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

1	model	top1	top1_err	top5	top5_err	param_count	img_size	cropt_pct	interpolation
2	tf_efficientnet_l2_ns	88.336	11.664	98.664	1.336	480.31	800	0.960	bicubic
3	tf_efficientnet_l2_ns_475	88.230	11.770	98.546	1.454	480.31	475	0.936	bicubic
4	tf_efficientnet_b7_ns	86.830	13.170	98.092	1.908	66.35	600	0.949	bicubic
5	tf_efficientnet_b6_ns	86.462	13.538	97.878	2.122	43.04	528	0.942	bicubic
6	dm_nfnet_f6	86.306	13.694	97.742	2.258	438.36	576	0.956	bicubic
7	tf_efficientnet_b5_ns	86.072	13.928	97.748	2.252	30.39	456	0.934	bicubic
8	dm_nfnet_f4	85.726	14.274	97.518	2.482	316.07	512	0.951	bicubic
9	dm_nfnet_f5	85.720	14.280	97.436	2.564	377.21	544	0.954	bicubic
10	dm_nfnet_f3	85.582	14.418	97.390	2.610	254.92	416	0.940	bicubic
11	ig_resnext101_32x48d	85.502	14.498	97.548	2.452	828.41	224	0.875	bilinear
12	vit_deit_base_distilled_patch16_384	85.422	14.578	97.334	2.666	87.63	384	1.000	bicubic
13	tf_efficientnet_b8	85.384	14.616	97.400	2.600	87.41	672	0.954	bicubic
14	tf_efficientnet_b8_ap	85.384	14.616	97.298	2.702	87.41	672	0.954	bicubic
15	tf_efficientnet_b4_ns	85.194	14.806	97.500	2.500	19.34	380	0.922	bicubic
16	vit_large_patch16_384	85.170	14.830	97.344	2.656	304.72	384	1.000	bicubic
17	ig_resnext101_32x32d	85.146	14.854	97.456	2.544	468.53	224	0.875	bilinear
18	tf_efficientnet_b7_ap	85.124	14.876	97.256	2.744	66.35	600	0.949	bicubic
19	vit_base_resnet50_384	84.994	15.006	97.294	2.706	98.95	384	1.000	bicubic
20	dm_nfnet_f2	84.968	15.032	97.124	2.876	193.78	352	0.920	bicubic
21	tf_efficientnet_b7	84.936	15.064	97.208	2.792	66.35	600	0.949	bicubic
22	ecaresnet269d	84.926	15.074	97.236	2.764	102.09	352	1.000	bicubic
23	resnetv2_152x4_bitm	84.916	15.084	97.444	2.556	936.53	480	1.000	bilinear
24	tf_efficientnet_b6_ap	84.790	15.210	97.136	2.864	43.04	528	0.942	bicubic
25	dm_nfnet_f1	84.594	15.406	97.080	2.920	132.63	320	0.910	bicubic
26	resnest269e	84.518	15.482	97.002	2.998	110.93	416	0.928	bicubic
27	resnetv2_152x2_bitm	84.428	15.572	97.452	2.548	236.34	480	1.000	bilinear
28	resnetv2_101x3_bitm	84.392	15.608	97.358	2.642	387.93	480	1.000	bilinear
29	seresnet152d	84.350	15.650	97.042	2.958	66.84	320	1.000	bicubic
30	swsl_resnext101_32x8d	84.332	15.668	97.154	2.846	88.79	224	0.875	bilinear
31	tf_efficientnet_b5_ap	84.260	15.740	96.974	3.026	30.39	456	0.934	bicubic
32	vit_base_patch16_384	84.212	15.788	97.216	2.784	86.86	384	1.000	bicubic
33	ig_resnext101_32x16d	84.168	15.832	97.196	2.804	194.03	224	0.875	bilinear
34	tf_efficientnet_b6	84.122	15.878	96.890	3.110	43.04	528	0.942	bicubic
35	tf_efficientnet_b3_ns	84.012	15.988	96.910	3.090	12.23	300	0.904	bicubic
36	resnet200d	84.000	16.000	96.824	3.176	64.69	320	1.000	bicubic
37	resnest200e	83.840	16.160	96.858	3.142	70.20	320	0.909	bicubic
38	tf_efficientnet_b5	83.820	16.180	96.760	3.240	30.39	456	0.934	bicubic
39	resnetv2_50x3_bitm	83.800	16.200	97.110	2.890	217.32	480	1.000	bilinear
40	resnet152d	83.664	16.336	96.726	3.274	60.21	320	1.000	bicubic
41	swsl_resnext101_32x16d	83.464	16.536	96.866	3.134	194.03	224	0.875	bilinear
42	vit_deit_base_distilled_patch16_224	83.372	16.628	96.504	3.496	87.34	224	0.900	bicubic
43	dm_nfnet_f0	83.370	16.630	96.558	3.442	71.49	256	0.900	bicubic
44	swsl_resnext101_32x4d	83.252	16.748	96.768	3.232	44.18	224	0.875	bilinear
45	tf_efficientnet_b4_ap	83.224	16.776	96.366	3.634	19.34	380	0.922	bicubic
46	vit_deit_base_patch16_384	83.092	16.908	96.352	3.648	86.86	384	1.000	bicubic
47	vit_large_patch16_224	83.060	16.940	96.424	3.576	304.33	224	0.900	bicubic
48	tresnet_xl_448	83.042	16.958	96.182	3.818	78.44	448	0.875	bilinear
49	resnet101d	83.000	17.000	96.460	3.540	44.57	320	1.000	bicubic
50	tf_efficientnet_b4	82.974	17.026	96.292	3.708	19.34	380	0.922	bicubic
51	resnest101e	82.824	17.176	96.310	3.690	48.28	256	0.875	bilinear
52	pnasnet5large	82.786	17.214	96.076	3.924	86.06	331	0.911	bicubic
53	ig_resnext101_32x8d	82.660	17.340	96.684	3.316	88.79	224	0.875	bilinear
54	nasnetalarge	82.640	17.360	96.052	3.948	88.75	331	0.911	bicubic
55	tf_efficientnet_b2_ns	82.366	17.634	96.260	3.740	9.11	260	0.890	bicubic
56	ecaresnet50t	82.348	17.652	96.144	3.856	25.57	320	0.950	bicubic
57	tresnet_l_448	82.290	17.710	95.978	4.022	55.99	448	0.875	bilinear
58	efficientnet_b3a	82.232	17.768	96.126	3.874	12.23	320	1.000	bicubic
59	resnetv2_101x1_bitm	82.208	17.792	96.460	3.540	44.54	480	1.000	bilinear
60	swsl_resnext50_32x4d	82.186	17.814	96.264	3.736	25.03	224	0.875	bilinear
61	tresnet_xl	82.166	17.834	95.934	4.066	78.44	224	0.875	bilinear
62	ecaresnet101d	82.118	17.882	96.040	3.960	44.57	224	0.875	bicubic
63	efficientnet_b3	82.032	17.968	96.036	3.964	12.23	300	0.904	bicubic
64	regnety_032	82.016	17.984	95.932	4.068	19.44	224	0.875	bicubic
65	vit_deit_base_patch16_224	81.994	18.006	95.738	4.262	86.57	224	0.900	bicubic
66	ssl_resnext101_32x16d	81.846	18.154	96.132	3.868	194.03	224	0.875	bilinear
67	tf_efficientnet_b3_ap	81.802	18.198	95.600	4.400	12.23	300	0.904	bicubic
68	vit_base_patch16_224	81.780	18.220	96.112	3.888	86.57	224	0.900	bicubic
69	tresnet_m_448	81.692	18.308	95.560	4.440	31.39	448	0.875	bilinear
70	rexnet_200	81.688	18.312	95.690	4.310	16.37	224	0.875	bicubic
71	vit_base_patch32_384	81.664	18.336	96.128	3.872	88.30	384	1.000	bicubic
72	tf_efficientnet_b3	81.626	18.374	95.706	4.294	12.23	300	0.904	bicubic
73	ssl_resnext101_32x8d	81.600	18.400	96.022	3.978	88.79	224	0.875	bilinear
74	tf_efficientnet_lite4	81.516	18.484	95.624	4.376	13.01	380	0.920	bilinear
75	vit_large_patch32_384	81.506	18.494	96.108	3.892	306.63	384	1.000	bicubic
76	tresnet_l	81.490	18.510	95.584	4.416	55.99	224	0.875	bilinear
77	tf_efficientnet_b1_ns	81.398	18.602	95.730	4.270	7.79	240	0.882	bicubic
78	gernet_l	81.344	18.656	95.540	4.460	31.08	256	0.875	bilinear
79	legacy_senet154	81.322	18.678	95.454	4.546	115.09	224	0.875	bilinear
80	wide_resnet50_2	81.306	18.694	95.588	4.412	68.88	224	0.875	bicubic
81	seresnext50_32x4d	81.270	18.730	95.656	4.344	27.56	224	0.875	bicubic
82	vit_deit_small_distilled_patch16_224	81.250	18.750	95.396	4.604	22.44	224	0.900	bicubic
83	gluon_senet154	81.216	18.784	95.320	4.680	115.09	224	0.875	bicubic
84	resnest50d_4s2x40d	81.148	18.852	95.552	4.448	30.42	224	0.875	bicubic
85	swsl_resnet50	81.124	18.876	95.988	4.012	25.56	224	0.875	bilinear
86	ssl_resnext101_32x4d	81.024	18.976	95.748	4.252	44.18	224	0.875	bilinear
87	gluon_resnet152_v1s	81.020	18.980	95.426	4.574	60.32	224	0.875	bicubic
88	resnest50d	80.970	19.030	95.350	4.650	27.48	224	0.875	bilinear
89	resnest50d_1s4x24d	80.938	19.062	95.318	4.682	25.68	224	0.875	bicubic
90	ecaresnet101d_pruned	80.886	19.114	95.572	4.428	24.88	224	0.875	bicubic
91	gluon_seresnext101_32x4d	80.878	19.122	95.274	4.726	48.96	224	0.875	bicubic
92	gluon_seresnext101_64x4d	80.852	19.148	95.336	4.664	88.23	224	0.875	bicubic
93	efficientnet_b3_pruned	80.820	19.180	95.224	4.776	9.86	300	0.904	bicubic
94	regnety_320	80.782	19.218	95.262	4.738	145.05	224	0.875	bicubic
95	gernet_m	80.730	19.270	95.212	4.788	21.14	224	0.875	bilinear
96	tresnet_m	80.720	19.280	94.856	5.144	31.39	224	0.875	bilinear
97	nf_resnet50	80.666	19.334	95.358	4.642	25.56	288	0.940	bicubic
98	gluon_resnext101_64x4d	80.636	19.364	94.990	5.010	83.46	224	0.875	bicubic
99	ecaresnet50d	80.614	19.386	95.314	4.686	25.58	224	0.875	bicubic
100	efficientnet_b2a	80.608	19.392	95.298	4.702	9.11	288	1.000	bicubic
101	resnet50d	80.492	19.508	95.128	4.872	25.58	224	0.875	bicubic
102	gluon_resnet152_v1d	80.480	19.520	95.262	4.738	60.21	224	0.875	bicubic
103	ecaresnetlight	80.460	19.540	95.202	4.798	30.16	224	0.875	bicubic
104	inception_resnet_v2	80.448	19.552	95.292	4.708	55.84	299	0.897	bicubic
105	repvgg_b3	80.440	19.560	95.194	4.806	123.09	224	0.875	bilinear
106	gluon_resnet101_v1d	80.430	19.570	95.014	4.986	44.57	224	0.875	bicubic
107	mixnet_xl	80.424	19.576	94.888	5.112	11.90	224	0.875	bicubic
108	regnety_160	80.414	19.586	94.980	5.020	83.59	224	0.875	bicubic
109	regnety_120	80.374	19.626	95.108	4.892	51.82	224	0.875	bicubic
110	rexnet_150	80.350	19.650	95.202	4.798	9.73	224	0.875	bicubic
111	ssl_resnext50_32x4d	80.332	19.668	95.382	4.618	25.03	224	0.875	bilinear
112	efficientnet_b2	80.314	19.686	95.112	4.888	9.11	260	0.875	bicubic
113	regnetx_320	80.314	19.686	95.068	4.932	107.81	224	0.875	bicubic
114	gluon_resnet101_v1s	80.296	19.704	95.176	4.824	44.67	224	0.875	bicubic
115	seresnet50	80.292	19.708	95.048	4.952	28.09	224	0.875	bicubic
116	tf_efficientnet_el	80.292	19.708	95.120	4.880	10.59	300	0.904	bicubic
117	legacy_seresnext101_32x4d	80.282	19.718	95.024	4.976	48.96	224	0.875	bilinear
118	tf_efficientnet_b2_ap	80.240	19.760	94.984	5.016	9.11	260	0.890	bicubic
119	repvgg_b3g4	80.238	19.762	95.068	4.932	83.83	224	0.875	bilinear
120	gluon_resnext101_32x4d	80.218	19.782	94.908	5.092	44.18	224	0.875	bicubic
121	dpn107	80.180	19.820	94.906	5.094	86.92	224	0.875	bicubic
122	inception_v4	80.154	19.846	94.962	5.038	42.68	299	0.875	bicubic
123	skresnext50_32x4d	80.154	19.846	94.702	5.298	27.48	224	0.875	bicubic
124	resnetv2_50x1_bitm	80.152	19.848	95.644	4.356	25.55	480	1.000	bilinear
125	cspdarknet53	80.050	19.950	95.076	4.924	27.64	256	0.887	bilinear
126	dpn92	80.034	19.966	94.818	5.182	37.67	224	0.875	bicubic
127	tf_efficientnet_b2	80.024	19.976	94.944	5.056	9.11	260	0.890	bicubic
128	cspresnext50	80.006	19.994	94.932	5.068	20.57	224	0.875	bilinear
129	gluon_seresnext50_32x4d	79.948	20.052	94.836	5.164	27.56	224	0.875	bicubic
130	ens_adv_inception_resnet_v2	79.930	20.070	94.950	5.050	55.84	299	0.897	bicubic
131	ecaresnet26t	79.884	20.116	95.072	4.928	16.01	320	0.950	bicubic
132	regnetx_160	79.884	20.116	94.826	5.174	54.28	224	0.875	bicubic
133	vit_deit_small_patch16_224	79.868	20.132	95.042	4.958	22.05	224	0.900	bicubic
134	dpn131	79.866	20.134	94.726	5.274	79.25	224	0.875	bicubic
135	gluon_resnet152_v1c	79.850	20.150	94.890	5.110	60.21	224	0.875	bicubic
136	xception71	79.846	20.154	94.936	5.064	42.34	299	0.903	bicubic
137	regnety_080	79.840	20.160	94.848	5.152	39.18	224	0.875	bicubic
138	efficientnet_b2_pruned	79.832	20.168	94.806	5.194	8.31	260	0.890	bicubic
139	tf_efficientnet_lite3	79.758	20.242	94.864	5.136	8.20	300	0.904	bilinear
140	gluon_xception65	79.756	20.244	94.852	5.148	39.92	299	0.903	bicubic
141	regnety_064	79.736	20.264	94.758	5.242	30.58	224	0.875	bicubic
142	resnext50_32x4d	79.722	20.278	94.606	5.394	25.03	224	0.875	bicubic
143	dpn98	79.688	20.312	94.644	5.356	61.57	224	0.875	bicubic
144	resnext50d_32x4d	79.688	20.312	94.844	5.156	25.05	224	0.875	bicubic
145	ecaresnet50d_pruned	79.676	20.324	94.922	5.078	19.94	224	0.875	bicubic
146	gluon_resnet152_v1b	79.634	20.366	94.758	5.242	60.19	224	0.875	bicubic
147	xception65	79.592	20.408	94.658	5.342	39.92	299	0.903	bicubic
148	cspresnet50	79.582	20.418	94.712	5.288	21.62	256	0.887	bilinear
149	regnetx_120	79.574	20.426	94.692	5.308	46.11	224	0.875	bicubic
150	gluon_resnet101_v1c	79.550	20.450	94.642	5.358	44.57	224	0.875	bicubic
151	rexnet_130	79.516	20.484	94.660	5.340	7.56	224	0.875	bicubic
152	hrnet_w64	79.488	20.512	94.638	5.362	128.06	224	0.875	bilinear
153	dla102x2	79.428	20.572	94.628	5.372	41.28	224	0.875	bilinear
154	repvgg_b2g4	79.404	20.596	94.706	5.294	61.76	224	0.875	bilinear
155	gluon_resnet101_v1b	79.360	20.640	94.508	5.492	44.55	224	0.875	bicubic
156	nf_regnet_b1	79.324	20.676	94.772	5.228	10.22	288	0.900	bicubic
157	gluon_resnext50_32x4d	79.320	20.680	94.500	5.500	25.03	224	0.875	bicubic
158	tf_efficientnet_b1_ap	79.290	20.710	94.326	5.674	7.79	240	0.882	bicubic
159	tf_efficientnet_cc_b1_8e	79.288	20.712	94.358	5.642	39.72	240	0.882	bicubic
160	resnetblur50	79.262	20.738	94.622	5.378	25.56	224	0.875	bicubic
161	ssl_resnet50	79.240	20.760	94.914	5.086	25.56	224	0.875	bilinear
162	hrnet_w48	79.236	20.764	94.522	5.478	77.47	224	0.875	bilinear
163	efficientnet_em	79.230	20.770	94.792	5.208	6.90	240	0.882	bicubic
164	regnety_040	79.216	20.784	94.662	5.338	20.65	224	0.875	bicubic
165	resnext101_32x8d	79.210	20.790	94.556	5.444	88.79	224	0.875	bilinear
166	ese_vovnet39b	79.206	20.794	94.728	5.272	24.57	224	0.875	bicubic
167	regnetx_080	79.174	20.826	94.556	5.444	39.57	224	0.875	bicubic
168	dpn68b	79.140	20.860	94.424	5.576	12.61	224	0.875	bicubic
169	res2net50_26w_8s	79.130	20.870	94.404	5.596	48.40	224	0.875	bilinear
170	res2net101_26w_4s	79.120	20.880	94.432	5.568	45.21	224	0.875	bilinear
171	legacy_seresnext50_32x4d	79.108	20.892	94.478	5.522	27.56	224	0.875	bilinear
172	regnetx_064	79.078	20.922	94.460	5.540	26.21	224	0.875	bicubic
173	gluon_resnet50_v1d	79.072	20.928	94.478	5.522	25.58	224	0.875	bicubic
174	xception	79.028	20.972	94.370	5.630	22.86	299	0.897	bicubic
175	resnet50	79.004	20.996	94.392	5.608	25.56	224	0.875	bicubic
176	mixnet_l	78.932	21.068	94.184	5.816	7.33	224	0.875	bicubic
177	wide_resnet101_2	78.910	21.090	94.344	5.656	126.89	224	0.875	bilinear
178	hrnet_w40	78.906	21.094	94.434	5.566	57.56	224	0.875	bilinear
179	hrnet_w44	78.886	21.114	94.410	5.590	67.06	224	0.875	bilinear
180	repvgg_b2	78.882	21.118	94.346	5.654	89.02	224	0.875	bilinear
181	tf_efficientnet_b1	78.832	21.168	94.206	5.794	7.79	240	0.882	bicubic
182	gluon_inception_v3	78.830	21.170	94.398	5.602	23.83	299	0.875	bicubic
183	tf_mixnet_l	78.802	21.198	94.054	5.946	7.33	224	0.875	bicubic
184	gluon_resnet50_v1s	78.788	21.212	94.240	5.760	25.68	224	0.875	bicubic
185	dla169	78.732	21.268	94.334	5.666	53.39	224	0.875	bilinear
186	legacy_seresnet152	78.644	21.356	94.390	5.610	66.82	224	0.875	bilinear
187	efficientnet_b1	78.604	21.396	94.094	5.906	7.79	240	0.875	bicubic
188	res2net50_26w_6s	78.604	21.396	94.164	5.836	37.05	224	0.875	bilinear
189	tf_efficientnet_b0_ns	78.600	21.400	94.388	5.612	5.29	224	0.875	bicubic
190	dla102x	78.528	21.472	94.206	5.794	26.31	224	0.875	bilinear
191	dla60_res2net	78.522	21.478	94.252	5.748	20.85	224	0.875	bilinear
192	selecsls60b	78.496	21.504	94.192	5.808	32.77	224	0.875	bicubic
193	xception41	78.496	21.504	94.256	5.744	26.97	299	0.903	bicubic
194	regnetx_040	78.494	21.506	94.270	5.730	22.12	224	0.875	bicubic
195	repvgg_b1	78.442	21.558	94.158	5.842	57.42	224	0.875	bilinear
196	resnest26d	78.440	21.560	94.296	5.704	17.07	224	0.875	bilinear
197	hrnet_w32	78.424	21.576	94.202	5.798	41.23	224	0.875	bilinear
198	legacy_seresnet101	78.420	21.580	94.174	5.826	49.33	224	0.875	bilinear
199	dla60_res2next	78.322	21.678	94.190	5.810	17.03	224	0.875	bilinear
200	efficientnet_b1_pruned	78.274	21.726	93.808	6.192	6.33	240	0.882	bicubic
201	tv_resnet152	78.250	21.750	93.982	6.018	60.19	224	0.875	bilinear
202	dla60x	78.226	21.774	93.988	6.012	17.35	224	0.875	bilinear
203	tf_efficientnet_em	78.160	21.840	94.046	5.954	6.90	240	0.882	bicubic
204	regnetx_032	78.148	21.852	94.066	5.934	15.30	224	0.875	bicubic
205	hrnet_w30	78.134	21.866	94.192	5.808	37.71	224	0.875	bilinear
206	res2net50_14w_8s	78.118	21.882	93.836	6.164	25.06	224	0.875	bilinear
207	res2next50	78.080	21.920	93.952	6.048	24.67	224	0.875	bilinear
208	dla102	78.054	21.946	93.918	6.082	33.27	224	0.875	bilinear
209	efficientnet_es	78.032	21.968	93.900	6.100	5.44	224	0.875	bicubic
210	res2net50_26w_4s	77.966	22.034	93.830	6.170	25.70	224	0.875	bilinear
211	gluon_resnet50_v1c	77.926	22.074	94.006	5.994	25.58	224	0.875	bicubic
212	tf_efficientnet_cc_b0_8e	77.926	22.074	93.598	6.402	24.01	224	0.875	bicubic
213	selecsls60	77.914	22.086	93.822	6.178	30.67	224	0.875	bicubic
214	rexnet_100	77.886	22.114	93.858	6.142	4.80	224	0.875	bicubic
215	vit_small_patch16_224	77.872	22.128	93.392	6.608	48.75	224	0.900	bicubic
216	seresnext26t_32x4d	77.830	22.170	93.728	6.272	16.81	224	0.875	bicubic
217	tf_inception_v3	77.804	22.196	93.650	6.350	23.83	299	0.875	bicubic
218	regnety_016	77.804	22.196	93.724	6.276	11.20	224	0.875	bicubic
219	gluon_resnet50_v1b	77.664	22.336	93.674	6.326	25.56	224	0.875	bicubic
220	tv_resnext50_32x4d	77.628	22.372	93.680	6.320	25.03	224	0.875	bilinear
221	legacy_seresnet50	77.612	22.388	93.796	6.204	28.09	224	0.875	bilinear
222	efficientnet_b0	77.610	22.390	93.564	6.436	5.29	224	0.875	bicubic
223	adv_inception_v3	77.562	22.438	93.686	6.314	23.83	299	0.875	bicubic
224	repvgg_b1g4	77.540	22.460	93.794	6.206	39.97	224	0.875	bilinear
225	res2net50_48w_2s	77.518	22.482	93.582	6.418	25.29	224	0.875	bilinear
226	seresnext26d_32x4d	77.518	22.482	93.606	6.394	16.81	224	0.875	bicubic
227	tf_efficientnet_lite2	77.440	22.560	93.762	6.238	6.09	260	0.890	bicubic
228	inception_v3	77.410	22.590	93.474	6.526	23.83	299	0.875	bicubic
229	densenet161	77.338	22.662	93.688	6.312	28.68	224	0.875	bicubic
230	mobilenetv2_120d	77.328	22.672	93.478	6.522	5.83	224	0.875	bicubic
231	densenet201	77.320	22.680	93.482	6.518	20.01	224	0.875	bicubic
232	tv_resnet101	77.314	22.686	93.556	6.444	44.55	224	0.875	bilinear
233	tf_efficientnet_cc_b0_4e	77.296	22.704	93.360	6.640	13.31	224	0.875	bicubic
234	mixnet_m	77.176	22.824	93.426	6.574	5.01	224	0.875	bicubic
235	legacy_seresnext26_32x4d	77.116	22.884	93.358	6.642	16.79	224	0.875	bicubic
236	selecsls42b	77.096	22.904	93.424	6.576	32.46	224	0.875	bicubic
237	resnet34d	77.096	22.904	93.392	6.608	21.82	224	0.875	bicubic
238	tf_efficientnet_b0_ap	77.072	22.928	93.262	6.738	5.29	224	0.875	bicubic
239	tf_mixnet_m	76.964	23.036	93.212	6.788	5.01	224	0.875	bicubic
240	dla60	76.924	23.076	93.290	6.710	22.04	224	0.875	bilinear
241	regnetx_016	76.914	23.086	93.372	6.628	9.19	224	0.875	bicubic
242	skresnet34	76.910	23.090	93.272	6.728	22.28	224	0.875	bicubic
243	gernet_s	76.874	23.126	93.128	6.872	8.17	224	0.875	bilinear
244	hrnet_w18	76.832	23.168	93.404	6.596	21.30	224	0.875	bilinear
245	tf_efficientnet_b0	76.830	23.170	93.272	6.728	5.29	224	0.875	bicubic
246	ese_vovnet19b_dw	76.772	23.228	93.276	6.724	6.54	224	0.875	bicubic
247	tf_efficientnet_lite1	76.628	23.372	93.248	6.752	5.42	240	0.882	bicubic
248	resnet26d	76.600	23.400	93.188	6.812	16.01	224	0.875	bicubic
249	tf_efficientnet_es	76.562	23.438	93.184	6.816	5.44	224	0.875	bicubic
250	mobilenetv2_140	76.538	23.462	92.944	7.056	6.11	224	0.875	bicubic
251	repvgg_a2	76.488	23.512	93.022	6.978	28.21	224	0.875	bilinear
252	densenetblur121d	76.474	23.526	93.096	6.904	8.00	224	0.875	bicubic
253	dpn68	76.378	23.622	92.978	7.022	12.61	224	0.875	bicubic
254	regnety_008	76.324	23.676	93.100	6.900	6.26	224	0.875	bicubic
255	mixnet_s	76.062	23.938	92.826	7.174	4.13	224	0.875	bicubic
256	tv_resnet50	76.012	23.988	92.934	7.066	25.56	224	0.875	bilinear
257	densenet169	75.950	24.050	92.994	7.006	14.15	224	0.875	bicubic
258	mobilenetv3_large_100	75.710	24.290	92.496	7.504	5.48	224	0.875	bicubic
259	tf_mixnet_s	75.658	24.342	92.618	7.382	4.13	224	0.875	bicubic
260	resnest14d	75.588	24.412	92.488	7.512	10.61	224	0.875	bilinear
261	mobilenetv3_rw	75.542	24.458	92.676	7.324	5.48	224	0.875	bicubic
262	densenet121	75.530	24.470	92.616	7.384	7.98	224	0.875	bicubic
263	tf_mobilenetv3_large_100	75.520	24.480	92.550	7.450	5.48	224	0.875	bilinear
264	efficientnet_lite0	75.444	24.556	92.544	7.456	4.65	224	0.875	bicubic
265	semnasnet_100	75.426	24.574	92.548	7.452	3.89	224	0.875	bicubic
266	resnet26	75.394	24.606	92.584	7.416	16.00	224	0.875	bicubic
267	repvgg_b0	75.214	24.786	92.454	7.546	15.82	224	0.875	bilinear
268	regnety_006	75.206	24.794	92.560	7.440	6.06	224	0.875	bicubic
269	hrnet_w18_small_v2	75.164	24.836	92.430	7.570	15.60	224	0.875	bilinear
270	resnet34	75.096	24.904	92.246	7.754	21.80	224	0.875	bilinear
271	fbnetc_100	75.082	24.918	92.354	7.646	5.57	224	0.875	bilinear
272	mobilenetv2_110d	75.048	24.952	92.132	7.868	4.52	224	0.875	bicubic
273	regnetx_008	75.026	24.974	92.332	7.668	7.26	224	0.875	bicubic
274	legacy_seresnet34	74.912	25.088	92.164	7.836	21.96	224	0.875	bilinear
275	tf_efficientnet_lite0	74.868	25.132	92.130	7.870	4.65	224	0.875	bicubic
276	tv_densenet121	74.746	25.254	92.130	7.870	7.98	224	0.875	bicubic
277	mnasnet_100	74.692	25.308	92.140	7.860	4.38	224	0.875	bicubic
278	dla34	74.636	25.364	92.122	7.878	15.74	224	0.875	bilinear
279	gluon_resnet34_v1b	74.496	25.504	92.008	7.992	21.80	224	0.875	bicubic
280	vit_deit_tiny_distilled_patch16_224	74.494	25.506	91.884	8.116	5.91	224	0.900	bicubic
281	vgg19_bn	74.216	25.784	91.848	8.152	143.68	224	0.875	bilinear
282	spnasnet_100	74.120	25.880	91.882	8.118	4.42	224	0.875	bilinear
283	regnetx_006	73.962	26.038	91.684	8.316	6.20	224	0.875	bicubic
284	regnety_004	73.942	26.058	91.754	8.246	4.34	224	0.875	bicubic
285	vgg16_bn	73.476	26.524	91.536	8.464	138.37	224	0.875	bilinear
286	tf_mobilenetv3_large_075	73.372	26.628	91.404	8.596	3.99	224	0.875	bilinear
287	swsl_resnet18	73.318	26.682	91.752	8.248	11.69	224	0.875	bilinear
288	tv_resnet34	73.266	26.734	91.430	8.570	21.80	224	0.875	bilinear
289	skresnet18	73.000	27.000	91.156	8.844	11.96	224	0.875	bicubic
290	mobilenetv2_100	72.956	27.044	91.042	8.958	3.50	224	0.875	bicubic
291	regnetx_004	72.536	27.464	90.842	9.158	5.16	224	0.875	bicubic
292	ssl_resnet18	72.492	27.508	91.442	8.558	11.69	224	0.875	bilinear
293	resnet18d	72.380	27.620	90.710	9.290	11.71	224	0.875	bicubic
294	vgg19	72.360	27.640	90.850	9.150	143.67	224	0.875	bilinear
295	hrnet_w18_small	72.276	27.724	90.586	9.414	13.19	224	0.875	bilinear
296	tf_mobilenetv3_large_minimal_100	72.228	27.772	90.682	9.318	3.92	224	0.875	bilinear
297	vit_deit_tiny_patch16_224	72.196	27.804	91.092	8.908	5.72	224	0.900	bicubic
298	legacy_seresnet18	71.752	28.248	90.308	9.692	11.78	224	0.875	bicubic
299	vgg16	71.628	28.372	90.368	9.632	138.36	224	0.875	bilinear
300	vgg13_bn	71.618	28.382	90.360	9.640	133.05	224	0.875	bilinear
301	gluon_resnet18_v1b	70.922	29.078	89.770	10.230	11.69	224	0.875	bicubic
302	vgg11_bn	70.408	29.592	89.724	10.276	132.87	224	0.875	bilinear
303	regnety_002	70.326	29.674	89.556	10.444	3.16	224	0.875	bicubic
304	vgg13	69.984	30.016	89.306	10.694	133.05	224	0.875	bilinear
305	resnet18	69.644	30.356	88.982	11.018	11.69	224	0.875	bilinear
306	vgg11	68.872	31.128	88.658	11.342	132.86	224	0.875	bilinear
307	regnetx_002	68.830	31.170	88.510	11.490	2.68	224	0.875	bicubic
308	dla60x_c	67.952	32.048	88.438	11.562	1.32	224	0.875	bilinear
309	tf_mobilenetv3_small_100	67.876	32.124	87.682	12.318	2.54	224	0.875	bilinear
310	dla46x_c	65.930	34.070	87.004	12.996	1.07	224	0.875	bilinear
311	tf_mobilenetv3_small_075	65.732	34.268	86.168	13.832	2.04	224	0.875	bilinear
312	dla46_c	64.930	35.070	86.308	13.692	1.30	224	0.875	bilinear
313	tf_mobilenetv3_small_minimal_100	62.744	37.256	84.380	15.620	2.04	224	0.875	bilinear