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

1	model	top1	top1_err	top5	top5_err	param_count	img_size	cropt_pct	interpolation
2	tf_efficientnet_l2_ns	97.780	2.220	99.890	0.110	480.31	800	0.960	bicubic
3	tf_efficientnet_l2_ns_475	97.750	2.250	99.820	0.180	480.31	475	0.936	bicubic
4	tf_efficientnet_b7_ns	97.200	2.800	99.700	0.300	66.35	600	0.949	bicubic
5	swin_large_patch4_window12_384	97.170	2.830	99.680	0.320	196.74	384	1.000	bicubic
6	swin_base_patch4_window12_384	97.120	2.880	99.780	0.220	87.90	384	1.000	bicubic
7	tf_efficientnet_b6_ns	97.020	2.980	99.710	0.290	43.04	528	0.942	bicubic
8	dm_nfnet_f6	96.990	3.010	99.740	0.260	438.36	576	0.956	bicubic
9	ig_resnext101_32x48d	96.970	3.030	99.670	0.330	828.41	224	0.875	bilinear
10	swin_large_patch4_window7_224	96.950	3.050	99.660	0.340	196.53	224	0.900	bicubic
11	cait_m48_448	96.880	3.120	99.620	0.380	356.46	448	1.000	bicubic
12	resnetv2_152x4_bitm	96.880	3.120	99.660	0.340	936.53	480	1.000	bilinear
13	tf_efficientnet_b5_ns	96.870	3.130	99.640	0.360	30.39	456	0.934	bicubic
14	cait_m36_384	96.830	3.170	99.660	0.340	271.22	384	1.000	bicubic
15	dm_nfnet_f4	96.820	3.180	99.600	0.400	316.07	512	0.951	bicubic
16	ig_resnext101_32x32d	96.780	3.220	99.530	0.470	468.53	224	0.875	bilinear
17	dm_nfnet_f5	96.710	3.290	99.680	0.320	377.21	544	0.954	bicubic
18	tf_efficientnet_b4_ns	96.710	3.290	99.640	0.360	19.34	380	0.922	bicubic
19	tf_efficientnet_b8	96.700	3.300	99.530	0.470	87.41	672	0.954	bicubic
20	swin_base_patch4_window7_224	96.680	3.320	99.660	0.340	87.77	224	0.900	bicubic
21	cait_s36_384	96.630	3.370	99.600	0.400	68.37	384	1.000	bicubic
22	dm_nfnet_f3	96.630	3.370	99.640	0.360	254.92	416	0.940	bicubic
23	tf_efficientnet_b7	96.580	3.420	99.510	0.490	66.35	600	0.949	bicubic
24	cait_s24_384	96.570	3.430	99.550	0.450	47.06	384	1.000	bicubic
25	tf_efficientnet_b8_ap	96.550	3.450	99.540	0.460	87.41	672	0.954	bicubic
26	vit_deit_base_distilled_patch16_384	96.510	3.490	99.590	0.410	87.63	384	1.000	bicubic
27	dm_nfnet_f2	96.500	3.500	99.570	0.430	193.78	352	0.920	bicubic
28	resnetv2_152x2_bitm	96.500	3.500	99.620	0.380	236.34	480	1.000	bilinear
29	ecaresnet269d	96.460	3.540	99.610	0.390	102.09	352	1.000	bicubic
30	vit_base_r50_s16_384	96.450	3.550	99.660	0.340	98.95	384	1.000	bicubic
31	ig_resnext101_32x16d	96.440	3.560	99.540	0.460	194.03	224	0.875	bilinear
32	resnetrs420	96.400	3.600	99.540	0.460	191.89	416	1.000	bicubic
33	dm_nfnet_f1	96.370	3.630	99.470	0.530	132.63	320	0.910	bicubic
34	tf_efficientnet_b6_ap	96.370	3.630	99.550	0.450	43.04	528	0.942	bicubic
35	resnetv2_101x3_bitm	96.360	3.640	99.600	0.400	387.93	480	1.000	bilinear
36	vit_large_patch16_384	96.360	3.640	99.630	0.370	304.72	384	1.000	bicubic
37	tf_efficientnet_b7_ap	96.350	3.650	99.590	0.410	66.35	600	0.949	bicubic
38	seresnet152d	96.310	3.690	99.510	0.490	66.84	320	1.000	bicubic
39	tf_efficientnet_b6	96.290	3.710	99.520	0.480	43.04	528	0.942	bicubic
40	swsl_resnext101_32x16d	96.270	3.730	99.500	0.500	194.03	224	0.875	bilinear
41	resnetrs350	96.240	3.760	99.470	0.530	163.96	384	1.000	bicubic
42	swsl_resnext101_32x8d	96.240	3.760	99.590	0.410	88.79	224	0.875	bilinear
43	vit_base_patch16_384	96.190	3.810	99.530	0.470	86.86	384	1.000	bicubic
44	resnetv2_50x3_bitm	96.140	3.860	99.620	0.380	217.32	480	1.000	bilinear
45	resnest269e	96.120	3.880	99.520	0.480	110.93	416	0.928	bicubic
46	resnet200d	96.110	3.890	99.460	0.540	64.69	320	1.000	bicubic
47	tf_efficientnet_b3_ns	96.100	3.900	99.480	0.520	12.23	300	0.904	bicubic
48	tf_efficientnet_b5_ap	96.080	3.920	99.540	0.460	30.39	456	0.934	bicubic
49	pit_b_distilled_224	96.070	3.930	99.380	0.620	74.79	224	0.900	bicubic
50	resnest200e	96.070	3.930	99.480	0.520	70.20	320	0.909	bicubic
51	resnetrs270	96.060	3.940	99.490	0.510	129.86	352	1.000	bicubic
52	swsl_resnext101_32x4d	96.050	3.950	99.530	0.470	44.18	224	0.875	bilinear
53	vit_base_patch16_224_miil	96.030	3.970	99.350	0.650	86.54	224	0.875	bilinear
54	cait_xs24_384	96.010	3.990	99.430	0.570	26.67	384	1.000	bicubic
55	resnetrs200	95.990	4.010	99.440	0.560	93.21	320	1.000	bicubic
56	tf_efficientnet_b5	95.980	4.020	99.450	0.550	30.39	456	0.934	bicubic
57	resnetrs152	95.960	4.040	99.380	0.620	86.62	320	1.000	bicubic
58	ig_resnext101_32x8d	95.930	4.070	99.380	0.620	88.79	224	0.875	bilinear
59	eca_nfnet_l1	95.930	4.070	99.500	0.500	41.41	320	1.000	bicubic
60	regnety_160	95.880	4.120	99.560	0.440	83.59	288	1.000	bicubic
61	resnet152d	95.870	4.130	99.430	0.570	60.21	320	1.000	bicubic
62	resnet101d	95.750	4.250	99.440	0.560	44.57	320	1.000	bicubic
63	vit_deit_base_distilled_patch16_224	95.750	4.250	99.280	0.720	87.34	224	0.900	bicubic
64	swin_small_patch4_window7_224	95.720	4.280	99.290	0.710	49.61	224	0.900	bicubic
65	efficientnet_v2s	95.710	4.290	99.380	0.620	23.94	384	1.000	bicubic
66	cait_s24_224	95.650	4.350	99.390	0.610	46.92	224	1.000	bicubic
67	vit_deit_base_patch16_384	95.650	4.350	99.240	0.760	86.86	384	1.000	bicubic
68	dm_nfnet_f0	95.630	4.370	99.300	0.700	71.49	256	0.900	bicubic
69	swsl_resnext50_32x4d	95.620	4.380	99.440	0.560	25.03	224	0.875	bilinear
70	tf_efficientnet_b4	95.590	4.410	99.330	0.670	19.34	380	0.922	bicubic
71	resnest101e	95.570	4.430	99.270	0.730	48.28	256	0.875	bilinear
72	efficientnet_b4	95.520	4.480	99.390	0.610	19.34	384	1.000	bicubic
73	tf_efficientnet_b2_ns	95.520	4.480	99.340	0.660	9.11	260	0.890	bicubic
74	resnetv2_101x1_bitm	95.510	4.490	99.510	0.490	44.54	480	1.000	bilinear
75	tresnet_xl_448	95.510	4.490	99.340	0.660	78.44	448	0.875	bilinear
76	tf_efficientnet_b4_ap	95.490	4.510	99.390	0.610	19.34	380	0.922	bicubic
77	eca_nfnet_l0	95.470	4.530	99.380	0.620	24.14	288	1.000	bicubic
78	regnety_032	95.470	4.530	99.320	0.680	19.44	288	1.000	bicubic
79	ssl_resnext101_32x16d	95.410	4.590	99.410	0.590	194.03	224	0.875	bilinear
80	tresnet_l_448	95.410	4.590	99.300	0.700	55.99	448	0.875	bilinear
81	nfnet_l0	95.390	4.610	99.420	0.580	35.07	288	1.000	bicubic
82	tresnet_m	95.380	4.620	99.150	0.850	31.39	224	0.875	bilinear
83	pnasnet5large	95.360	4.640	99.130	0.870	86.06	331	0.911	bicubic
84	ssl_resnext101_32x8d	95.340	4.660	99.320	0.680	88.79	224	0.875	bilinear
85	vit_large_patch16_224	95.290	4.710	99.310	0.690	304.33	224	0.900	bicubic
86	vit_base_patch32_384	95.260	4.740	99.180	0.820	88.30	384	1.000	bicubic
87	resnetrs101	95.250	4.750	99.210	0.790	63.62	288	0.940	bicubic
88	vit_large_patch32_384	95.240	4.760	99.320	0.680	306.63	384	1.000	bicubic
89	cait_xxs36_384	95.220	4.780	99.320	0.680	17.37	384	1.000	bicubic
90	vit_base_patch16_224	95.210	4.790	99.230	0.770	86.57	224	0.900	bicubic
91	swsl_resnet50	95.200	4.800	99.390	0.610	25.56	224	0.875	bilinear
92	ssl_resnext101_32x4d	95.160	4.840	99.300	0.700	44.18	224	0.875	bilinear
93	ecaresnet101d	95.160	4.840	99.230	0.770	44.57	224	0.875	bicubic
94	nasnetalarge	95.150	4.850	99.130	0.870	88.75	331	0.911	bicubic
95	efficientnet_b3	95.140	4.860	99.210	0.790	12.23	320	1.000	bicubic
96	ecaresnet50t	95.070	4.930	99.290	0.710	25.57	320	0.950	bicubic
97	tresnet_xl	95.060	4.940	99.260	0.740	78.44	224	0.875	bilinear
98	vit_deit_base_patch16_224	95.010	4.990	98.980	1.020	86.57	224	0.900	bicubic
99	tf_efficientnet_b3_ap	94.970	5.030	99.110	0.890	12.23	300	0.904	bicubic
100	gernet_l	94.930	5.070	99.200	0.800	31.08	256	0.875	bilinear
101	cait_xxs24_384	94.920	5.080	99.140	0.860	12.03	384	1.000	bicubic
102	tf_efficientnet_b3	94.910	5.090	99.110	0.890	12.23	300	0.904	bicubic
103	tresnet_l	94.900	5.100	99.030	0.970	55.99	224	0.875	bilinear
104	tf_efficientnet_lite4	94.870	5.130	99.090	0.910	13.01	380	0.920	bilinear
105	tf_efficientnet_b1_ns	94.860	5.140	99.250	0.750	7.79	240	0.882	bicubic
106	seresnext50_32x4d	94.820	5.180	99.130	0.870	27.56	224	0.875	bicubic
107	pit_b_224	94.790	5.210	98.820	1.180	73.76	224	0.900	bicubic
108	legacy_senet154	94.730	5.270	99.100	0.900	115.09	224	0.875	bilinear
109	pit_s_distilled_224	94.730	5.270	99.190	0.810	24.04	224	0.900	bicubic
110	gluon_resnet152_v1s	94.720	5.280	99.060	0.940	60.32	224	0.875	bicubic
111	gluon_senet154	94.710	5.290	98.970	1.030	115.09	224	0.875	bicubic
112	resnest50d_4s2x40d	94.710	5.290	99.130	0.870	30.42	224	0.875	bicubic
113	ssl_resnext50_32x4d	94.700	5.300	99.240	0.760	25.03	224	0.875	bilinear
114	wide_resnet50_2	94.670	5.330	99.050	0.950	68.88	224	0.875	bicubic
115	efficientnet_el	94.670	5.330	99.130	0.870	10.59	300	0.904	bicubic
116	rexnet_200	94.660	5.340	99.090	0.910	16.37	224	0.875	bicubic
117	tresnet_m_448	94.660	5.340	99.150	0.850	31.39	448	0.875	bilinear
118	gluon_seresnext101_64x4d	94.650	5.350	98.980	1.020	88.23	224	0.875	bicubic
119	resnest50d	94.620	5.380	99.030	0.970	27.48	224	0.875	bilinear
120	swin_tiny_patch4_window7_224	94.620	5.380	99.120	0.880	28.29	224	0.900	bicubic
121	pit_s_224	94.590	5.410	98.930	1.070	23.46	224	0.900	bicubic
122	vit_deit_small_distilled_patch16_224	94.590	5.410	99.100	0.900	22.44	224	0.900	bicubic
123	efficientnet_b3_pruned	94.580	5.420	99.070	0.930	9.86	300	0.904	bicubic
124	tnt_s_patch16_224	94.580	5.420	99.180	0.820	23.76	224	0.900	bicubic
125	resnetv2_50x1_bitm	94.550	5.450	99.250	0.750	25.55	480	1.000	bilinear
126	repvgg_b3	94.550	5.450	98.910	1.090	123.09	224	0.875	bilinear
127	gernet_m	94.550	5.450	98.930	1.070	21.14	224	0.875	bilinear
128	regnety_320	94.520	5.480	99.170	0.830	145.05	224	0.875	bicubic
129	repvgg_b3g4	94.490	5.510	99.020	0.980	83.83	224	0.875	bilinear
130	ecaresnet101d_pruned	94.450	5.550	99.100	0.900	24.88	224	0.875	bicubic
131	gluon_seresnext101_32x4d	94.450	5.550	99.090	0.910	48.96	224	0.875	bicubic
132	gluon_resnet152_v1d	94.440	5.560	99.010	0.990	60.21	224	0.875	bicubic
133	nf_resnet50	94.410	5.590	99.100	0.900	25.56	288	0.940	bicubic
134	resnest50d_1s4x24d	94.390	5.610	99.070	0.930	25.68	224	0.875	bicubic
135	inception_v4	94.380	5.620	98.820	1.180	42.68	299	0.875	bicubic
136	efficientnet_b2	94.370	5.630	99.050	0.950	9.11	288	1.000	bicubic
137	tf_efficientnet_el	94.360	5.640	99.100	0.900	10.59	300	0.904	bicubic
138	gluon_resnext101_64x4d	94.350	5.650	98.880	1.120	83.46	224	0.875	bicubic
139	inception_resnet_v2	94.340	5.660	98.800	1.200	55.84	299	0.897	bicubic
140	ssl_resnet50	94.310	5.690	99.150	0.850	25.56	224	0.875	bilinear
141	regnetx_120	94.270	5.730	99.190	0.810	46.11	224	0.875	bicubic
142	rexnet_150	94.270	5.730	99.080	0.920	9.73	224	0.875	bicubic
143	tf_efficientnet_b2_ap	94.270	5.730	98.950	1.050	9.11	260	0.890	bicubic
144	mixnet_xl	94.230	5.770	98.820	1.180	11.90	224	0.875	bicubic
145	regnetx_320	94.210	5.790	99.050	0.950	107.81	224	0.875	bicubic
146	tf_efficientnet_b2	94.210	5.790	99.030	0.970	9.11	260	0.890	bicubic
147	dpn92	94.190	5.810	98.930	1.070	37.67	224	0.875	bicubic
148	ecaresnet50d	94.190	5.810	99.020	0.980	25.58	224	0.875	bicubic
149	gluon_seresnext50_32x4d	94.170	5.830	98.910	1.090	27.56	224	0.875	bicubic
150	gluon_resnet101_v1s	94.170	5.830	99.010	0.990	44.67	224	0.875	bicubic
151	gluon_resnet101_v1d	94.170	5.830	98.940	1.060	44.57	224	0.875	bicubic
152	ecaresnetlight	94.140	5.860	98.950	1.050	30.16	224	0.875	bicubic
153	regnety_064	94.140	5.860	99.030	0.970	30.58	224	0.875	bicubic
154	ens_adv_inception_resnet_v2	94.130	5.870	98.790	1.210	55.84	299	0.897	bicubic
155	legacy_seresnext101_32x4d	94.130	5.870	98.970	1.030	48.96	224	0.875	bilinear
156	tf_efficientnet_lite3	94.130	5.870	98.960	1.040	8.20	300	0.904	bilinear
157	gluon_resnext101_32x4d	94.120	5.880	98.930	1.070	44.18	224	0.875	bicubic
158	cspdarknet53	94.090	5.910	98.980	1.020	27.64	256	0.887	bilinear
159	efficientnet_el_pruned	94.090	5.910	99.010	0.990	10.59	300	0.904	bicubic
160	seresnet50	94.080	5.920	98.970	1.030	28.09	224	0.875	bicubic
161	resnet50d	94.070	5.930	98.920	1.080	25.58	224	0.875	bicubic
162	gluon_resnet152_v1b	94.030	5.970	98.740	1.260	60.19	224	0.875	bicubic
163	hrnet_w48	94.030	5.970	99.040	0.960	77.47	224	0.875	bilinear
164	resnetrs50	94.020	5.980	98.850	1.150	35.69	224	0.910	bicubic
165	gluon_xception65	94.010	5.990	99.020	0.980	39.92	299	0.903	bicubic
166	regnety_120	94.010	5.990	99.030	0.970	51.82	224	0.875	bicubic
167	dla102x2	94.000	6.000	99.030	0.970	41.28	224	0.875	bilinear
168	vit_deit_small_patch16_224	94.000	6.000	98.960	1.040	22.05	224	0.900	bicubic
169	dpn107	93.960	6.040	98.840	1.160	86.92	224	0.875	bicubic
170	skresnext50_32x4d	93.950	6.050	98.820	1.180	27.48	224	0.875	bicubic
171	dpn98	93.940	6.060	98.920	1.080	61.57	224	0.875	bicubic
172	ecaresnet26t	93.940	6.060	98.920	1.080	16.01	320	0.950	bicubic
173	cait_xxs36_224	93.940	6.060	98.890	1.110	17.30	224	1.000	bicubic
174	nf_regnet_b1	93.890	6.110	98.750	1.250	10.22	288	0.900	bicubic
175	regnety_080	93.890	6.110	99.000	1.000	39.18	224	0.875	bicubic
176	xception71	93.890	6.110	98.950	1.050	42.34	299	0.903	bicubic
177	gluon_resnet152_v1c	93.880	6.120	98.800	1.200	60.21	224	0.875	bicubic
178	regnetx_160	93.880	6.120	99.090	0.910	54.28	224	0.875	bicubic
179	cspresnet50	93.860	6.140	98.870	1.130	21.62	256	0.887	bilinear
180	ese_vovnet39b	93.850	6.150	98.900	1.100	24.57	224	0.875	bicubic
181	resnext50_32x4d	93.840	6.160	98.830	1.170	25.03	224	0.875	bicubic
182	hrnet_w64	93.830	6.170	98.930	1.070	128.06	224	0.875	bilinear
183	repvgg_b2g4	93.820	6.180	98.930	1.070	61.76	224	0.875	bilinear
184	ecaresnet50d_pruned	93.820	6.180	99.000	1.000	19.94	224	0.875	bicubic
185	resnext50d_32x4d	93.810	6.190	98.740	1.260	25.05	224	0.875	bicubic
186	efficientnet_b2_pruned	93.800	6.200	98.910	1.090	8.31	260	0.890	bicubic
187	dla169	93.800	6.200	98.840	1.160	53.39	224	0.875	bilinear
188	regnetx_080	93.790	6.210	98.910	1.090	39.57	224	0.875	bicubic
189	resnext101_32x8d	93.770	6.230	98.950	1.050	88.79	224	0.875	bilinear
190	cspresnext50	93.760	6.240	98.840	1.160	20.57	224	0.875	bilinear
191	dpn131	93.760	6.240	98.800	1.200	79.25	224	0.875	bicubic
192	gluon_resnet101_v1b	93.760	6.240	98.700	1.300	44.55	224	0.875	bicubic
193	xception65	93.760	6.240	98.860	1.140	39.92	299	0.903	bicubic
194	efficientnet_em	93.740	6.260	98.930	1.070	6.90	240	0.882	bicubic
195	tf_efficientnet_b0_ns	93.740	6.260	98.980	1.020	5.29	224	0.875	bicubic
196	wide_resnet101_2	93.730	6.270	98.810	1.190	126.89	224	0.875	bilinear
197	hrnet_w40	93.710	6.290	98.800	1.200	57.56	224	0.875	bilinear
198	tf_efficientnet_b1	93.710	6.290	98.800	1.200	7.79	240	0.882	bicubic
199	resnetblur50	93.710	6.290	98.810	1.190	25.56	224	0.875	bicubic
200	gluon_resnet101_v1c	93.690	6.310	98.760	1.240	44.57	224	0.875	bicubic
201	regnetx_040	93.680	6.320	98.940	1.060	22.12	224	0.875	bicubic
202	rexnet_130	93.670	6.330	98.710	1.290	7.56	224	0.875	bicubic
203	gluon_resnext50_32x4d	93.650	6.350	98.690	1.310	25.03	224	0.875	bicubic
204	xception	93.640	6.360	98.770	1.230	22.86	299	0.897	bicubic
205	regnetx_064	93.630	6.370	99.050	0.950	26.21	224	0.875	bicubic
206	tf_efficientnet_b1_ap	93.630	6.370	98.800	1.200	7.79	240	0.882	bicubic
207	regnety_040	93.620	6.380	98.950	1.050	20.65	224	0.875	bicubic
208	dpn68b	93.620	6.380	98.700	1.300	12.61	224	0.875	bicubic
209	hrnet_w44	93.620	6.380	98.960	1.040	67.06	224	0.875	bilinear
210	gluon_resnet50_v1s	93.590	6.410	98.840	1.160	25.68	224	0.875	bicubic
211	repvgg_b2	93.590	6.410	99.070	0.930	89.02	224	0.875	bilinear
212	res2net50_26w_6s	93.590	6.410	98.750	1.250	37.05	224	0.875	bilinear
213	dla60_res2next	93.570	6.430	98.800	1.200	17.03	224	0.875	bilinear
214	tf_efficientnet_cc_b1_8e	93.570	6.430	98.690	1.310	39.72	240	0.882	bicubic
215	gluon_inception_v3	93.540	6.460	98.830	1.170	23.83	299	0.875	bicubic
216	dla102x	93.530	6.470	98.850	1.150	26.31	224	0.875	bilinear
217	gluon_resnet50_v1d	93.530	6.470	98.710	1.290	25.58	224	0.875	bicubic
218	res2net101_26w_4s	93.520	6.480	98.600	1.400	45.21	224	0.875	bilinear
219	selecsls60b	93.500	6.500	98.840	1.160	32.77	224	0.875	bicubic
220	cait_xxs24_224	93.490	6.510	98.770	1.230	11.96	224	1.000	bicubic
221	xception41	93.480	6.520	98.750	1.250	26.97	299	0.903	bicubic
222	resnet50	93.460	6.540	98.600	1.400	25.56	224	0.875	bicubic
223	coat_lite_mini	93.450	6.550	98.780	1.220	11.01	224	0.900	bicubic
224	res2net50_26w_8s	93.450	6.550	98.700	1.300	48.40	224	0.875	bilinear
225	legacy_seresnet152	93.440	6.560	98.850	1.150	66.82	224	0.875	bilinear
226	legacy_seresnext50_32x4d	93.430	6.570	98.800	1.200	27.56	224	0.875	bilinear
227	repvgg_b1	93.410	6.590	98.790	1.210	57.42	224	0.875	bilinear
228	dla60_res2net	93.380	6.620	98.860	1.140	20.85	224	0.875	bilinear
229	hrnet_w30	93.370	6.630	98.830	1.170	37.71	224	0.875	bilinear
230	dla102	93.260	6.740	98.780	1.220	33.27	224	0.875	bilinear
231	legacy_seresnet101	93.260	6.740	98.740	1.260	49.33	224	0.875	bilinear
232	mixnet_l	93.260	6.740	98.700	1.300	7.33	224	0.875	bicubic
233	regnetx_032	93.250	6.750	98.730	1.270	15.30	224	0.875	bicubic
234	pit_xs_distilled_224	93.240	6.760	98.820	1.180	11.00	224	0.900	bicubic
235	resnest26d	93.240	6.760	98.850	1.150	17.07	224	0.875	bilinear
236	tv_resnet152	93.240	6.760	98.750	1.250	60.19	224	0.875	bilinear
237	tf_inception_v3	93.200	6.800	98.480	1.520	23.83	299	0.875	bicubic
238	dla60x	93.190	6.810	98.710	1.290	17.35	224	0.875	bilinear
239	res2net50_26w_4s	93.180	6.820	98.670	1.330	25.70	224	0.875	bilinear
240	tf_efficientnet_em	93.170	6.830	98.670	1.330	6.90	240	0.882	bicubic
241	res2next50	93.150	6.850	98.660	1.340	24.67	224	0.875	bilinear
242	tf_mixnet_l	93.040	6.960	98.540	1.460	7.33	224	0.875	bicubic
243	efficientnet_b1	93.030	6.970	98.710	1.290	7.79	256	1.000	bicubic
244	repvgg_b1g4	93.030	6.970	98.820	1.180	39.97	224	0.875	bilinear
245	res2net50_14w_8s	93.030	6.970	98.700	1.300	25.06	224	0.875	bilinear
246	adv_inception_v3	93.010	6.990	98.490	1.510	23.83	299	0.875	bicubic
247	selecsls60	93.010	6.990	98.830	1.170	30.67	224	0.875	bicubic
248	regnety_016	93.000	7.000	98.680	1.320	11.20	224	0.875	bicubic
249	efficientnet_b1_pruned	92.980	7.020	98.530	1.470	6.33	240	0.882	bicubic
250	hardcorenas_f	92.980	7.020	98.620	1.380	8.20	224	0.875	bilinear
251	hrnet_w32	92.950	7.050	98.840	1.160	41.23	224	0.875	bilinear
252	hardcorenas_e	92.950	7.050	98.570	1.430	8.07	224	0.875	bilinear
253	efficientnet_es	92.910	7.090	98.690	1.310	5.44	224	0.875	bicubic
254	gluon_resnet50_v1c	92.910	7.090	98.710	1.290	25.58	224	0.875	bicubic
255	pit_xs_224	92.910	7.090	98.780	1.220	10.62	224	0.900	bicubic
256	densenet161	92.900	7.100	98.810	1.190	28.68	224	0.875	bicubic
257	inception_v3	92.900	7.100	98.330	1.670	23.83	299	0.875	bicubic
258	tv_resnext50_32x4d	92.900	7.100	98.720	1.280	25.03	224	0.875	bilinear
259	tv_resnet101	92.880	7.120	98.660	1.340	44.55	224	0.875	bilinear
260	tf_efficientnet_cc_b0_8e	92.870	7.130	98.460	1.540	24.01	224	0.875	bicubic
261	coat_lite_tiny	92.850	7.150	98.640	1.360	5.72	224	0.900	bicubic
262	rexnet_100	92.850	7.150	98.620	1.380	4.80	224	0.875	bicubic
263	tf_efficientnet_cc_b0_4e	92.840	7.160	98.440	1.560	13.31	224	0.875	bicubic
264	seresnext26t_32x4d	92.820	7.180	98.560	1.440	16.81	224	0.875	bicubic
265	res2net50_48w_2s	92.790	7.210	98.470	1.530	25.29	224	0.875	bilinear
266	hrnet_w18	92.760	7.240	98.660	1.340	21.30	224	0.875	bilinear
267	densenet201	92.690	7.310	98.650	1.350	20.01	224	0.875	bicubic
268	repvgg_a2	92.680	7.320	98.520	1.480	28.21	224	0.875	bilinear
269	dla60	92.670	7.330	98.630	1.370	22.04	224	0.875	bilinear
270	legacy_seresnet50	92.670	7.330	98.650	1.350	28.09	224	0.875	bilinear
271	resnet34d	92.640	7.360	98.420	1.580	21.82	224	0.875	bicubic
272	mobilenetv2_120d	92.610	7.390	98.510	1.490	5.83	224	0.875	bicubic
273	tf_efficientnet_b0_ap	92.610	7.390	98.370	1.630	5.29	224	0.875	bicubic
274	vit_small_patch16_224	92.600	7.400	98.390	1.610	48.75	224	0.900	bicubic
275	hardcorenas_d	92.600	7.400	98.430	1.570	7.50	224	0.875	bilinear
276	tf_efficientnet_lite2	92.590	7.410	98.550	1.450	6.09	260	0.890	bicubic
277	legacy_seresnext26_32x4d	92.570	7.430	98.420	1.580	16.79	224	0.875	bicubic
278	skresnet34	92.570	7.430	98.520	1.480	22.28	224	0.875	bicubic
279	gluon_resnet50_v1b	92.560	7.440	98.550	1.450	25.56	224	0.875	bicubic
280	regnetx_016	92.540	7.460	98.550	1.450	9.19	224	0.875	bicubic
281	efficientnet_b0	92.480	7.520	98.680	1.320	5.29	224	0.875	bicubic
282	selecsls42b	92.480	7.520	98.440	1.560	32.46	224	0.875	bicubic
283	gernet_s	92.440	7.560	98.500	1.500	8.17	224	0.875	bilinear
284	seresnext26d_32x4d	92.440	7.560	98.540	1.460	16.81	224	0.875	bicubic
285	densenetblur121d	92.400	7.600	98.410	1.590	8.00	224	0.875	bicubic
286	tf_efficientnet_b0	92.400	7.600	98.470	1.530	5.29	224	0.875	bicubic
287	hardcorenas_c	92.330	7.670	98.340	1.660	5.52	224	0.875	bilinear
288	tf_efficientnet_lite1	92.310	7.690	98.490	1.510	5.42	240	0.882	bicubic
289	densenet169	92.300	7.700	98.590	1.410	14.15	224	0.875	bicubic
290	mixnet_m	92.270	7.730	98.350	1.650	5.01	224	0.875	bicubic
291	mobilenetv3_large_100_miil	92.250	7.750	98.250	1.750	5.48	224	0.875	bilinear
292	dpn68	92.240	7.760	98.610	1.390	12.61	224	0.875	bicubic
293	resnet26d	92.230	7.770	98.450	1.550	16.01	224	0.875	bicubic
294	tf_mixnet_m	92.200	7.800	98.420	1.580	5.01	224	0.875	bicubic
295	tv_resnet50	92.140	7.860	98.420	1.580	25.56	224	0.875	bilinear
296	tf_efficientnet_es	92.100	7.900	98.440	1.560	5.44	224	0.875	bicubic
297	mobilenetv2_140	92.030	7.970	98.250	1.750	6.11	224	0.875	bicubic
298	ese_vovnet19b_dw	92.010	7.990	98.510	1.490	6.54	224	0.875	bicubic
299	densenet121	91.940	8.060	98.280	1.720	7.98	224	0.875	bicubic
300	hardcorenas_b	91.940	8.060	98.400	1.600	5.18	224	0.875	bilinear
301	regnety_008	91.900	8.100	98.420	1.580	6.26	224	0.875	bicubic
302	mixnet_s	91.780	8.220	98.300	1.700	4.13	224	0.875	bicubic
303	efficientnet_es_pruned	91.700	8.300	98.420	1.580	5.44	224	0.875	bicubic
304	repvgg_b0	91.680	8.320	98.450	1.550	15.82	224	0.875	bilinear
305	tf_mixnet_s	91.680	8.320	98.240	1.760	4.13	224	0.875	bicubic
306	semnasnet_100	91.660	8.340	98.270	1.730	3.89	224	0.875	bicubic
307	hardcorenas_a	91.620	8.380	98.170	1.830	5.26	224	0.875	bilinear
308	regnety_006	91.570	8.430	98.430	1.570	6.06	224	0.875	bicubic
309	mobilenetv3_rw	91.550	8.450	98.270	1.730	5.48	224	0.875	bicubic
310	mobilenetv3_large_100	91.480	8.520	98.320	1.680	5.48	224	0.875	bicubic
311	legacy_seresnet34	91.480	8.520	98.200	1.800	21.96	224	0.875	bilinear
312	resnet26	91.440	8.560	98.280	1.720	16.00	224	0.875	bicubic
313	tf_mobilenetv3_large_100	91.420	8.580	98.260	1.740	5.48	224	0.875	bilinear
314	tv_densenet121	91.400	8.600	98.250	1.750	7.98	224	0.875	bicubic
315	mobilenetv2_110d	91.350	8.650	98.190	1.810	4.52	224	0.875	bicubic
316	tf_efficientnet_lite0	91.300	8.700	98.090	1.910	4.65	224	0.875	bicubic
317	fbnetc_100	91.270	8.730	97.830	2.170	5.57	224	0.875	bilinear
318	efficientnet_lite0	91.260	8.740	98.250	1.750	4.65	224	0.875	bicubic
319	dla34	91.240	8.760	98.180	1.820	15.74	224	0.875	bilinear
320	resnet34	91.200	8.800	98.240	1.760	21.80	224	0.875	bilinear
321	mnasnet_100	91.200	8.800	98.050	1.950	4.38	224	0.875	bicubic
322	regnetx_008	91.180	8.820	98.380	1.620	7.26	224	0.875	bicubic
323	hrnet_w18_small_v2	91.170	8.830	98.340	1.660	15.60	224	0.875	bilinear
324	mixer_b16_224	91.140	8.860	97.400	2.600	59.88	224	0.875	bicubic
325	resnest14d	91.130	8.870	98.330	1.670	10.61	224	0.875	bilinear
326	gluon_resnet34_v1b	91.100	8.900	98.180	1.820	21.80	224	0.875	bicubic
327	vit_deit_tiny_distilled_patch16_224	91.100	8.900	98.270	1.730	5.91	224	0.900	bicubic
328	swsl_resnet18	91.090	8.910	98.210	1.790	11.69	224	0.875	bilinear
329	vgg19_bn	90.990	9.010	98.110	1.890	143.68	224	0.875	bilinear
330	pit_ti_distilled_224	90.900	9.100	98.220	1.780	5.10	224	0.900	bicubic
331	regnety_004	90.780	9.220	98.080	1.920	4.34	224	0.875	bicubic
332	regnetx_006	90.760	9.240	98.100	1.900	6.20	224	0.875	bicubic
333	ssl_resnet18	90.700	9.300	98.020	1.980	11.69	224	0.875	bilinear
334	spnasnet_100	90.610	9.390	97.950	2.050	4.42	224	0.875	bilinear
335	vgg16_bn	90.540	9.460	97.990	2.010	138.37	224	0.875	bilinear
336	ghostnet_100	90.440	9.560	97.830	2.170	5.18	224	0.875	bilinear
337	pit_ti_224	90.420	9.580	98.010	1.990	4.85	224	0.900	bicubic
338	tf_mobilenetv3_large_075	90.320	9.680	97.870	2.130	3.99	224	0.875	bilinear
339	tv_resnet34	90.290	9.710	97.980	2.020	21.80	224	0.875	bilinear
340	skresnet18	90.160	9.840	97.780	2.220	11.96	224	0.875	bicubic
341	resnet18d	89.990	10.010	97.830	2.170	11.71	224	0.875	bicubic
342	hrnet_w18_small	89.880	10.120	97.900	2.100	13.19	224	0.875	bilinear
343	mobilenetv2_100	89.830	10.170	97.830	2.170	3.50	224	0.875	bicubic
344	vgg19	89.680	10.320	97.550	2.450	143.67	224	0.875	bilinear
345	vit_deit_tiny_patch16_224	89.620	10.380	97.960	2.040	5.72	224	0.900	bicubic
346	regnetx_004	89.460	10.540	97.770	2.230	5.16	224	0.875	bicubic
347	vgg16	89.360	10.640	97.520	2.480	138.36	224	0.875	bilinear
348	legacy_seresnet18	89.270	10.730	97.680	2.320	11.78	224	0.875	bicubic
349	vgg13_bn	89.200	10.800	97.530	2.470	133.05	224	0.875	bilinear
350	tf_mobilenetv3_large_minimal_100	89.180	10.820	97.320	2.680	3.92	224	0.875	bilinear
351	gluon_resnet18_v1b	88.660	11.340	97.100	2.900	11.69	224	0.875	bicubic
352	vgg11_bn	88.390	11.610	97.270	2.730	132.87	224	0.875	bilinear
353	regnety_002	88.200	11.800	97.430	2.570	3.16	224	0.875	bicubic
354	resnet18	88.150	11.850	97.120	2.880	11.69	224	0.875	bilinear
355	vgg13	87.570	12.430	97.120	2.880	133.05	224	0.875	bilinear
356	regnetx_002	87.380	12.620	96.990	3.010	2.68	224	0.875	bicubic
357	vgg11	87.340	12.660	97.110	2.890	132.86	224	0.875	bilinear
358	dla60x_c	87.110	12.890	97.140	2.860	1.32	224	0.875	bilinear
359	mixer_l16_224	86.970	13.030	94.060	5.940	208.20	224	0.875	bicubic
360	tf_mobilenetv3_small_100	85.960	14.040	96.400	3.600	2.54	224	0.875	bilinear
361	dla46x_c	85.480	14.520	96.440	3.560	1.07	224	0.875	bilinear
362	dla46_c	84.660	15.340	96.200	3.800	1.30	224	0.875	bilinear
363	tf_mobilenetv3_small_075	84.530	15.470	95.890	4.110	2.04	224	0.875	bilinear
364	tf_mobilenetv3_small_minimal_100	82.670	17.330	95.000	5.000	2.04	224	0.875	bilinear