_384	97.180	2.820	99.560	0.440	98.95	384	1.000	bicubic
28	resnetv2_152x2_bitm	97.150	2.850	99.590	0.410	236.34	480	1.000	bilinear
29	tf_efficientnetv2_m	97.140	2.860	99.410	0.590	54.14	480	1.000	bicubic
30	tf_efficientnet_b8_ap	97.110	2.890	99.660	0.340	87.41	672	0.954	bicubic
31	vit_large_patch16_384	97.110	2.890	99.640	0.360	304.72	384	1.000	bicubic
32	ecaresnet269d	97.080	2.920	99.470	0.530	102.09	352	1.000	bicubic
33	tf_efficientnet_b6_ap	97.080	2.920	99.620	0.380	43.04	528	0.942	bicubic
34	cait_s24_384	97.070	2.930	99.430	0.570	47.06	384	1.000	bicubic
35	resnetv2_101x3_bitm	97.050	2.950	99.520	0.480	387.93	480	1.000	bilinear
36	tf_efficientnet_b7	97.010	2.990	99.520	0.480	66.35	600	0.949	bicubic
37	efficientnetv2_rw_m	96.980	3.020	99.540	0.460	53.24	416	1.000	bicubic
38	dm_nfnet_f2	96.960	3.040	99.450	0.550	193.78	352	0.920	bicubic
39	vit_deit_base_distilled_patch16_384	96.960	3.040	99.480	0.520	87.63	384	1.000	bicubic
40	tf_efficientnet_b4_ns	96.950	3.050	99.580	0.420	19.34	380	0.922	bicubic
41	dm_nfnet_f1	96.920	3.080	99.390	0.610	132.63	320	0.910	bicubic
42	resnetrs420	96.910	3.090	99.460	0.540	191.89	416	1.000	bicubic
43	ig_resnext101_32x16d	96.820	3.180	99.590	0.410	194.03	224	0.875	bilinear
44	resnetv2_50x3_bitm	96.770	3.230	99.430	0.570	217.32	480	1.000	bilinear
45	seresnet152d	96.770	3.230	99.450	0.550	66.84	320	1.000	bicubic
46	resnetrs350	96.760	3.240	99.370	0.630	163.96	384	1.000	bicubic
47	tf_efficientnetv2_s_in21ft1k	96.730	3.270	99.420	0.580	21.46	384	1.000	bicubic
48	resnet200d	96.720	3.280	99.330	0.670	64.69	320	1.000	bicubic
49	vit_base_patch16_384	96.700	3.300	99.510	0.490	86.86	384	1.000	bicubic
50	eca_nfnet_l1	96.700	3.300	99.270	0.730	41.41	320	1.000	bicubic
51	resnetrs270	96.690	3.310	99.350	0.650	129.86	352	1.000	bicubic
52	pit_b_distilled_224	96.680	3.320	99.350	0.650	74.79	224	0.900	bicubic
53	tf_efficientnet_b5_ap	96.680	3.320	99.460	0.540	30.39	456	0.934	bicubic
54	tf_efficientnet_b6	96.670	3.330	99.370	0.630	43.04	528	0.942	bicubic
55	resnest200e	96.610	3.390	99.350	0.650	70.20	320	0.909	bicubic
56	swsl_resnext101_32x16d	96.600	3.400	99.520	0.480	194.03	224	0.875	bilinear
57	resnetrs152	96.580	3.420	99.240	0.760	86.62	320	1.000	bicubic
58	cait_xs24_384	96.550	3.450	99.420	0.580	26.67	384	1.000	bicubic
59	efficientnetv2_rw_s	96.540	3.460	99.360	0.640	23.94	384	1.000	bicubic
60	resnetrs200	96.530	3.470	99.350	0.650	93.21	320	1.000	bicubic
61	resnest269e	96.520	3.480	99.350	0.650	110.93	416	0.928	bicubic
62	vit_base_patch16_224_miil	96.460	3.540	99.300	0.700	86.54	224	0.875	bilinear
63	swsl_resnext101_32x4d	96.420	3.580	99.470	0.530	44.18	224	0.875	bilinear
64	tf_efficientnet_b3_ns	96.390	3.610	99.350	0.650	12.23	300	0.904	bicubic
65	cait_s24_224	96.380	3.620	99.150	0.850	46.92	224	1.000	bicubic
66	resnet152d	96.360	3.640	99.390	0.610	60.21	320	1.000	bicubic
67	regnety_160	96.350	3.650	99.330	0.670	83.59	288	1.000	bicubic
68	tf_efficientnet_b5	96.350	3.650	99.310	0.690	30.39	456	0.934	bicubic
69	tf_efficientnetv2_s	96.340	3.660	99.200	0.800	21.46	384	1.000	bicubic
70	ig_resnext101_32x8d	96.320	3.680	99.430	0.570	88.79	224	0.875	bilinear
71	resnet101d	96.290	3.710	99.230	0.770	44.57	320	1.000	bicubic
72	twins_svt_large	96.270	3.730	99.170	0.830	99.27	224	0.900	bicubic
73	twins_svt_base	96.160	3.840	99.060	0.940	56.07	224	0.900	bicubic
74	tf_efficientnet_b4_ap	96.160	3.840	99.280	0.720	19.34	380	0.922	bicubic
75	efficientnet_b4	96.150	3.850	99.200	0.800	19.34	384	1.000	bicubic
76	twins_pcpvt_large	96.150	3.850	99.180	0.820	60.99	224	0.900	bicubic
77	vit_deit_base_patch16_384	96.150	3.850	99.140	0.860	86.86	384	1.000	bicubic
78	dm_nfnet_f0	96.140	3.860	99.240	0.760	71.49	256	0.900	bicubic
79	nfnet_l0	96.090	3.910	99.260	0.740	35.07	288	1.000	bicubic
80	resnetv2_101x1_bitm	96.090	3.910	99.300	0.700	44.54	480	1.000	bilinear
81	vit_deit_base_distilled_patch16_224	96.090	3.910	99.190	0.810	87.34	224	0.900	bicubic
82	regnety_032	95.970	4.030	99.190	0.810	19.44	288	1.000	bicubic
83	tresnet_xl_448	95.970	4.030	99.130	0.870	78.44	448	0.875	bilinear
84	vit_large_patch16_224	95.950	4.050	99.240	0.760	304.33	224	0.900	bicubic
85	eca_nfnet_l0	95.930	4.070	99.210	0.790	24.14	288	1.000	bicubic
86	swin_small_patch4_window7_224	95.910	4.090	99.020	0.980	49.61	224	0.900	bicubic
87	tf_efficientnet_b4	95.900	4.100	99.170	0.830	19.34	380	0.922	bicubic
88	swsl_resnext50_32x4d	95.870	4.130	99.250	0.750	25.03	224	0.875	bilinear
89	resnest101e	95.860	4.140	99.210	0.790	48.28	256	0.875	bilinear
90	resnet51q	95.860	4.140	99.120	0.880	35.70	288	1.000	bilinear
91	tresnet_l_448	95.860	4.140	99.120	0.880	55.99	448	0.875	bilinear
92	cait_xxs36_384	95.850	4.150	99.090	0.910	17.37	384	1.000	bicubic
93	vit_large_patch32_384	95.830	4.170	99.150	0.850	306.63	384	1.000	bicubic
94	vit_base_patch32_384	95.810	4.190	99.150	0.850	88.30	384	1.000	bicubic
95	ssl_resnext101_32x16d	95.800	4.200	99.180	0.820	194.03	224	0.875	bilinear
96	twins_pcpvt_base	95.790	4.210	99.130	0.870	43.83	224	0.900	bicubic
97	tf_efficientnet_b2_ns	95.770	4.230	99.120	0.880	9.11	260	0.890	bicubic
98	tresnet_m	95.720	4.280	99.030	0.970	31.39	224	0.875	bilinear
99	pnasnet5large	95.710	4.290	98.920	1.080	86.06	331	0.911	bicubic
100	efficientnet_b3	95.710	4.290	99.040	0.960	12.23	320	1.000	bicubic
101	nasnetalarge	95.680	4.320	98.930	1.070	88.75	331	0.911	bicubic
102	pit_b_224	95.640	4.360	98.660	1.340	73.76	224	0.900	bicubic
103	convit_base	95.550	4.450	98.870	1.130	86.54	224	0.875	bicubic
104	coat_lite_small	95.540	4.460	98.860	1.140	19.84	224	0.900	bicubic
105	ecaresnet101d	95.530	4.470	99.130	0.870	44.57	224	0.875	bicubic
106	levit_384	95.530	4.470	99.050	0.950	39.13	224	0.900	bicubic
107	ecaresnet50t	95.510	4.490	99.120	0.880	25.57	320	0.950	bicubic
108	visformer_small	95.490	4.510	98.900	1.100	40.22	224	0.900	bicubic
109	ssl_resnext101_32x8d	95.470	4.530	99.110	0.890	88.79	224	0.875	bilinear
110	tresnet_xl	95.440	4.560	99.050	0.950	78.44	224	0.875	bilinear
111	vit_deit_base_patch16_224	95.440	4.560	98.840	1.160	86.57	224	0.900	bicubic
112	ssl_resnext101_32x4d	95.440	4.560	99.130	0.870	44.18	224	0.875	bilinear
113	resnetrs101	95.430	4.570	99.030	0.970	63.62	288	0.940	bicubic
114	swsl_resnet50	95.410	4.590	99.290	0.710	25.56	224	0.875	bilinear
115	vit_base_patch16_224	95.330	4.670	99.000	1.000	86.57	224	0.900	bicubic
116	tf_efficientnet_b3_ap	95.320	4.680	98.900	1.100	12.23	300	0.904	bicubic
117	mixer_b16_224_miil	95.300	4.700	98.880	1.120	59.88	224	0.875	bilinear
118	tresnet_l	95.290	4.710	99.010	0.990	55.99	224	0.875	bilinear
119	cait_xxs24_384	95.260	4.740	98.960	1.040	12.03	384	1.000	bicubic
120	pit_s_distilled_224	95.240	4.760	99.050	0.950	24.04	224	0.900	bicubic
121	twins_pcpvt_small	95.210	4.790	98.880	1.120	24.11	224	0.900	bicubic
122	convit_small	95.200	4.800	98.900	1.100	27.78	224	0.875	bicubic
123	twins_svt_small	95.200	4.800	98.880	1.120	24.06	224	0.900	bicubic
124	tf_efficientnet_b1_ns	95.170	4.830	99.110	0.890	7.79	240	0.882	bicubic
125	tf_efficientnetv2_b3	95.160	4.840	98.820	1.180	14.36	300	0.904	bicubic
126	swin_tiny_patch4_window7_224	95.140	4.860	98.850	1.150	28.29	224	0.900	bicubic
127	efficientnet_el	95.120	4.880	98.990	1.010	10.59	300	0.904	bicubic
128	gernet_l	95.090	4.910	98.900	1.100	31.08	256	0.875	bilinear
129	ecaresnet101d_pruned	95.080	4.920	98.980	1.020	24.88	224	0.875	bicubic
130	wide_resnet50_2	95.080	4.920	98.970	1.030	68.88	224	0.875	bicubic
131	legacy_senet154	95.070	4.930	98.830	1.170	115.09	224	0.875	bilinear
132	resnetv2_50x1_bitm	95.050	4.950	99.160	0.840	25.55	480	1.000	bilinear
133	gluon_resnet152_v1s	95.040	4.960	98.930	1.070	60.32	224	0.875	bicubic
134	seresnext50_32x4d	95.040	4.960	98.880	1.120	27.56	224	0.875	bicubic
135	tnt_s_patch16_224	95.040	4.960	98.830	1.170	23.76	224	0.900	bicubic
136	tf_efficientnet_b3	95.010	4.990	98.910	1.090	12.23	300	0.904	bicubic
137	levit_256	95.010	4.990	98.890	1.110	18.89	224	0.900	bicubic
138	tresnet_m_448	94.990	5.010	98.980	1.020	31.39	448	0.875	bilinear
139	coat_mini	94.970	5.030	98.780	1.220	10.34	224	0.900	bicubic
140	resnest50d_4s2x40d	94.960	5.040	99.070	0.930	30.42	224	0.875	bicubic
141	rexnet_200	94.940	5.060	99.010	0.990	16.37	224	0.875	bicubic
142	gluon_seresnext101_64x4d	94.930	5.070	98.830	1.170	88.23	224	0.875	bicubic
143	gluon_senet154	94.920	5.080	98.760	1.240	115.09	224	0.875	bicubic
144	gluon_seresnext101_32x4d	94.920	5.080	98.810	1.190	48.96	224	0.875	bicubic
145	tf_efficientnet_lite4	94.890	5.110	99.020	0.980	13.01	380	0.920	bilinear
146	ssl_resnext50_32x4d	94.870	5.130	98.880	1.120	25.03	224	0.875	bilinear
147	resnest50d	94.830	5.170	98.880	1.120	27.48	224	0.875	bilinear
148	ecaresnetlight	94.770	5.230	98.800	1.200	30.16	224	0.875	bicubic
149	resnest50d_1s4x24d	94.750	5.250	98.980	1.020	25.68	224	0.875	bicubic
150	gluon_resnet152_v1d	94.740	5.260	98.740	1.260	60.21	224	0.875	bicubic
151	gluon_resnet101_v1s	94.720	5.280	98.820	1.180	44.67	224	0.875	bicubic
152	vit_deit_small_distilled_patch16_224	94.710	5.290	99.030	0.970	22.44	224	0.900	bicubic
153	gluon_resnext101_64x4d	94.670	5.330	98.650	1.350	83.46	224	0.875	bicubic
154	cspdarknet53	94.660	5.340	98.800	1.200	27.64	256	0.887	bilinear
155	ecaresnet50d	94.630	5.370	98.890	1.110	25.58	224	0.875	bicubic
156	efficientnet_b3_pruned	94.630	5.370	98.760	1.240	9.86	300	0.904	bicubic
157	gernet_m	94.620	5.380	98.860	1.140	21.14	224	0.875	bilinear
158	efficientnet_b2	94.610	5.390	98.710	1.290	9.11	288	1.000	bicubic
159	nf_resnet50	94.590	5.410	98.810	1.190	25.56	288	0.940	bicubic
160	pit_s_224	94.590	5.410	98.710	1.290	23.46	224	0.900	bicubic
161	repvgg_b3	94.570	5.430	98.780	1.220	123.09	224	0.875	bilinear
162	seresnet50	94.550	5.450	98.750	1.250	28.09	224	0.875	bicubic
163	inception_resnet_v2	94.540	5.460	98.790	1.210	55.84	299	0.897	bicubic
164	regnety_320	94.540	5.460	98.850	1.150	145.05	224	0.875	bicubic
165	gluon_resnext101_32x4d	94.530	5.470	98.630	1.370	44.18	224	0.875	bicubic
166	repvgg_b3g4	94.520	5.480	98.970	1.030	83.83	224	0.875	bilinear
167	tf_efficientnet_b2_ap	94.490	5.510	98.620	1.380	9.11	260	0.890	bicubic
168	cspresnext50	94.480	5.520	98.680	1.320	20.57	224	0.875	bilinear
169	regnety_120	94.480	5.520	98.810	1.190	51.82	224	0.875	bicubic
170	rexnet_150	94.480	5.520	98.790	1.210	9.73	224	0.875	bicubic
171	regnetx_320	94.460	5.540	98.740	1.260	107.81	224	0.875	bicubic
172	ssl_resnet50	94.450	5.550	98.920	1.080	25.56	224	0.875	bilinear
173	tf_efficientnetv2_b2	94.420	5.580	98.570	1.430	10.10	260	0.890	bicubic
174	tf_efficientnet_el	94.410	5.590	98.710	1.290	10.59	300	0.904	bicubic
175	efficientnet_el_pruned	94.400	5.600	98.740	1.260	10.59	300	0.904	bicubic
176	vit_deit_small_patch16_224	94.400	5.600	98.690	1.310	22.05	224	0.900	bicubic
177	inception_v4	94.380	5.620	98.580	1.420	42.68	299	0.875	bicubic
178	legacy_seresnext101_32x4d	94.370	5.630	98.650	1.350	48.96	224	0.875	bilinear
179	tf_efficientnet_b2	94.360	5.640	98.610	1.390	9.11	260	0.890	bicubic
180	gluon_seresnext50_32x4d	94.340	5.660	98.610	1.390	27.56	224	0.875	bicubic
181	dpn107	94.310	5.690	98.480	1.520	86.92	224	0.875	bicubic
182	ecaresnet26t	94.310	5.690	98.720	1.280	16.01	320	0.950	bicubic
183	resnetrs50	94.310	5.690	98.640	1.360	35.69	224	0.910	bicubic
184	xception71	94.280	5.720	98.640	1.360	42.34	299	0.903	bicubic
185	resnet50d	94.260	5.740	98.720	1.280	25.58	224	0.875	bicubic
186	skresnext50_32x4d	94.260	5.740	98.460	1.540	27.48	224	0.875	bicubic
187	gluon_xception65	94.260	5.740	98.570	1.430	39.92	299	0.903	bicubic
188	cait_xxs36_224	94.260	5.740	98.720	1.280	17.30	224	1.000	bicubic
189	regnetx_120	94.240	5.760	98.650	1.350	46.11	224	0.875	bicubic
190	dpn92	94.230	5.770	98.730	1.270	37.67	224	0.875	bicubic
191	ecaresnet50d_pruned	94.220	5.780	98.730	1.270	19.94	224	0.875	bicubic
192	gluon_resnet101_v1d	94.220	5.780	98.550	1.450	44.57	224	0.875	bicubic
193	tf_efficientnet_lite3	94.200	5.800	98.640	1.360	8.20	300	0.904	bilinear
194	mixnet_xl	94.190	5.810	98.340	1.660	11.90	224	0.875	bicubic
195	resnext50d_32x4d	94.180	5.820	98.570	1.430	25.05	224	0.875	bicubic
196	levit_192	94.170	5.830	98.540	1.460	10.95	224	0.900	bicubic
197	regnety_080	94.170	5.830	98.680	1.320	39.18	224	0.875	bicubic
198	gluon_resnet152_v1c	94.160	5.840	98.640	1.360	60.21	224	0.875	bicubic
199	ens_adv_inception_resnet_v2	94.160	5.840	98.600	1.400	55.84	299	0.897	bicubic
200	regnety_064	94.150	5.850	98.730	1.270	30.58	224	0.875	bicubic
201	efficientnet_b2_pruned	94.140	5.860	98.530	1.470	8.31	260	0.890	bicubic
202	dpn98	94.130	5.870	98.570	1.430	61.57	224	0.875	bicubic
203	nf_regnet_b1	94.130	5.870	98.630	1.370	10.22	288	0.900	bicubic
204	regnetx_160	94.120	5.880	98.750	1.250	54.28	224	0.875	bicubic
205	resnext50_32x4d	94.100	5.900	98.350	1.650	25.03	224	0.875	bicubic
206	ese_vovnet39b	94.090	5.910	98.660	1.340	24.57	224	0.875	bicubic
207	gluon_resnet152_v1b	94.080	5.920	98.450	1.550	60.19	224	0.875	bicubic
208	coat_lite_mini	94.060	5.940	98.560	1.440	11.01	224	0.900	bicubic
209	dpn131	94.010	5.990	98.720	1.280	79.25	224	0.875	bicubic
210	hrnet_w64	94.010	5.990	98.610	1.390	128.06	224	0.875	bilinear
211	resnetblur50	93.960	6.040	98.590	1.410	25.56	224	0.875	bicubic
212	dla102x2	93.950	6.050	98.490	1.510	41.28	224	0.875	bilinear
213	tf_efficientnetv2_b1	93.940	6.060	98.620	1.380	8.14	240	0.882	bicubic
214	hrnet_w48	93.920	6.080	98.610	1.390	77.47	224	0.875	bilinear
215	rexnet_130	93.900	6.100	98.400	1.600	7.56	224	0.875	bicubic
216	tf_efficientnet_cc_b1_8e	93.900	6.100	98.260	1.740	39.72	240	0.882	bicubic
217	regnetx_064	93.890	6.110	98.630	1.370	26.21	224	0.875	bicubic
218	regnetx_080	93.870	6.130	98.520	1.480	39.57	224	0.875	bicubic
219	regnety_040	93.860	6.140	98.650	1.350	20.65	224	0.875	bicubic
220	repvgg_b2g4	93.860	6.140	98.590	1.410	61.76	224	0.875	bilinear
221	efficientnet_em	93.840	6.160	98.810	1.190	6.90	240	0.882	bicubic
222	resnext101_32x8d	93.830	6.170	98.580	1.420	88.79	224	0.875	bilinear
223	resnet50	93.810	6.190	98.390	1.610	25.56	224	0.875	bicubic
224	pit_xs_distilled_224	93.810	6.190	98.670	1.330	11.00	224	0.900	bicubic
225	gluon_resnext50_32x4d	93.810	6.190	98.410	1.590	25.03	224	0.875	bicubic
226	gluon_resnet50_v1d	93.770	6.230	98.390	1.610	25.58	224	0.875	bicubic
227	xception65	93.760	6.240	98.370	1.630	39.92	299	0.903	bicubic
228	gluon_resnet101_v1b	93.750	6.250	98.380	1.620	44.55	224	0.875	bicubic
229	res2net101_26w_4s	93.750	6.250	98.310	1.690	45.21	224	0.875	bilinear
230	cspresnet50	93.740	6.260	98.640	1.360	21.62	256	0.887	bilinear
231	legacy_seresnext50_32x4d	93.730	6.270	98.580	1.420	27.56	224	0.875	bilinear
232	wide_resnet101_2	93.720	6.280	98.540	1.460	126.89	224	0.875	bilinear
233	dpn68b	93.690	6.310	98.510	1.490	12.61	224	0.875	bicubic
234	tf_efficientnet_b1_ap	93.690	6.310	98.360	1.640	7.79	240	0.882	bicubic
235	gluon_resnet101_v1c	93.670	6.330	98.420	1.580	44.57	224	0.875	bicubic
236	tf_efficientnet_b0_ns	93.630	6.370	98.640	1.360	5.29	224	0.875	bicubic
237	gluon_resnet50_v1s	93.620	6.380	98.460	1.540	25.68	224	0.875	bicubic
238	cait_xxs24_224	93.600	6.400	98.440	1.560	11.96	224	1.000	bicubic
239	coat_tiny	93.590	6.410	98.430	1.570	5.50	224	0.900	bicubic
240	regnetx_040	93.560	6.440	98.540	1.460	22.12	224	0.875	bicubic
241	hrnet_w44	93.550	6.450	98.700	1.300	67.06	224	0.875	bilinear
242	res2net50_26w_8s	93.540	6.460	98.260	1.740	48.40	224	0.875	bilinear
243	hrnet_w32	93.530	6.470	98.450	1.550	41.23	224	0.875	bilinear
244	dla102x	93.520	6.480	98.510	1.490	26.31	224	0.875	bilinear
245	repvgg_b2	93.500	6.500	98.730	1.270	89.02	224	0.875	bilinear
246	tf_efficientnet_b1	93.500	6.500	98.360	1.640	7.79	240	0.882	bicubic
247	hrnet_w40	93.490	6.510	98.580	1.420	57.56	224	0.875	bilinear
248	xception	93.460	6.540	98.530	1.470	22.86	299	0.897	bicubic
249	gluon_inception_v3	93.460	6.540	98.570	1.430	23.83	299	0.875	bicubic
250	mixnet_l	93.450	6.550	98.220	1.780	7.33	224	0.875	bicubic
251	xception41	93.430	6.570	98.430	1.570	26.97	299	0.903	bicubic
252	res2net50_26w_6s	93.410	6.590	98.280	1.720	37.05	224	0.875	bilinear
253	legacy_seresnet152	93.400	6.600	98.350	1.650	66.82	224	0.875	bilinear
254	dla169	93.340	6.660	98.600	1.400	53.39	224	0.875	bilinear
255	levit_128	93.340	6.660	98.380	1.620	9.21	224	0.900	bicubic
256	repvgg_b1	93.330	6.670	98.510	1.490	57.42	224	0.875	bilinear
257	resnest26d	93.330	6.670	98.630	1.370	17.07	224	0.875	bilinear
258	tf_inception_v3	93.320	6.680	98.030	1.970	23.83	299	0.875	bicubic
259	tf_mixnet_l	93.310	6.690	98.030	1.970	7.33	224	0.875	bicubic
260	tv_resnet152	93.300	6.700	98.390	1.610	60.19	224	0.875	bilinear
261	selecsls60b	93.300	6.700	98.280	1.720	32.77	224	0.875	bicubic
262	legacy_seresnet101	93.280	6.720	98.510	1.490	49.33	224	0.875	bilinear
263	efficientnet_b1	93.250	6.750	98.290	1.710	7.79	256	1.000	bicubic
264	coat_lite_tiny	93.240	6.760	98.260	1.740	5.72	224	0.900	bicubic
265	hrnet_w30	93.200	6.800	98.410	1.590	37.71	224	0.875	bilinear
266	dla60_res2net	93.180	6.820	98.420	1.580	20.85	224	0.875	bilinear
267	dla60_res2next	93.180	6.820	98.410	1.590	17.03	224	0.875	bilinear
268	efficientnet_es	93.140	6.860	98.420	1.580	5.44	224	0.875	bicubic
269	dla60x	93.120	6.880	98.510	1.490	17.35	224	0.875	bilinear
270	regnetx_032	93.120	6.880	98.390	1.610	15.30	224	0.875	bicubic
271	pit_xs_224	93.110	6.890	98.310	1.690	10.62	224	0.900	bicubic
272	tf_efficientnetv2_b0	93.110	6.890	98.390	1.610	7.14	224	0.875	bicubic
273	dla102	93.060	6.940	98.540	1.460	33.27	224	0.875	bilinear
274	gluon_resnet50_v1c	93.030	6.970	98.390	1.610	25.58	224	0.875	bicubic
275	regnety_016	93.030	6.970	98.360	1.640	11.20	224	0.875	bicubic
276	rexnet_100	93.030	6.970	98.190	1.810	4.80	224	0.875	bicubic
277	selecsls60	93.030	6.970	98.300	1.700	30.67	224	0.875	bicubic
278	repvgg_b1g4	92.980	7.020	98.430	1.570	39.97	224	0.875	bilinear
279	legacy_seresnet50	92.960	7.040	98.190	1.810	28.09	224	0.875	bilinear
280	hardcorenas_f	92.950	7.050	98.160	1.840	8.20	224	0.875	bilinear
281	tf_efficientnet_em	92.930	7.070	98.190	1.810	6.90	240	0.882	bicubic
282	adv_inception_v3	92.880	7.120	98.140	1.860	23.83	299	0.875	bicubic
283	res2next50	92.840	7.160	98.180	1.820	24.67	224	0.875	bilinear
284	tf_efficientnet_cc_b0_8e	92.830	7.170	98.180	1.820	24.01	224	0.875	bicubic
285	seresnext26t_32x4d	92.820	7.180	98.370	1.630	16.81	224	0.875	bicubic
286	tv_resnet101	92.810	7.190	98.250	1.750	44.55	224	0.875	bilinear
287	efficientnet_b1_pruned	92.770	7.230	98.040	1.960	6.33	240	0.882	bicubic
288	vit_small_patch16_224	92.760	7.240	97.930	2.070	48.75	224	0.900	bicubic
289	densenet201	92.750	7.250	98.230	1.770	20.01	224	0.875	bicubic
290	res2net50_14w_8s	92.740	7.260	98.180	1.820	25.06	224	0.875	bilinear
291	tv_resnext50_32x4d	92.740	7.260	98.270	1.730	25.03	224	0.875	bilinear
292	inception_v3	92.720	7.280	97.970	2.030	23.83	299	0.875	bicubic
293	seresnext26d_32x4d	92.700	7.300	98.150	1.850	16.81	224	0.875	bicubic
294	efficientnet_b0	92.690	7.310	98.070	1.930	5.29	224	0.875	bicubic
295	resnet34d	92.680	7.320	98.310	1.690	21.82	224	0.875	bicubic
296	tf_efficientnet_lite2	92.650	7.350	98.230	1.770	6.09	260	0.890	bicubic
297	legacy_seresnext26_32x4d	92.640	7.360	98.130	1.870	16.79	224	0.875	bicubic
298	tf_efficientnet_lite1	92.620	7.380	98.080	1.920	5.42	240	0.882	bicubic
299	tf_efficientnet_cc_b0_4e	92.590	7.410	98.080	1.920	13.31	224	0.875	bicubic
300	hardcorenas_e	92.570	7.430	98.110	1.890	8.07	224	0.875	bilinear
301	res2net50_48w_2s	92.550	7.450	98.080	1.920	25.29	224	0.875	bilinear
302	gluon_resnet50_v1b	92.540	7.460	98.170	1.830	25.56	224	0.875	bicubic
303	densenet161	92.500	7.500	98.290	1.710	28.68	224	0.875	bicubic
304	res2net50_26w_4s	92.500	7.500	98.060	1.940	25.70	224	0.875	bilinear
305	mixnet_m	92.430	7.570	97.870	2.130	5.01	224	0.875	bicubic
306	hardcorenas_d	92.400	7.600	98.070	1.930	7.50	224	0.875	bilinear
307	mobilenetv2_120d	92.400	7.600	98.050	1.950	5.83	224	0.875	bicubic
308	skresnet34	92.390	7.610	98.150	1.850	22.28	224	0.875	bicubic
309	tf_mixnet_m	92.330	7.670	97.890	2.110	5.01	224	0.875	bicubic
310	hrnet_w18	92.320	7.680	98.240	1.760	21.30	224	0.875	bilinear
311	ese_vovnet19b_dw	92.290	7.710	98.090	1.910	6.54	224	0.875	bicubic
312	selecsls42b	92.280	7.720	98.150	1.850	32.46	224	0.875	bicubic
313	mobilenetv3_large_100_miil	92.260	7.740	97.640	2.360	5.48	224	0.875	bilinear
314	tf_efficientnet_b0	92.250	7.750	98.000	2.000	5.29	224	0.875	bicubic
315	dla60	92.230	7.770	98.110	1.890	22.04	224	0.875	bilinear
316	tf_efficientnet_b0_ap	92.200	7.800	98.020	1.980	5.29	224	0.875	bicubic
317	regnetx_016	92.170	7.830	98.210	1.790	9.19	224	0.875	bicubic
318	gernet_s	92.140	7.860	98.190	1.810	8.17	224	0.875	bilinear
319	resnet26d	92.070	7.930	97.960	2.040	16.01	224	0.875	bicubic
320	hardcorenas_c	92.020	7.980	97.840	2.160	5.52	224	0.875	bilinear
321	dpn68	92.010	7.990	98.050	1.950	12.61	224	0.875	bicubic
322	tf_efficientnet_es	91.980	8.020	97.860	2.140	5.44	224	0.875	bicubic
323	levit_128s	91.970	8.030	98.060	1.940	7.78	224	0.900	bicubic
324	repvgg_a2	91.940	8.060	98.150	1.850	28.21	224	0.875	bilinear
325	densenet169	91.930	8.070	98.100	1.900	14.15	224	0.875	bicubic
326	densenetblur121d	91.910	8.090	98.070	1.930	8.00	224	0.875	bicubic
327	tv_resnet50	91.880	8.120	98.040	1.960	25.56	224	0.875	bilinear
328	mixer_b16_224	91.870	8.130	97.250	2.750	59.88	224	0.875	bicubic
329	mixnet_s	91.830	8.170	97.690	2.310	4.13	224	0.875	bicubic
330	mobilenetv2_140	91.830	8.170	97.860	2.140	6.11	224	0.875	bicubic
331	hardcorenas_b	91.770	8.230	97.780	2.220	5.18	224	0.875	bilinear
332	regnety_008	91.750	8.250	98.180	1.820	6.26	224	0.875	bicubic
333	resnest14d	91.720	8.280	97.870	2.130	10.61	224	0.875	bilinear
334	densenet121	91.570	8.430	98.030	1.970	7.98	224	0.875	bicubic
335	tf_mixnet_s	91.510	8.490	97.620	2.380	4.13	224	0.875	bicubic
336	repvgg_b0	91.430	8.570	97.990	2.010	15.82	224	0.875	bilinear
337	regnety_006	91.370	8.630	97.710	2.290	6.06	224	0.875	bicubic
338	hardcorenas_a	91.350	8.650	97.860	2.140	5.26	224	0.875	bilinear
339	mobilenetv3_large_100	91.320	8.680	97.710	2.290	5.48	224	0.875	bicubic
340	semnasnet_100	91.280	8.720	97.560	2.440	3.89	224	0.875	bicubic
341	tf_mobilenetv3_large_100	91.240	8.760	97.660	2.340	5.48	224	0.875	bilinear
342	mobilenetv3_rw	91.210	8.790	97.660	2.340	5.48	224	0.875	bicubic
343	hrnet_w18_small_v2	91.190	8.810	97.900	2.100	15.60	224	0.875	bilinear
344	efficientnet_es_pruned	91.180	8.820	97.750	2.250	5.44	224	0.875	bicubic
345	efficientnet_lite0	91.140	8.860	97.630	2.370	4.65	224	0.875	bicubic
346	resnet34	91.130	8.870	97.620	2.380	21.80	224	0.875	bilinear
347	resnet26	91.110	8.890	97.740	2.260	16.00	224	0.875	bicubic
348	regnetx_008	91.050	8.950	97.710	2.290	7.26	224	0.875	bicubic
349	tf_efficientnet_lite0	91.040	8.960	97.590	2.410	4.65	224	0.875	bicubic
350	gluon_resnet34_v1b	90.960	9.040	97.630	2.370	21.80	224	0.875	bicubic
351	mobilenetv2_110d	90.950	9.050	97.550	2.450	4.52	224	0.875	bicubic
352	pit_ti_distilled_224	90.900	9.100	97.700	2.300	5.10	224	0.900	bicubic
353	legacy_seresnet34	90.890	9.110	97.580	2.420	21.96	224	0.875	bilinear
354	tv_densenet121	90.890	9.110	97.710	2.290	7.98	224	0.875	bicubic
355	dla34	90.760	9.240	97.660	2.340	15.74	224	0.875	bilinear
356	fbnetc_100	90.700	9.300	97.210	2.790	5.57	224	0.875	bilinear
357	vit_deit_tiny_distilled_patch16_224	90.700	9.300	97.570	2.430	5.91	224	0.900	bicubic
358	swsl_resnet18	90.690	9.310	97.700	2.300	11.69	224	0.875	bilinear
359	convit_tiny	90.630	9.370	97.740	2.260	5.71	224	0.875	bicubic
360	mnasnet_100	90.510	9.490	97.470	2.530	4.38	224	0.875	bicubic
361	regnety_004	90.500	9.500	97.540	2.460	4.34	224	0.875	bicubic
362	regnetx_006	90.350	9.650	97.430	2.570	6.20	224	0.875	bicubic
363	spnasnet_100	90.350	9.650	97.190	2.810	4.42	224	0.875	bilinear
364	ssl_resnet18	90.220	9.780	97.550	2.450	11.69	224	0.875	bilinear
365	vgg16_bn	90.090	9.910	97.370	2.630	138.37	224	0.875	bilinear
366	vgg19_bn	90.080	9.920	97.580	2.420	143.68	224	0.875	bilinear
367	ghostnet_100	90.020	9.980	97.370	2.630	5.18	224	0.875	bilinear
368	pit_ti_224	89.940	10.060	97.450	2.550	4.85	224	0.900	bicubic
369	tv_resnet34	89.940	10.060	97.340	2.660	21.80	224	0.875	bilinear
370	tf_mobilenetv3_large_075	89.680	10.320	97.210	2.790	3.99	224	0.875	bilinear
371	vit_deit_tiny_patch16_224	89.670	10.330	97.450	2.550	5.72	224	0.900	bicubic
372	skresnet18	89.660	10.340	97.230	2.770	11.96	224	0.875	bicubic
373	mobilenetv2_100	89.600	10.400	97.140	2.860	3.50	224	0.875	bicubic
374	resnet18d	89.280	10.720	97.150	2.850	11.71	224	0.875	bicubic
375	hrnet_w18_small	89.050	10.950	97.110	2.890	13.19	224	0.875	bilinear
376	vgg19	89.040	10.960	96.870	3.130	143.67	224	0.875	bilinear
377	tf_mobilenetv3_large_minimal_100	88.970	11.030	96.860	3.140	3.92	224	0.875	bilinear
378	regnetx_004	88.900	11.100	97.120	2.880	5.16	224	0.875	bicubic
379	legacy_seresnet18	88.880	11.120	96.980	3.020	11.78	224	0.875	bicubic
380	vgg13_bn	88.760	11.240	96.970	3.030	133.05	224	0.875	bilinear
381	vgg16	88.550	11.450	96.790	3.210	138.36	224	0.875	bilinear
382	gluon_resnet18_v1b	88.400	11.600	96.680	3.320	11.69	224	0.875	bicubic
383	vgg11_bn	87.500	12.500	96.820	3.180	132.87	224	0.875	bilinear
384	resnet18	87.390	12.610	96.290	3.710	11.69	224	0.875	bilinear
385	regnety_002	87.380	12.620	96.590	3.410	3.16	224	0.875	bicubic
386	mixer_l16_224	87.150	12.850	93.520	6.480	208.20	224	0.875	bicubic
387	vgg13	87.050	12.950	96.320	3.680	133.05	224	0.875	bilinear
388	vgg11	86.550	13.450	96.280	3.720	132.86	224	0.875	bilinear
389	dla60x_c	86.290	13.710	96.160	3.840	1.32	224	0.875	bilinear
390	regnetx_002	86.190	13.810	95.980	4.020	2.68	224	0.875	bicubic
391	tf_mobilenetv3_small_100	85.190	14.810	95.770	4.230	2.54	224	0.875	bilinear
392	dla46x_c	84.250	15.750	95.270	4.730	1.07	224	0.875	bilinear
393	dla46_c	83.650	16.350	94.920	5.080	1.30	224	0.875	bilinear
394	tf_mobilenetv3_small_075	83.520	16.480	94.790	5.210	2.04	224	0.875	bilinear
395	tf_mobilenetv3_small_minimal_100	81.380	18.620	93.670	6.330	2.04	224	0.875	bilinear