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	88.352	11.648	98.650	1.350	480.31	800	0.960	bicubic
3	tf_efficientnet_l2_ns_475	88.234	11.766	98.546	1.454	480.31	475	0.936	bicubic
4	tf_efficientnet_b7_ns	86.840	13.160	98.094	1.906	66.35	600	0.949	bicubic
5	tf_efficientnet_b6_ns	86.452	13.548	97.882	2.118	43.04	528	0.942	bicubic
6	tf_efficientnet_b5_ns	86.088	13.912	97.752	2.248	30.39	456	0.934	bicubic
7	ig_resnext101_32x48d	85.428	14.572	97.572	2.428	828.41	224	0.875	bilinear
8	tf_efficientnet_b8	85.370	14.630	97.390	2.610	87.41	672	0.954	bicubic
9	tf_efficientnet_b8_ap	85.370	14.630	97.294	2.706	87.41	672	0.954	bicubic
10	tf_efficientnet_b4_ns	85.162	14.838	97.470	2.530	19.34	380	0.922	bicubic
11	vit_large_patch16_384	85.158	14.842	97.356	2.644	304.72	384	1.000	bicubic
12	tf_efficientnet_b7_ap	85.120	14.880	97.252	2.748	66.35	600	0.949	bicubic
13	ig_resnext101_32x32d	85.094	14.906	97.438	2.562	468.53	224	0.875	bilinear
14	tf_efficientnet_b7	84.936	15.064	97.204	2.796	66.35	600	0.949	bicubic
15	tf_efficientnet_b6_ap	84.788	15.212	97.138	2.862	43.04	528	0.942	bicubic
16	resnest269e	84.518	15.482	96.986	3.014	110.93	416	0.928	bicubic
17	swsl_resnext101_32x8d	84.284	15.716	97.176	2.824	88.79	224	0.875	bilinear
18	tf_efficientnet_b5_ap	84.252	15.748	96.974	3.026	30.39	456	0.934	bicubic
19	vit_base_patch16_384	84.210	15.790	97.218	2.782	86.86	384	1.000	bicubic
20	ig_resnext101_32x16d	84.170	15.830	97.196	2.804	194.03	224	0.875	bilinear
21	tf_efficientnet_b6	84.110	15.890	96.886	3.114	43.04	528	0.942	bicubic
22	tf_efficientnet_b3_ns	84.048	15.952	96.910	3.090	12.23	300	0.904	bicubic
23	resnest200e	83.832	16.168	96.894	3.106	70.20	320	0.909	bicubic
24	tf_efficientnet_b5	83.812	16.188	96.748	3.252	30.39	456	0.934	bicubic
25	swsl_resnext101_32x16d	83.346	16.654	96.846	3.154	194.03	224	0.875	bilinear
26	tf_efficientnet_b4_ap	83.248	16.752	96.392	3.608	19.34	380	0.922	bicubic
27	swsl_resnext101_32x4d	83.230	16.770	96.760	3.240	44.18	224	0.875	bilinear
28	tresnet_xl_448	83.050	16.950	96.174	3.826	78.44	448	0.875	bilinear
29	tf_efficientnet_b4	83.022	16.978	96.300	3.700	19.34	380	0.922	bicubic
30	resnest101e	82.890	17.110	96.320	3.680	48.28	256	0.875	bilinear
31	pnasnet5large	82.782	17.218	96.040	3.960	86.06	331	0.911	bicubic
32	ig_resnext101_32x8d	82.688	17.312	96.636	3.364	88.79	224	0.875	bilinear
33	nasnetalarge	82.620	17.380	96.046	3.954	88.75	331	0.911	bicubic
34	tf_efficientnet_b2_ns	82.380	17.620	96.248	3.752	9.11	260	0.890	bicubic
35	tresnet_l_448	82.268	17.732	95.976	4.024	55.99	448	0.875	bilinear
36	efficientnet_b3a	82.242	17.758	96.114	3.886	12.23	320	1.000	bicubic
37	swsl_resnext50_32x4d	82.182	17.818	96.230	3.770	25.03	224	0.875	bilinear
38	ecaresnet101d	82.172	17.828	96.046	3.954	44.57	224	0.875	bicubic
39	efficientnet_b3	82.076	17.924	96.020	3.980	12.23	300	0.904	bicubic
40	tresnet_xl	82.054	17.946	95.936	4.064	78.44	224	0.875	bilinear
41	regnety_032	82.002	17.998	95.906	4.094	19.44	224	0.875	bicubic
42	ssl_resnext101_32x16d	81.844	18.156	96.096	3.904	194.03	224	0.875	bilinear
43	tf_efficientnet_b3_ap	81.822	18.178	95.624	4.376	12.23	300	0.904	bicubic
44	tresnet_m_448	81.714	18.286	95.572	4.428	31.39	448	0.875	bilinear
45	vit_base_patch32_384	81.652	18.348	96.128	3.872	88.30	384	1.000	bicubic
46	tf_efficientnet_b3	81.636	18.364	95.718	4.282	12.23	300	0.904	bicubic
47	rexnet_200	81.632	18.368	95.668	4.332	16.37	224	0.875	bicubic
48	ssl_resnext101_32x8d	81.616	18.384	96.038	3.962	88.79	224	0.875	bilinear
49	tf_efficientnet_lite4	81.536	18.464	95.668	4.332	13.01	380	0.920	bilinear
50	vit_large_patch32_384	81.506	18.494	96.092	3.908	306.63	384	1.000	bicubic
51	tresnet_l	81.490	18.510	95.624	4.376	55.99	224	0.875	bilinear
52	wide_resnet50_2	81.456	18.544	95.532	4.468	68.88	224	0.875	bicubic
53	tf_efficientnet_b1_ns	81.388	18.612	95.738	4.262	7.79	240	0.882	bicubic
54	legacy_senet154	81.310	18.690	95.496	4.504	115.09	224	0.875	bilinear
55	seresnext50_32x4d	81.266	18.734	95.620	4.380	27.56	224	0.875	bicubic
56	gluon_senet154	81.234	18.766	95.348	4.652	115.09	224	0.875	bicubic
57	swsl_resnet50	81.166	18.834	95.972	4.028	25.56	224	0.875	bilinear
58	resnest50d_4s2x40d	81.108	18.892	95.558	4.442	30.42	224	0.875	bicubic
59	gluon_resnet152_v1s	81.016	18.984	95.412	4.588	60.32	224	0.875	bicubic
60	resnest50d_1s4x24d	80.988	19.012	95.322	4.678	25.68	224	0.875	bicubic
61	resnest50d	80.974	19.026	95.378	4.622	27.48	224	0.875	bilinear
62	ssl_resnext101_32x4d	80.924	19.076	95.728	4.272	44.18	224	0.875	bilinear
63	gluon_seresnext101_32x4d	80.904	19.096	95.294	4.706	48.96	224	0.875	bicubic
64	gluon_seresnext101_64x4d	80.894	19.106	95.308	4.692	88.23	224	0.875	bicubic
65	efficientnet_b3_pruned	80.858	19.142	95.242	4.758	9.86	300	0.904	bicubic
66	ecaresnet101d_pruned	80.818	19.182	95.628	4.372	24.88	224	0.875	bicubic
67	regnety_320	80.812	19.188	95.244	4.756	145.05	224	0.875	bicubic
68	tresnet_m	80.802	19.198	94.860	5.140	31.39	224	0.875	bilinear
69	efficientnet_b2a	80.612	19.388	95.318	4.682	9.11	288	1.000	bicubic
70	gluon_resnext101_64x4d	80.604	19.396	94.988	5.012	83.46	224	0.875	bicubic
71	ecaresnet50d	80.592	19.408	95.320	4.680	25.58	224	0.875	bicubic
72	resnet50d	80.530	19.470	95.160	4.840	25.58	224	0.875	bicubic
73	mixnet_xl	80.476	19.524	94.936	5.064	11.90	224	0.875	bicubic
74	gluon_resnet152_v1d	80.474	19.526	95.206	4.794	60.21	224	0.875	bicubic
75	ecaresnetlight	80.462	19.538	95.248	4.752	30.16	224	0.875	bicubic
76	inception_resnet_v2	80.458	19.542	95.306	4.694	55.84	299	0.897	bicubic
77	tf_efficientnet_el	80.440	19.560	95.164	4.836	10.59	300	0.904	bicubic
78	gluon_resnet101_v1d	80.414	19.586	95.014	4.986	44.57	224	0.875	bicubic
79	efficientnet_b2	80.392	19.608	95.076	4.924	9.11	260	0.875	bicubic
80	regnety_120	80.366	19.634	95.126	4.874	51.82	224	0.875	bicubic
81	gluon_resnext101_32x4d	80.334	19.666	94.926	5.074	44.18	224	0.875	bicubic
82	ssl_resnext50_32x4d	80.318	19.682	95.406	4.594	25.03	224	0.875	bilinear
83	rexnet_150	80.310	19.690	95.166	4.834	9.73	224	0.875	bicubic
84	gluon_resnet101_v1s	80.302	19.698	95.160	4.840	44.67	224	0.875	bicubic
85	tf_efficientnet_b2_ap	80.300	19.700	95.028	4.972	9.11	260	0.890	bicubic
86	regnety_160	80.296	19.704	94.962	5.038	83.59	224	0.875	bicubic
87	seresnet50	80.274	19.726	95.070	4.930	28.09	224	0.875	bicubic
88	regnetx_320	80.246	19.754	95.026	4.974	107.81	224	0.875	bicubic
89	legacy_seresnext101_32x4d	80.228	19.772	95.018	4.982	48.96	224	0.875	bilinear
90	inception_v4	80.168	19.832	94.968	5.032	42.68	299	0.875	bicubic
91	dpn107	80.156	19.844	94.910	5.090	86.92	224	0.875	bicubic
92	skresnext50_32x4d	80.156	19.844	94.642	5.358	27.48	224	0.875	bicubic
93	tf_efficientnet_b2	80.086	19.914	94.908	5.092	9.11	260	0.890	bicubic
94	cspdarknet53	80.058	19.942	95.084	4.916	27.64	256	0.887	bilinear
95	cspresnext50	80.040	19.960	94.944	5.056	20.57	224	0.875	bilinear
96	dpn92	80.008	19.992	94.836	5.164	37.67	224	0.875	bicubic
97	ens_adv_inception_resnet_v2	79.982	20.018	94.936	5.064	55.84	299	0.897	bicubic
98	gluon_seresnext50_32x4d	79.918	20.082	94.822	5.178	27.56	224	0.875	bicubic
99	efficientnet_b2_pruned	79.916	20.084	94.856	5.144	8.31	260	0.890	bicubic
100	gluon_resnet152_v1c	79.910	20.090	94.840	5.160	60.21	224	0.875	bicubic
101	regnety_080	79.876	20.124	94.830	5.170	39.18	224	0.875	bicubic
102	xception71	79.874	20.126	94.922	5.078	42.34	299	0.903	bicubic
103	regnetx_160	79.856	20.144	94.830	5.170	54.28	224	0.875	bicubic
104	dpn131	79.822	20.178	94.710	5.290	79.25	224	0.875	bicubic
105	tf_efficientnet_lite3	79.820	20.180	94.914	5.086	8.20	300	0.904	bilinear
106	resnext50_32x4d	79.768	20.232	94.598	5.402	25.03	224	0.875	bicubic
107	regnety_064	79.722	20.278	94.768	5.232	30.58	224	0.875	bicubic
108	ecaresnet50d_pruned	79.716	20.284	94.880	5.120	19.94	224	0.875	bicubic
109	gluon_xception65	79.716	20.284	94.860	5.140	39.92	299	0.903	bicubic
110	gluon_resnet152_v1b	79.686	20.314	94.736	5.264	60.19	224	0.875	bicubic
111	resnext50d_32x4d	79.676	20.324	94.866	5.134	25.05	224	0.875	bicubic
112	dpn98	79.642	20.358	94.598	5.402	61.57	224	0.875	bicubic
113	regnetx_120	79.596	20.404	94.738	5.262	46.11	224	0.875	bicubic
114	cspresnet50	79.574	20.426	94.712	5.288	21.62	256	0.887	bilinear
115	xception65	79.552	20.448	94.654	5.346	39.92	299	0.903	bicubic
116	gluon_resnet101_v1c	79.534	20.466	94.578	5.422	44.57	224	0.875	bicubic
117	rexnet_130	79.500	20.500	94.682	5.318	7.56	224	0.875	bicubic
118	hrnet_w64	79.474	20.526	94.652	5.348	128.06	224	0.875	bilinear
119	dla102x2	79.448	20.552	94.640	5.360	41.28	224	0.875	bilinear
120	gluon_resnext50_32x4d	79.354	20.646	94.426	5.574	25.03	224	0.875	bicubic
121	vit_base_patch16_224	79.348	20.652	94.512	5.488	86.54	224	0.900	bicubic
122	ese_vovnet39b	79.320	20.680	94.712	5.288	24.57	224	0.875	bicubic
123	resnext101_32x8d	79.308	20.692	94.518	5.482	88.79	224	0.875	bilinear
124	tf_efficientnet_cc_b1_8e	79.308	20.692	94.370	5.630	39.72	240	0.882	bicubic
125	gluon_resnet101_v1b	79.306	20.694	94.524	5.476	44.55	224	0.875	bicubic
126	hrnet_w48	79.300	20.700	94.512	5.488	77.47	224	0.875	bilinear
127	resnetblur50	79.286	20.714	94.638	5.362	25.56	224	0.875	bicubic
128	tf_efficientnet_b1_ap	79.280	20.720	94.306	5.694	7.79	240	0.882	bicubic
129	efficientnet_em	79.252	20.748	94.794	5.206	6.90	240	0.882	bicubic
130	ssl_resnet50	79.222	20.778	94.832	5.168	25.56	224	0.875	bilinear
131	regnety_040	79.220	20.780	94.656	5.344	20.65	224	0.875	bicubic
132	dpn68b	79.216	20.784	94.414	5.586	12.61	224	0.875	bicubic
133	res2net101_26w_4s	79.198	20.802	94.432	5.568	45.21	224	0.875	bilinear
134	res2net50_26w_8s	79.198	20.802	94.368	5.632	48.40	224	0.875	bilinear
135	regnetx_080	79.194	20.806	94.560	5.440	39.57	224	0.875	bicubic
136	legacy_seresnext50_32x4d	79.078	20.922	94.436	5.564	27.56	224	0.875	bilinear
137	gluon_resnet50_v1d	79.074	20.926	94.470	5.530	25.58	224	0.875	bicubic
138	regnetx_064	79.072	20.928	94.458	5.542	26.21	224	0.875	bicubic
139	xception	79.052	20.948	94.392	5.608	22.86	299	0.897	bicubic
140	resnet50	79.038	20.962	94.390	5.610	25.56	224	0.875	bicubic
141	mixnet_l	78.976	21.024	94.182	5.818	7.33	224	0.875	bicubic
142	hrnet_w40	78.920	21.080	94.470	5.530	57.56	224	0.875	bilinear
143	hrnet_w44	78.896	21.104	94.368	5.632	67.06	224	0.875	bilinear
144	wide_resnet101_2	78.856	21.144	94.282	5.718	126.89	224	0.875	bilinear
145	tf_efficientnet_b1	78.826	21.174	94.198	5.802	7.79	240	0.882	bicubic
146	gluon_inception_v3	78.806	21.194	94.370	5.630	23.83	299	0.875	bicubic
147	tf_mixnet_l	78.774	21.226	93.998	6.002	7.33	224	0.875	bicubic
148	gluon_resnet50_v1s	78.710	21.290	94.238	5.762	25.68	224	0.875	bicubic
149	tf_efficientnet_em	78.708	21.292	94.314	5.686	6.90	240	0.882	bicubic
150	efficientnet_b1	78.698	21.302	94.144	5.856	7.79	240	0.875	bicubic
151	dla169	78.688	21.312	94.336	5.664	53.39	224	0.875	bilinear
152	legacy_seresnet152	78.660	21.340	94.370	5.630	66.82	224	0.875	bilinear
153	tf_efficientnet_b0_ns	78.658	21.342	94.376	5.624	5.29	224	0.875	bicubic
154	res2net50_26w_6s	78.570	21.430	94.124	5.876	37.05	224	0.875	bilinear
155	xception41	78.516	21.484	94.278	5.722	26.97	299	0.903	bicubic
156	dla102x	78.510	21.490	94.228	5.772	26.31	224	0.875	bilinear
157	regnetx_040	78.482	21.518	94.244	5.756	22.12	224	0.875	bicubic
158	resnest26d	78.478	21.522	94.298	5.702	17.07	224	0.875	bilinear
159	dla60_res2net	78.464	21.536	94.206	5.794	20.85	224	0.875	bilinear
160	hrnet_w32	78.450	21.550	94.186	5.814	41.23	224	0.875	bilinear
161	dla60_res2next	78.440	21.560	94.152	5.848	17.03	224	0.875	bilinear
162	selecsls60b	78.412	21.588	94.174	5.826	32.77	224	0.875	bicubic
163	legacy_seresnet101	78.382	21.618	94.264	5.736	49.33	224	0.875	bilinear
164	tv_resnet152	78.312	21.688	94.038	5.962	60.19	224	0.875	bilinear
165	dla60x	78.246	21.754	94.018	5.982	17.35	224	0.875	bilinear
166	res2next50	78.246	21.754	93.892	6.108	24.67	224	0.875	bilinear
167	efficientnet_b1_pruned	78.236	21.764	93.834	6.166	6.33	240	0.882	bicubic
168	hrnet_w30	78.206	21.794	94.222	5.778	37.71	224	0.875	bilinear
169	regnetx_032	78.172	21.828	94.088	5.912	15.30	224	0.875	bicubic
170	res2net50_14w_8s	78.150	21.850	93.848	6.152	25.06	224	0.875	bilinear
171	efficientnet_es	78.066	21.934	93.926	6.074	5.44	224	0.875	bicubic
172	dla102	78.032	21.968	93.946	6.054	33.27	224	0.875	bilinear
173	gluon_resnet50_v1c	78.012	21.988	93.988	6.012	25.58	224	0.875	bicubic
174	seresnext26t_32x4d	77.998	22.002	93.708	6.292	16.82	224	0.875	bicubic
175	seresnext26tn_32x4d	77.986	22.014	93.746	6.254	16.81	224	0.875	bicubic
176	selecsls60	77.982	22.018	93.828	6.172	30.67	224	0.875	bicubic
177	res2net50_26w_4s	77.964	22.036	93.854	6.146	25.70	224	0.875	bilinear
178	tf_efficientnet_cc_b0_8e	77.908	22.092	93.654	6.346	24.01	224	0.875	bicubic
179	regnety_016	77.862	22.138	93.720	6.280	11.20	224	0.875	bicubic
180	tf_inception_v3	77.862	22.138	93.640	6.360	23.83	299	0.875	bicubic
181	rexnet_100	77.858	22.142	93.870	6.130	4.80	224	0.875	bicubic
182	vit_small_patch16_224	77.858	22.142	93.416	6.584	48.75	224	0.900	bicubic
183	efficientnet_b0	77.698	22.302	93.532	6.468	5.29	224	0.875	bicubic
184	legacy_seresnet50	77.630	22.370	93.748	6.252	28.09	224	0.875	bilinear
185	tv_resnext50_32x4d	77.620	22.380	93.696	6.304	25.03	224	0.875	bilinear
186	seresnext26d_32x4d	77.602	22.398	93.608	6.392	16.81	224	0.875	bicubic
187	adv_inception_v3	77.582	22.418	93.736	6.264	23.83	299	0.875	bicubic
188	gluon_resnet50_v1b	77.580	22.420	93.716	6.284	25.56	224	0.875	bicubic
189	res2net50_48w_2s	77.522	22.478	93.554	6.446	25.29	224	0.875	bilinear
190	tf_efficientnet_lite2	77.468	22.532	93.754	6.246	6.09	260	0.890	bicubic
191	inception_v3	77.438	22.562	93.476	6.524	23.83	299	0.875	bicubic
192	tv_resnet101	77.374	22.626	93.540	6.460	44.55	224	0.875	bilinear
193	densenet161	77.358	22.642	93.638	6.362	28.68	224	0.875	bicubic
194	tf_efficientnet_cc_b0_4e	77.306	22.694	93.334	6.666	13.31	224	0.875	bicubic
195	densenet201	77.286	22.714	93.478	6.522	20.01	224	0.875	bicubic
196	mobilenetv2_120d	77.284	22.716	93.492	6.508	5.83	224	0.875	bicubic
197	mixnet_m	77.260	22.740	93.424	6.576	5.01	224	0.875	bicubic
198	tf_efficientnet_es	77.258	22.742	93.594	6.406	5.44	224	0.875	bicubic
199	selecsls42b	77.174	22.826	93.390	6.610	32.46	224	0.875	bicubic
200	resnet34d	77.116	22.884	93.382	6.618	21.82	224	0.875	bicubic
201	legacy_seresnext26_32x4d	77.104	22.896	93.316	6.684	16.79	224	0.875	bicubic
202	tf_efficientnet_b0_ap	77.086	22.914	93.256	6.744	5.29	224	0.875	bicubic
203	dla60	77.032	22.968	93.318	6.682	22.04	224	0.875	bilinear
204	regnetx_016	76.950	23.050	93.420	6.580	9.19	224	0.875	bicubic
205	tf_mixnet_m	76.942	23.058	93.152	6.848	5.01	224	0.875	bicubic
206	skresnet34	76.912	23.088	93.322	6.678	22.28	224	0.875	bicubic
207	tf_efficientnet_b0	76.848	23.152	93.228	6.772	5.29	224	0.875	bicubic
208	ese_vovnet19b_dw	76.798	23.202	93.268	6.732	6.54	224	0.875	bicubic
209	hrnet_w18	76.758	23.242	93.444	6.556	21.30	224	0.875	bilinear
210	resnet26d	76.696	23.304	93.150	6.850	16.01	224	0.875	bicubic
211	tf_efficientnet_lite1	76.642	23.358	93.226	6.774	5.42	240	0.882	bicubic
212	densenetblur121d	76.588	23.412	93.192	6.808	8.00	224	0.875	bicubic
213	mobilenetv2_140	76.516	23.484	92.996	7.004	6.11	224	0.875	bicubic
214	dpn68	76.318	23.682	92.978	7.022	12.61	224	0.875	bicubic
215	regnety_008	76.316	23.684	93.066	6.934	6.26	224	0.875	bicubic
216	tv_resnet50	76.138	23.862	92.864	7.136	25.56	224	0.875	bilinear
217	mixnet_s	75.992	24.008	92.796	7.204	4.13	224	0.875	bicubic
218	densenet169	75.906	24.094	93.026	6.974	14.15	224	0.875	bicubic
219	mobilenetv3_large_100	75.766	24.234	92.542	7.458	5.48	224	0.875	bicubic
220	tf_mixnet_s	75.650	24.350	92.630	7.370	4.13	224	0.875	bicubic
221	mobilenetv3_rw	75.634	24.366	92.708	7.292	5.48	224	0.875	bicubic
222	densenet121	75.578	24.422	92.652	7.348	7.98	224	0.875	bicubic
223	tf_mobilenetv3_large_100	75.518	24.482	92.606	7.394	5.48	224	0.875	bilinear
224	resnest14d	75.504	24.496	92.518	7.482	10.61	224	0.875	bilinear
225	efficientnet_lite0	75.484	24.516	92.510	7.490	4.65	224	0.875	bicubic
226	semnasnet_100	75.448	24.552	92.604	7.396	3.89	224	0.875	bicubic
227	resnet26	75.292	24.708	92.570	7.430	16.00	224	0.875	bicubic
228	regnety_006	75.246	24.754	92.532	7.468	6.06	224	0.875	bicubic
229	fbnetc_100	75.124	24.876	92.386	7.614	5.57	224	0.875	bilinear
230	hrnet_w18_small_v2	75.114	24.886	92.416	7.584	15.60	224	0.875	bilinear
231	resnet34	75.110	24.890	92.284	7.716	21.80	224	0.875	bilinear
232	regnetx_008	75.038	24.962	92.336	7.664	7.26	224	0.875	bicubic
233	mobilenetv2_110d	75.036	24.964	92.186	7.814	4.52	224	0.875	bicubic
234	tf_efficientnet_lite0	74.830	25.170	92.176	7.824	4.65	224	0.875	bicubic
235	legacy_seresnet34	74.808	25.192	92.124	7.876	21.96	224	0.875	bilinear
236	tv_densenet121	74.738	25.262	92.150	7.850	7.98	224	0.875	bicubic
237	mnasnet_100	74.658	25.342	92.114	7.886	4.38	224	0.875	bicubic
238	dla34	74.630	25.370	92.078	7.922	15.74	224	0.875	bilinear
239	gluon_resnet34_v1b	74.588	25.412	91.990	8.010	21.80	224	0.875	bicubic
240	spnasnet_100	74.084	25.916	91.818	8.182	4.42	224	0.875	bilinear
241	regnety_004	74.034	25.966	91.752	8.248	4.34	224	0.875	bicubic
242	regnetx_006	73.852	26.148	91.672	8.328	6.20	224	0.875	bicubic
243	tf_mobilenetv3_large_075	73.438	26.562	91.350	8.650	3.99	224	0.875	bilinear
244	tv_resnet34	73.312	26.688	91.426	8.574	21.80	224	0.875	bilinear
245	swsl_resnet18	73.276	26.724	91.734	8.266	11.69	224	0.875	bilinear
246	skresnet18	73.038	26.962	91.168	8.832	11.96	224	0.875	bicubic
247	mobilenetv2_100	72.970	27.030	91.016	8.984	3.50	224	0.875	bicubic
248	ssl_resnet18	72.610	27.390	91.416	8.584	11.69	224	0.875	bilinear
249	regnetx_004	72.396	27.604	90.830	9.170	5.16	224	0.875	bicubic
250	hrnet_w18_small	72.342	27.658	90.678	9.322	13.19	224	0.875	bilinear
251	resnet18d	72.260	27.740	90.696	9.304	11.71	224	0.875	bicubic
252	tf_mobilenetv3_large_minimal_100	72.248	27.752	90.630	9.370	3.92	224	0.875	bilinear
253	legacy_seresnet18	71.742	28.258	90.334	9.666	11.78	224	0.875	bicubic
254	gluon_resnet18_v1b	70.836	29.164	89.762	10.238	11.69	224	0.875	bicubic
255	regnety_002	70.252	29.748	89.540	10.460	3.16	224	0.875	bicubic
256	resnet18	69.748	30.252	89.078	10.922	11.69	224	0.875	bilinear
257	regnetx_002	68.762	31.238	88.556	11.444	2.68	224	0.875	bicubic
258	tf_mobilenetv3_small_100	67.922	32.078	87.664	12.336	2.54	224	0.875	bilinear
259	dla60x_c	67.892	32.108	88.426	11.574	1.32	224	0.875	bilinear
260	dla46x_c	65.970	34.030	86.980	13.020	1.07	224	0.875	bilinear
261	tf_mobilenetv3_small_075	65.716	34.284	86.130	13.870	2.04	224	0.875	bilinear
262	dla46_c	64.866	35.134	86.292	13.708	1.30	224	0.875	bilinear
263	tf_mobilenetv3_small_minimal_100	62.906	37.094	84.230	15.770	2.04	224	0.875	bilinear