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	swin_large_patch4_window7_224	97.650	2.350	99.580	0.420	196.53	224	0.900	bicubic
9	tf_efficientnet_b6_ns	97.630	2.370	99.580	0.420	43.04	528	0.942	bicubic
10	ig_resnext101_32x48d	97.620	2.380	99.700	0.300	828.41	224	0.875	bilinear
11	dm_nfnet_f5	97.600	2.400	99.550	0.450	377.21	544	0.954	bicubic
12	dm_nfnet_f4	97.570	2.430	99.520	0.480	316.07	512	0.951	bicubic
13	tf_efficientnet_b5_ns	97.500	2.500	99.630	0.370	30.39	456	0.934	bicubic
14	resnetv2_152x4_bitm	97.490	2.510	99.600	0.400	936.53	480	1.000	bilinear
15	cait_m48_448	97.480	2.520	99.550	0.450	356.46	448	1.000	bicubic
16	cait_m36_384	97.400	2.600	99.510	0.490	271.22	384	1.000	bicubic
17	dm_nfnet_f3	97.360	2.640	99.580	0.420	254.92	416	0.940	bicubic
18	ig_resnext101_32x32d	97.360	2.640	99.680	0.320	468.53	224	0.875	bilinear
19	cait_s36_384	97.330	2.670	99.530	0.470	68.37	384	1.000	bicubic
20	swin_base_patch4_window7_224	97.250	2.750	99.530	0.470	87.77	224	0.900	bicubic
21	swsl_resnext101_32x8d	97.200	2.800	99.570	0.430	88.79	224	0.875	bilinear
22	tf_efficientnet_b7_ap	97.200	2.800	99.540	0.460	66.35	600	0.949	bicubic
23	tf_efficientnet_b8	97.200	2.800	99.500	0.500	87.41	672	0.954	bicubic
24	vit_base_r50_s16_384	97.180	2.820	99.560	0.440	98.95	384	1.000	bicubic
25	resnetv2_152x2_bitm	97.150	2.850	99.590	0.410	236.34	480	1.000	bilinear
26	tf_efficientnet_b8_ap	97.110	2.890	99.660	0.340	87.41	672	0.954	bicubic
27	vit_large_patch16_384	97.110	2.890	99.640	0.360	304.72	384	1.000	bicubic
28	ecaresnet269d	97.080	2.920	99.470	0.530	102.09	352	1.000	bicubic
29	tf_efficientnet_b6_ap	97.080	2.920	99.620	0.380	43.04	528	0.942	bicubic
30	cait_s24_384	97.070	2.930	99.430	0.570	47.06	384	1.000	bicubic
31	resnetv2_101x3_bitm	97.050	2.950	99.520	0.480	387.93	480	1.000	bilinear
32	tf_efficientnet_b7	97.010	2.990	99.520	0.480	66.35	600	0.949	bicubic
33	dm_nfnet_f2	96.960	3.040	99.450	0.550	193.78	352	0.920	bicubic
34	vit_deit_base_distilled_patch16_384	96.960	3.040	99.480	0.520	87.63	384	1.000	bicubic
35	tf_efficientnet_b4_ns	96.950	3.050	99.580	0.420	19.34	380	0.922	bicubic
36	dm_nfnet_f1	96.920	3.080	99.390	0.610	132.63	320	0.910	bicubic
37	resnetrs420	96.910	3.090	99.460	0.540	191.89	416	1.000	bicubic
38	ig_resnext101_32x16d	96.820	3.180	99.590	0.410	194.03	224	0.875	bilinear
39	resnetv2_50x3_bitm	96.770	3.230	99.430	0.570	217.32	480	1.000	bilinear
40	seresnet152d	96.770	3.230	99.450	0.550	66.84	320	1.000	bicubic
41	resnetrs350	96.760	3.240	99.370	0.630	163.96	384	1.000	bicubic
42	resnet200d	96.720	3.280	99.330	0.670	64.69	320	1.000	bicubic
43	eca_nfnet_l1	96.700	3.300	99.270	0.730	41.41	320	1.000	bicubic
44	vit_base_patch16_384	96.700	3.300	99.510	0.490	86.86	384	1.000	bicubic
45	resnetrs270	96.690	3.310	99.350	0.650	129.86	352	1.000	bicubic
46	tf_efficientnet_b5_ap	96.680	3.320	99.460	0.540	30.39	456	0.934	bicubic
47	pit_b_distilled_224	96.680	3.320	99.350	0.650	74.79	224	0.900	bicubic
48	tf_efficientnet_b6	96.670	3.330	99.370	0.630	43.04	528	0.942	bicubic
49	resnest200e	96.610	3.390	99.350	0.650	70.20	320	0.909	bicubic
50	swsl_resnext101_32x16d	96.600	3.400	99.520	0.480	194.03	224	0.875	bilinear
51	resnetrs152	96.580	3.420	99.240	0.760	86.62	320	1.000	bicubic
52	cait_xs24_384	96.550	3.450	99.420	0.580	26.67	384	1.000	bicubic
53	efficientnet_v2s	96.540	3.460	99.360	0.640	23.94	384	1.000	bicubic
54	resnetrs200	96.530	3.470	99.350	0.650	93.21	320	1.000	bicubic
55	resnest269e	96.520	3.480	99.350	0.650	110.93	416	0.928	bicubic
56	vit_base_patch16_224_miil	96.460	3.540	99.300	0.700	86.54	224	0.875	bilinear
57	swsl_resnext101_32x4d	96.420	3.580	99.470	0.530	44.18	224	0.875	bilinear
58	tf_efficientnet_b3_ns	96.390	3.610	99.350	0.650	12.23	300	0.904	bicubic
59	cait_s24_224	96.380	3.620	99.150	0.850	46.92	224	1.000	bicubic
60	resnet152d	96.360	3.640	99.390	0.610	60.21	320	1.000	bicubic
61	regnety_160	96.350	3.650	99.330	0.670	83.59	288	1.000	bicubic
62	tf_efficientnet_b5	96.350	3.650	99.310	0.690	30.39	456	0.934	bicubic
63	ig_resnext101_32x8d	96.320	3.680	99.430	0.570	88.79	224	0.875	bilinear
64	resnet101d	96.290	3.710	99.230	0.770	44.57	320	1.000	bicubic
65	tf_efficientnet_b4_ap	96.160	3.840	99.280	0.720	19.34	380	0.922	bicubic
66	efficientnet_b4	96.150	3.850	99.200	0.800	19.34	384	1.000	bicubic
67	vit_deit_base_patch16_384	96.150	3.850	99.140	0.860	86.86	384	1.000	bicubic
68	dm_nfnet_f0	96.140	3.860	99.240	0.760	71.49	256	0.900	bicubic
69	vit_deit_base_distilled_patch16_224	96.090	3.910	99.190	0.810	87.34	224	0.900	bicubic
70	nfnet_l0	96.090	3.910	99.260	0.740	35.07	288	1.000	bicubic
71	resnetv2_101x1_bitm	96.090	3.910	99.300	0.700	44.54	480	1.000	bilinear
72	regnety_032	95.970	4.030	99.190	0.810	19.44	288	1.000	bicubic
73	tresnet_xl_448	95.970	4.030	99.130	0.870	78.44	448	0.875	bilinear
74	vit_large_patch16_224	95.950	4.050	99.240	0.760	304.33	224	0.900	bicubic
75	eca_nfnet_l0	95.930	4.070	99.210	0.790	24.14	288	1.000	bicubic
76	swin_small_patch4_window7_224	95.910	4.090	99.020	0.980	49.61	224	0.900	bicubic
77	tf_efficientnet_b4	95.900	4.100	99.170	0.830	19.34	380	0.922	bicubic
78	swsl_resnext50_32x4d	95.870	4.130	99.250	0.750	25.03	224	0.875	bilinear
79	resnest101e	95.860	4.140	99.210	0.790	48.28	256	0.875	bilinear
80	tresnet_l_448	95.860	4.140	99.120	0.880	55.99	448	0.875	bilinear
81	cait_xxs36_384	95.850	4.150	99.090	0.910	17.37	384	1.000	bicubic
82	vit_large_patch32_384	95.830	4.170	99.150	0.850	306.63	384	1.000	bicubic
83	vit_base_patch32_384	95.810	4.190	99.150	0.850	88.30	384	1.000	bicubic
84	ssl_resnext101_32x16d	95.800	4.200	99.180	0.820	194.03	224	0.875	bilinear
85	tf_efficientnet_b2_ns	95.770	4.230	99.120	0.880	9.11	260	0.890	bicubic
86	tresnet_m	95.720	4.280	99.030	0.970	31.39	224	0.875	bilinear
87	efficientnet_b3	95.710	4.290	99.040	0.960	12.23	320	1.000	bicubic
88	pnasnet5large	95.710	4.290	98.920	1.080	86.06	331	0.911	bicubic
89	nasnetalarge	95.680	4.320	98.930	1.070	88.75	331	0.911	bicubic
90	pit_b_224	95.640	4.360	98.660	1.340	73.76	224	0.900	bicubic
91	ecaresnet101d	95.530	4.470	99.130	0.870	44.57	224	0.875	bicubic
92	ecaresnet50t	95.510	4.490	99.120	0.880	25.57	320	0.950	bicubic
93	ssl_resnext101_32x8d	95.470	4.530	99.110	0.890	88.79	224	0.875	bilinear
94	ssl_resnext101_32x4d	95.440	4.560	99.130	0.870	44.18	224	0.875	bilinear
95	tresnet_xl	95.440	4.560	99.050	0.950	78.44	224	0.875	bilinear
96	vit_deit_base_patch16_224	95.440	4.560	98.840	1.160	86.57	224	0.900	bicubic
97	resnetrs101	95.430	4.570	99.030	0.970	63.62	288	0.940	bicubic
98	swsl_resnet50	95.410	4.590	99.290	0.710	25.56	224	0.875	bilinear
99	vit_base_patch16_224	95.330	4.670	99.000	1.000	86.57	224	0.900	bicubic
100	tf_efficientnet_b3_ap	95.320	4.680	98.900	1.100	12.23	300	0.904	bicubic
101	tresnet_l	95.290	4.710	99.010	0.990	55.99	224	0.875	bilinear
102	cait_xxs24_384	95.260	4.740	98.960	1.040	12.03	384	1.000	bicubic
103	pit_s_distilled_224	95.240	4.760	99.050	0.950	24.04	224	0.900	bicubic
104	tf_efficientnet_b1_ns	95.170	4.830	99.110	0.890	7.79	240	0.882	bicubic
105	swin_tiny_patch4_window7_224	95.140	4.860	98.850	1.150	28.29	224	0.900	bicubic
106	efficientnet_el	95.120	4.880	98.990	1.010	10.59	300	0.904	bicubic
107	gernet_l	95.090	4.910	98.900	1.100	31.08	256	0.875	bilinear
108	ecaresnet101d_pruned	95.080	4.920	98.980	1.020	24.88	224	0.875	bicubic
109	wide_resnet50_2	95.080	4.920	98.970	1.030	68.88	224	0.875	bicubic
110	legacy_senet154	95.070	4.930	98.830	1.170	115.09	224	0.875	bilinear
111	resnetv2_50x1_bitm	95.050	4.950	99.160	0.840	25.55	480	1.000	bilinear
112	gluon_resnet152_v1s	95.040	4.960	98.930	1.070	60.32	224	0.875	bicubic
113	seresnext50_32x4d	95.040	4.960	98.880	1.120	27.56	224	0.875	bicubic
114	tnt_s_patch16_224	95.040	4.960	98.830	1.170	23.76	224	0.900	bicubic
115	tf_efficientnet_b3	95.010	4.990	98.910	1.090	12.23	300	0.904	bicubic
116	tresnet_m_448	94.990	5.010	98.980	1.020	31.39	448	0.875	bilinear
117	resnest50d_4s2x40d	94.960	5.040	99.070	0.930	30.42	224	0.875	bicubic
118	rexnet_200	94.940	5.060	99.010	0.990	16.37	224	0.875	bicubic
119	gluon_seresnext101_64x4d	94.930	5.070	98.830	1.170	88.23	224	0.875	bicubic
120	gluon_senet154	94.920	5.080	98.760	1.240	115.09	224	0.875	bicubic
121	gluon_seresnext101_32x4d	94.920	5.080	98.810	1.190	48.96	224	0.875	bicubic
122	tf_efficientnet_lite4	94.890	5.110	99.020	0.980	13.01	380	0.920	bilinear
123	ssl_resnext50_32x4d	94.870	5.130	98.880	1.120	25.03	224	0.875	bilinear
124	resnest50d	94.830	5.170	98.880	1.120	27.48	224	0.875	bilinear
125	ecaresnetlight	94.770	5.230	98.800	1.200	30.16	224	0.875	bicubic
126	resnest50d_1s4x24d	94.750	5.250	98.980	1.020	25.68	224	0.875	bicubic
127	gluon_resnet152_v1d	94.740	5.260	98.740	1.260	60.21	224	0.875	bicubic
128	gluon_resnet101_v1s	94.720	5.280	98.820	1.180	44.67	224	0.875	bicubic
129	vit_deit_small_distilled_patch16_224	94.710	5.290	99.030	0.970	22.44	224	0.900	bicubic
130	gluon_resnext101_64x4d	94.670	5.330	98.650	1.350	83.46	224	0.875	bicubic
131	cspdarknet53	94.660	5.340	98.800	1.200	27.64	256	0.887	bilinear
132	ecaresnet50d	94.630	5.370	98.890	1.110	25.58	224	0.875	bicubic
133	efficientnet_b3_pruned	94.630	5.370	98.760	1.240	9.86	300	0.904	bicubic
134	gernet_m	94.620	5.380	98.860	1.140	21.14	224	0.875	bilinear
135	efficientnet_b2	94.610	5.390	98.710	1.290	9.11	288	1.000	bicubic
136	nf_resnet50	94.590	5.410	98.810	1.190	25.56	288	0.940	bicubic
137	pit_s_224	94.590	5.410	98.710	1.290	23.46	224	0.900	bicubic
138	repvgg_b3	94.570	5.430	98.780	1.220	123.09	224	0.875	bilinear
139	seresnet50	94.550	5.450	98.750	1.250	28.09	224	0.875	bicubic
140	regnety_320	94.540	5.460	98.850	1.150	145.05	224	0.875	bicubic
141	inception_resnet_v2	94.540	5.460	98.790	1.210	55.84	299	0.897	bicubic
142	gluon_resnext101_32x4d	94.530	5.470	98.630	1.370	44.18	224	0.875	bicubic
143	repvgg_b3g4	94.520	5.480	98.970	1.030	83.83	224	0.875	bilinear
144	tf_efficientnet_b2_ap	94.490	5.510	98.620	1.380	9.11	260	0.890	bicubic
145	cspresnext50	94.480	5.520	98.680	1.320	20.57	224	0.875	bilinear
146	regnety_120	94.480	5.520	98.810	1.190	51.82	224	0.875	bicubic
147	rexnet_150	94.480	5.520	98.790	1.210	9.73	224	0.875	bicubic
148	regnetx_320	94.460	5.540	98.740	1.260	107.81	224	0.875	bicubic
149	ssl_resnet50	94.450	5.550	98.920	1.080	25.56	224	0.875	bilinear
150	tf_efficientnet_el	94.410	5.590	98.710	1.290	10.59	300	0.904	bicubic
151	vit_deit_small_patch16_224	94.400	5.600	98.690	1.310	22.05	224	0.900	bicubic
152	efficientnet_el_pruned	94.400	5.600	98.740	1.260	10.59	300	0.904	bicubic
153	inception_v4	94.380	5.620	98.580	1.420	42.68	299	0.875	bicubic
154	legacy_seresnext101_32x4d	94.370	5.630	98.650	1.350	48.96	224	0.875	bilinear
155	tf_efficientnet_b2	94.360	5.640	98.610	1.390	9.11	260	0.890	bicubic
156	gluon_seresnext50_32x4d	94.340	5.660	98.610	1.390	27.56	224	0.875	bicubic
157	dpn107	94.310	5.690	98.480	1.520	86.92	224	0.875	bicubic
158	ecaresnet26t	94.310	5.690	98.720	1.280	16.01	320	0.950	bicubic
159	resnetrs50	94.310	5.690	98.640	1.360	35.69	224	0.910	bicubic
160	xception71	94.280	5.720	98.640	1.360	42.34	299	0.903	bicubic
161	resnet50d	94.260	5.740	98.720	1.280	25.58	224	0.875	bicubic
162	skresnext50_32x4d	94.260	5.740	98.460	1.540	27.48	224	0.875	bicubic
163	cait_xxs36_224	94.260	5.740	98.720	1.280	17.30	224	1.000	bicubic
164	gluon_xception65	94.260	5.740	98.570	1.430	39.92	299	0.903	bicubic
165	regnetx_120	94.240	5.760	98.650	1.350	46.11	224	0.875	bicubic
166	dpn92	94.230	5.770	98.730	1.270	37.67	224	0.875	bicubic
167	ecaresnet50d_pruned	94.220	5.780	98.730	1.270	19.94	224	0.875	bicubic
168	gluon_resnet101_v1d	94.220	5.780	98.550	1.450	44.57	224	0.875	bicubic
169	tf_efficientnet_lite3	94.200	5.800	98.640	1.360	8.20	300	0.904	bilinear
170	mixnet_xl	94.190	5.810	98.340	1.660	11.90	224	0.875	bicubic
171	resnext50d_32x4d	94.180	5.820	98.570	1.430	25.05	224	0.875	bicubic
172	regnety_080	94.170	5.830	98.680	1.320	39.18	224	0.875	bicubic
173	gluon_resnet152_v1c	94.160	5.840	98.640	1.360	60.21	224	0.875	bicubic
174	ens_adv_inception_resnet_v2	94.160	5.840	98.600	1.400	55.84	299	0.897	bicubic
175	regnety_064	94.150	5.850	98.730	1.270	30.58	224	0.875	bicubic
176	efficientnet_b2_pruned	94.140	5.860	98.530	1.470	8.31	260	0.890	bicubic
177	dpn98	94.130	5.870	98.570	1.430	61.57	224	0.875	bicubic
178	nf_regnet_b1	94.130	5.870	98.630	1.370	10.22	288	0.900	bicubic
179	regnetx_160	94.120	5.880	98.750	1.250	54.28	224	0.875	bicubic
180	resnext50_32x4d	94.100	5.900	98.350	1.650	25.03	224	0.875	bicubic
181	ese_vovnet39b	94.090	5.910	98.660	1.340	24.57	224	0.875	bicubic
182	gluon_resnet152_v1b	94.080	5.920	98.450	1.550	60.19	224	0.875	bicubic
183	coat_lite_mini	94.060	5.940	98.560	1.440	11.01	224	0.900	bicubic
184	dpn131	94.010	5.990	98.720	1.280	79.25	224	0.875	bicubic
185	hrnet_w64	94.010	5.990	98.610	1.390	128.06	224	0.875	bilinear
186	resnetblur50	93.960	6.040	98.590	1.410	25.56	224	0.875	bicubic
187	dla102x2	93.950	6.050	98.490	1.510	41.28	224	0.875	bilinear
188	hrnet_w48	93.920	6.080	98.610	1.390	77.47	224	0.875	bilinear
189	rexnet_130	93.900	6.100	98.400	1.600	7.56	224	0.875	bicubic
190	tf_efficientnet_cc_b1_8e	93.900	6.100	98.260	1.740	39.72	240	0.882	bicubic
191	regnetx_064	93.890	6.110	98.630	1.370	26.21	224	0.875	bicubic
192	regnetx_080	93.870	6.130	98.520	1.480	39.57	224	0.875	bicubic
193	regnety_040	93.860	6.140	98.650	1.350	20.65	224	0.875	bicubic
194	repvgg_b2g4	93.860	6.140	98.590	1.410	61.76	224	0.875	bilinear
195	efficientnet_em	93.840	6.160	98.810	1.190	6.90	240	0.882	bicubic
196	resnext101_32x8d	93.830	6.170	98.580	1.420	88.79	224	0.875	bilinear
197	resnet50	93.810	6.190	98.390	1.610	25.56	224	0.875	bicubic
198	pit_xs_distilled_224	93.810	6.190	98.670	1.330	11.00	224	0.900	bicubic
199	gluon_resnext50_32x4d	93.810	6.190	98.410	1.590	25.03	224	0.875	bicubic
200	gluon_resnet50_v1d	93.770	6.230	98.390	1.610	25.58	224	0.875	bicubic
201	xception65	93.760	6.240	98.370	1.630	39.92	299	0.903	bicubic
202	gluon_resnet101_v1b	93.750	6.250	98.380	1.620	44.55	224	0.875	bicubic
203	res2net101_26w_4s	93.750	6.250	98.310	1.690	45.21	224	0.875	bilinear
204	cspresnet50	93.740	6.260	98.640	1.360	21.62	256	0.887	bilinear
205	legacy_seresnext50_32x4d	93.730	6.270	98.580	1.420	27.56	224	0.875	bilinear
206	wide_resnet101_2	93.720	6.280	98.540	1.460	126.89	224	0.875	bilinear
207	tf_efficientnet_b1_ap	93.690	6.310	98.360	1.640	7.79	240	0.882	bicubic
208	dpn68b	93.690	6.310	98.510	1.490	12.61	224	0.875	bicubic
209	gluon_resnet101_v1c	93.670	6.330	98.420	1.580	44.57	224	0.875	bicubic
210	tf_efficientnet_b0_ns	93.630	6.370	98.640	1.360	5.29	224	0.875	bicubic
211	gluon_resnet50_v1s	93.620	6.380	98.460	1.540	25.68	224	0.875	bicubic
212	cait_xxs24_224	93.600	6.400	98.440	1.560	11.96	224	1.000	bicubic
213	regnetx_040	93.560	6.440	98.540	1.460	22.12	224	0.875	bicubic
214	hrnet_w44	93.550	6.450	98.700	1.300	67.06	224	0.875	bilinear
215	res2net50_26w_8s	93.540	6.460	98.260	1.740	48.40	224	0.875	bilinear
216	hrnet_w32	93.530	6.470	98.450	1.550	41.23	224	0.875	bilinear
217	dla102x	93.520	6.480	98.510	1.490	26.31	224	0.875	bilinear
218	tf_efficientnet_b1	93.500	6.500	98.360	1.640	7.79	240	0.882	bicubic
219	repvgg_b2	93.500	6.500	98.730	1.270	89.02	224	0.875	bilinear
220	hrnet_w40	93.490	6.510	98.580	1.420	57.56	224	0.875	bilinear
221	gluon_inception_v3	93.460	6.540	98.570	1.430	23.83	299	0.875	bicubic
222	xception	93.460	6.540	98.530	1.470	22.86	299	0.897	bicubic
223	mixnet_l	93.450	6.550	98.220	1.780	7.33	224	0.875	bicubic
224	xception41	93.430	6.570	98.430	1.570	26.97	299	0.903	bicubic
225	res2net50_26w_6s	93.410	6.590	98.280	1.720	37.05	224	0.875	bilinear
226	legacy_seresnet152	93.400	6.600	98.350	1.650	66.82	224	0.875	bilinear
227	dla169	93.340	6.660	98.600	1.400	53.39	224	0.875	bilinear
228	resnest26d	93.330	6.670	98.630	1.370	17.07	224	0.875	bilinear
229	repvgg_b1	93.330	6.670	98.510	1.490	57.42	224	0.875	bilinear
230	tf_inception_v3	93.320	6.680	98.030	1.970	23.83	299	0.875	bicubic
231	tf_mixnet_l	93.310	6.690	98.030	1.970	7.33	224	0.875	bicubic
232	selecsls60b	93.300	6.700	98.280	1.720	32.77	224	0.875	bicubic
233	tv_resnet152	93.300	6.700	98.390	1.610	60.19	224	0.875	bilinear
234	legacy_seresnet101	93.280	6.720	98.510	1.490	49.33	224	0.875	bilinear
235	efficientnet_b1	93.250	6.750	98.290	1.710	7.79	256	1.000	bicubic
236	coat_lite_tiny	93.240	6.760	98.260	1.740	5.72	224	0.900	bicubic
237	hrnet_w30	93.200	6.800	98.410	1.590	37.71	224	0.875	bilinear
238	dla60_res2net	93.180	6.820	98.420	1.580	20.85	224	0.875	bilinear
239	dla60_res2next	93.180	6.820	98.410	1.590	17.03	224	0.875	bilinear
240	efficientnet_es	93.140	6.860	98.420	1.580	5.44	224	0.875	bicubic
241	dla60x	93.120	6.880	98.510	1.490	17.35	224	0.875	bilinear
242	regnetx_032	93.120	6.880	98.390	1.610	15.30	224	0.875	bicubic
243	pit_xs_224	93.110	6.890	98.310	1.690	10.62	224	0.900	bicubic
244	dla102	93.060	6.940	98.540	1.460	33.27	224	0.875	bilinear
245	gluon_resnet50_v1c	93.030	6.970	98.390	1.610	25.58	224	0.875	bicubic
246	regnety_016	93.030	6.970	98.360	1.640	11.20	224	0.875	bicubic
247	rexnet_100	93.030	6.970	98.190	1.810	4.80	224	0.875	bicubic
248	selecsls60	93.030	6.970	98.300	1.700	30.67	224	0.875	bicubic
249	repvgg_b1g4	92.980	7.020	98.430	1.570	39.97	224	0.875	bilinear
250	legacy_seresnet50	92.960	7.040	98.190	1.810	28.09	224	0.875	bilinear
251	hardcorenas_f	92.950	7.050	98.160	1.840	8.20	224	0.875	bilinear
252	tf_efficientnet_em	92.930	7.070	98.190	1.810	6.90	240	0.882	bicubic
253	adv_inception_v3	92.880	7.120	98.140	1.860	23.83	299	0.875	bicubic
254	res2next50	92.840	7.160	98.180	1.820	24.67	224	0.875	bilinear
255	tf_efficientnet_cc_b0_8e	92.830	7.170	98.180	1.820	24.01	224	0.875	bicubic
256	seresnext26t_32x4d	92.820	7.180	98.370	1.630	16.81	224	0.875	bicubic
257	tv_resnet101	92.810	7.190	98.250	1.750	44.55	224	0.875	bilinear
258	efficientnet_b1_pruned	92.770	7.230	98.040	1.960	6.33	240	0.882	bicubic
259	vit_small_patch16_224	92.760	7.240	97.930	2.070	48.75	224	0.900	bicubic
260	densenet201	92.750	7.250	98.230	1.770	20.01	224	0.875	bicubic
261	res2net50_14w_8s	92.740	7.260	98.180	1.820	25.06	224	0.875	bilinear
262	tv_resnext50_32x4d	92.740	7.260	98.270	1.730	25.03	224	0.875	bilinear
263	inception_v3	92.720	7.280	97.970	2.030	23.83	299	0.875	bicubic
264	seresnext26d_32x4d	92.700	7.300	98.150	1.850	16.81	224	0.875	bicubic
265	efficientnet_b0	92.690	7.310	98.070	1.930	5.29	224	0.875	bicubic
266	resnet34d	92.680	7.320	98.310	1.690	21.82	224	0.875	bicubic
267	tf_efficientnet_lite2	92.650	7.350	98.230	1.770	6.09	260	0.890	bicubic
268	legacy_seresnext26_32x4d	92.640	7.360	98.130	1.870	16.79	224	0.875	bicubic
269	tf_efficientnet_lite1	92.620	7.380	98.080	1.920	5.42	240	0.882	bicubic
270	tf_efficientnet_cc_b0_4e	92.590	7.410	98.080	1.920	13.31	224	0.875	bicubic
271	hardcorenas_e	92.570	7.430	98.110	1.890	8.07	224	0.875	bilinear
272	res2net50_48w_2s	92.550	7.450	98.080	1.920	25.29	224	0.875	bilinear
273	gluon_resnet50_v1b	92.540	7.460	98.170	1.830	25.56	224	0.875	bicubic
274	res2net50_26w_4s	92.500	7.500	98.060	1.940	25.70	224	0.875	bilinear
275	densenet161	92.500	7.500	98.290	1.710	28.68	224	0.875	bicubic
276	mixnet_m	92.430	7.570	97.870	2.130	5.01	224	0.875	bicubic
277	hardcorenas_d	92.400	7.600	98.070	1.930	7.50	224	0.875	bilinear
278	mobilenetv2_120d	92.400	7.600	98.050	1.950	5.83	224	0.875	bicubic
279	skresnet34	92.390	7.610	98.150	1.850	22.28	224	0.875	bicubic
280	tf_mixnet_m	92.330	7.670	97.890	2.110	5.01	224	0.875	bicubic
281	hrnet_w18	92.320	7.680	98.240	1.760	21.30	224	0.875	bilinear
282	ese_vovnet19b_dw	92.290	7.710	98.090	1.910	6.54	224	0.875	bicubic
283	selecsls42b	92.280	7.720	98.150	1.850	32.46	224	0.875	bicubic
284	mobilenetv3_large_100_miil	92.260	7.740	97.640	2.360	5.48	224	0.875	bilinear
285	tf_efficientnet_b0	92.250	7.750	98.000	2.000	5.29	224	0.875	bicubic
286	dla60	92.230	7.770	98.110	1.890	22.04	224	0.875	bilinear
287	tf_efficientnet_b0_ap	92.200	7.800	98.020	1.980	5.29	224	0.875	bicubic
288	regnetx_016	92.170	7.830	98.210	1.790	9.19	224	0.875	bicubic
289	gernet_s	92.140	7.860	98.190	1.810	8.17	224	0.875	bilinear
290	resnet26d	92.070	7.930	97.960	2.040	16.01	224	0.875	bicubic
291	hardcorenas_c	92.020	7.980	97.840	2.160	5.52	224	0.875	bilinear
292	dpn68	92.010	7.990	98.050	1.950	12.61	224	0.875	bicubic
293	tf_efficientnet_es	91.980	8.020	97.860	2.140	5.44	224	0.875	bicubic
294	repvgg_a2	91.940	8.060	98.150	1.850	28.21	224	0.875	bilinear
295	densenet169	91.930	8.070	98.100	1.900	14.15	224	0.875	bicubic
296	densenetblur121d	91.910	8.090	98.070	1.930	8.00	224	0.875	bicubic
297	tv_resnet50	91.880	8.120	98.040	1.960	25.56	224	0.875	bilinear
298	mixer_b16_224	91.870	8.130	97.250	2.750	59.88	224	0.875	bicubic
299	mixnet_s	91.830	8.170	97.690	2.310	4.13	224	0.875	bicubic
300	mobilenetv2_140	91.830	8.170	97.860	2.140	6.11	224	0.875	bicubic
301	hardcorenas_b	91.770	8.230	97.780	2.220	5.18	224	0.875	bilinear
302	regnety_008	91.750	8.250	98.180	1.820	6.26	224	0.875	bicubic
303	resnest14d	91.720	8.280	97.870	2.130	10.61	224	0.875	bilinear
304	densenet121	91.570	8.430	98.030	1.970	7.98	224	0.875	bicubic
305	tf_mixnet_s	91.510	8.490	97.620	2.380	4.13	224	0.875	bicubic
306	repvgg_b0	91.430	8.570	97.990	2.010	15.82	224	0.875	bilinear
307	regnety_006	91.370	8.630	97.710	2.290	6.06	224	0.875	bicubic
308	hardcorenas_a	91.350	8.650	97.860	2.140	5.26	224	0.875	bilinear
309	mobilenetv3_large_100	91.320	8.680	97.710	2.290	5.48	224	0.875	bicubic
310	semnasnet_100	91.280	8.720	97.560	2.440	3.89	224	0.875	bicubic
311	tf_mobilenetv3_large_100	91.240	8.760	97.660	2.340	5.48	224	0.875	bilinear
312	mobilenetv3_rw	91.210	8.790	97.660	2.340	5.48	224	0.875	bicubic
313	hrnet_w18_small_v2	91.190	8.810	97.900	2.100	15.60	224	0.875	bilinear
314	efficientnet_es_pruned	91.180	8.820	97.750	2.250	5.44	224	0.875	bicubic
315	efficientnet_lite0	91.140	8.860	97.630	2.370	4.65	224	0.875	bicubic
316	resnet34	91.130	8.870	97.620	2.380	21.80	224	0.875	bilinear
317	resnet26	91.110	8.890	97.740	2.260	16.00	224	0.875	bicubic
318	regnetx_008	91.050	8.950	97.710	2.290	7.26	224	0.875	bicubic
319	tf_efficientnet_lite0	91.040	8.960	97.590	2.410	4.65	224	0.875	bicubic
320	gluon_resnet34_v1b	90.960	9.040	97.630	2.370	21.80	224	0.875	bicubic
321	mobilenetv2_110d	90.950	9.050	97.550	2.450	4.52	224	0.875	bicubic
322	pit_ti_distilled_224	90.900	9.100	97.700	2.300	5.10	224	0.900	bicubic
323	legacy_seresnet34	90.890	9.110	97.580	2.420	21.96	224	0.875	bilinear
324	tv_densenet121	90.890	9.110	97.710	2.290	7.98	224	0.875	bicubic
325	dla34	90.760	9.240	97.660	2.340	15.74	224	0.875	bilinear
326	fbnetc_100	90.700	9.300	97.210	2.790	5.57	224	0.875	bilinear
327	vit_deit_tiny_distilled_patch16_224	90.700	9.300	97.570	2.430	5.91	224	0.900	bicubic
328	swsl_resnet18	90.690	9.310	97.700	2.300	11.69	224	0.875	bilinear
329	mnasnet_100	90.510	9.490	97.470	2.530	4.38	224	0.875	bicubic
330	regnety_004	90.500	9.500	97.540	2.460	4.34	224	0.875	bicubic
331	spnasnet_100	90.350	9.650	97.190	2.810	4.42	224	0.875	bilinear
332	regnetx_006	90.350	9.650	97.430	2.570	6.20	224	0.875	bicubic
333	ssl_resnet18	90.220	9.780	97.550	2.450	11.69	224	0.875	bilinear
334	vgg16_bn	90.090	9.910	97.370	2.630	138.37	224	0.875	bilinear
335	vgg19_bn	90.080	9.920	97.580	2.420	143.68	224	0.875	bilinear
336	ghostnet_100	90.020	9.980	97.370	2.630	5.18	224	0.875	bilinear
337	pit_ti_224	89.940	10.060	97.450	2.550	4.85	224	0.900	bicubic
338	tv_resnet34	89.940	10.060	97.340	2.660	21.80	224	0.875	bilinear
339	tf_mobilenetv3_large_075	89.680	10.320	97.210	2.790	3.99	224	0.875	bilinear
340	vit_deit_tiny_patch16_224	89.670	10.330	97.450	2.550	5.72	224	0.900	bicubic
341	skresnet18	89.660	10.340	97.230	2.770	11.96	224	0.875	bicubic
342	mobilenetv2_100	89.600	10.400	97.140	2.860	3.50	224	0.875	bicubic
343	resnet18d	89.280	10.720	97.150	2.850	11.71	224	0.875	bicubic
344	hrnet_w18_small	89.050	10.950	97.110	2.890	13.19	224	0.875	bilinear
345	vgg19	89.040	10.960	96.870	3.130	143.67	224	0.875	bilinear
346	tf_mobilenetv3_large_minimal_100	88.970	11.030	96.860	3.140	3.92	224	0.875	bilinear
347	regnetx_004	88.900	11.100	97.120	2.880	5.16	224	0.875	bicubic
348	legacy_seresnet18	88.880	11.120	96.980	3.020	11.78	224	0.875	bicubic
349	vgg13_bn	88.760	11.240	96.970	3.030	133.05	224	0.875	bilinear
350	vgg16	88.550	11.450	96.790	3.210	138.36	224	0.875	bilinear
351	gluon_resnet18_v1b	88.400	11.600	96.680	3.320	11.69	224	0.875	bicubic
352	vgg11_bn	87.500	12.500	96.820	3.180	132.87	224	0.875	bilinear
353	resnet18	87.390	12.610	96.290	3.710	11.69	224	0.875	bilinear
354	regnety_002	87.380	12.620	96.590	3.410	3.16	224	0.875	bicubic
355	mixer_l16_224	87.150	12.850	93.520	6.480	208.20	224	0.875	bicubic
356	vgg13	87.050	12.950	96.320	3.680	133.05	224	0.875	bilinear
357	vgg11	86.550	13.450	96.280	3.720	132.86	224	0.875	bilinear
358	dla60x_c	86.290	13.710	96.160	3.840	1.32	224	0.875	bilinear
359	regnetx_002	86.190	13.810	95.980	4.020	2.68	224	0.875	bicubic
360	tf_mobilenetv3_small_100	85.190	14.810	95.770	4.230	2.54	224	0.875	bilinear
361	dla46x_c	84.250	15.750	95.270	4.730	1.07	224	0.875	bilinear
362	dla46_c	83.650	16.350	94.920	5.080	1.30	224	0.875	bilinear
363	tf_mobilenetv3_small_075	83.520	16.480	94.790	5.210	2.04	224	0.875	bilinear
364	tf_mobilenetv3_small_minimal_100	81.380	18.620	93.670	6.330	2.04	224	0.875	bilinear