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

1	model	top1	top1_err	top5	top5_err	param_count	img_size	cropt_pct	interpolation
2	ig_resnext101_32x48d	85.428	14.572	97.572	2.428	828.41	224	0.875	bilinear
3	tf_efficientnet_b8	85.37	14.63	97.39	2.61	87.41	672	0.954	bicubic
4	tf_efficientnet_b8_ap	85.37	14.63	97.294	2.706	87.41	672	0.954	bicubic
5	tf_efficientnet_b7_ap	85.12	14.88	97.252	2.748	66.35	600	0.949	bicubic
6	ig_resnext101_32x32d	85.094	14.906	97.438	2.562	468.53	224	0.875	bilinear
7	tf_efficientnet_b7	84.936	15.064	97.204	2.796	66.35	600	0.949	bicubic
8	tf_efficientnet_b6_ap	84.788	15.212	97.138	2.862	43.04	528	0.942	bicubic
9	swsl_resnext101_32x8d	84.284	15.716	97.176	2.824	88.79	224	0.875	bilinear
10	tf_efficientnet_b5_ap	84.252	15.748	96.974	3.026	30.39	456	0.934	bicubic
11	ig_resnext101_32x16d	84.17	15.83	97.196	2.804	194.03	224	0.875	bilinear
12	tf_efficientnet_b6	84.11	15.89	96.886	3.114	43.04	528	0.942	bicubic
13	tf_efficientnet_b5	83.812	16.188	96.748	3.252	30.39	456	0.934	bicubic
14	swsl_resnext101_32x16d	83.346	16.654	96.846	3.154	194.03	224	0.875	bilinear
15	tf_efficientnet_b4_ap	83.248	16.752	96.392	3.608	19.34	380	0.922	bicubic
16	swsl_resnext101_32x4d	83.23	16.77	96.76	3.24	44.18	224	0.875	bilinear
17	tf_efficientnet_b4	83.022	16.978	96.3	3.7	19.34	380	0.922	bicubic
18	pnasnet5large	82.736	17.264	96.046	3.954	86.06	331	0.875	bicubic
19	ig_resnext101_32x8d	82.688	17.312	96.636	3.364	88.79	224	0.875	bilinear
20	nasnetalarge	82.554	17.446	96.038	3.962	88.75	331	0.875	bicubic
21	swsl_resnext50_32x4d	82.182	17.818	96.23	3.77	25.03	224	0.875	bilinear
22	efficientnet_b3a	81.866	18.134	95.836	4.164	12.23	320	1	bicubic
23	ssl_resnext101_32x16d	81.844	18.156	96.096	3.904	194.03	224	0.875	bilinear
24	tf_efficientnet_b3_ap	81.822	18.178	95.624	4.376	12.23	300	0.904	bicubic
25	tf_efficientnet_b3	81.636	18.364	95.718	4.282	12.23	300	0.904	bicubic
26	ssl_resnext101_32x8d	81.616	18.384	96.038	3.962	88.79	224	0.875	bilinear
27	efficientnet_b3	81.494	18.506	95.716	4.284	12.23	300	0.904	bicubic
28	senet154	81.31	18.69	95.496	4.504	115.09	224	0.875	bilinear
29	gluon_senet154	81.234	18.766	95.348	4.652	115.09	224	0.875	bicubic
30	swsl_resnet50	81.166	18.834	95.972	4.028	25.56	224	0.875	bilinear
31	gluon_resnet152_v1s	81.016	18.984	95.412	4.588	60.32	224	0.875	bicubic
32	ssl_resnext101_32x4d	80.924	19.076	95.728	4.272	44.18	224	0.875	bilinear
33	gluon_seresnext101_32x4d	80.904	19.096	95.294	4.706	48.96	224	0.875	bicubic
34	gluon_seresnext101_64x4d	80.894	19.106	95.308	4.692	88.23	224	0.875	bicubic
35	efficientnet_b2a	80.612	19.388	95.318	4.682	9.11	288	1	bicubic
36	gluon_resnext101_64x4d	80.604	19.396	94.988	5.012	83.46	224	0.875	bicubic
37	mixnet_xl	80.476	19.524	94.936	5.064	11.9	224	0.875	bicubic
38	gluon_resnet152_v1d	80.474	19.526	95.206	4.794	60.21	224	0.875	bicubic
39	inception_resnet_v2	80.458	19.542	95.306	4.694	55.84	299	0.8975	bicubic
40	tf_efficientnet_el	80.44	19.56	95.164	4.836	10.59	300	0.904	bicubic
41	gluon_resnet101_v1d	80.414	19.586	95.014	4.986	44.57	224	0.875	bicubic
42	efficientnet_b2	80.392	19.608	95.076	4.924	9.11	260	0.875	bicubic
43	gluon_resnext101_32x4d	80.334	19.666	94.926	5.074	44.18	224	0.875	bicubic
44	ssl_resnext50_32x4d	80.318	19.682	95.406	4.594	25.03	224	0.875	bilinear
45	gluon_resnet101_v1s	80.302	19.698	95.16	4.84	44.67	224	0.875	bicubic
46	tf_efficientnet_b2_ap	80.3	19.7	95.028	4.972	9.11	260	0.89	bicubic
47	seresnext101_32x4d	80.228	19.772	95.018	4.982	48.96	224	0.875	bilinear
48	inception_v4	80.168	19.832	94.968	5.032	42.68	299	0.875	bicubic
49	dpn107	80.156	19.844	94.91	5.09	86.92	224	0.875	bicubic
50	tf_efficientnet_b2	80.086	19.914	94.908	5.092	9.11	260	0.89	bicubic
51	dpn92	80.008	19.992	94.836	5.164	37.67	224	0.875	bicubic
52	ens_adv_inception_resnet_v2	79.982	20.018	94.938	5.062	55.84	299	0.8975	bicubic
53	gluon_seresnext50_32x4d	79.918	20.082	94.822	5.178	27.56	224	0.875	bicubic
54	gluon_resnet152_v1c	79.91	20.09	94.84	5.16	60.21	224	0.875	bicubic
55	dpn131	79.822	20.178	94.71	5.29	79.25	224	0.875	bicubic
56	gluon_resnet152_v1b	79.686	20.314	94.736	5.264	60.19	224	0.875	bicubic
57	resnext50d_32x4d	79.676	20.324	94.866	5.134	25.05	224	0.875	bicubic
58	dpn98	79.642	20.358	94.598	5.402	61.57	224	0.875	bicubic
59	gluon_xception65	79.588	20.412	94.756	5.244	39.92	299	0.875	bicubic
60	gluon_resnet101_v1c	79.534	20.466	94.578	5.422	44.57	224	0.875	bicubic
61	hrnet_w64	79.474	20.526	94.652	5.348	128.06	224	0.875	bilinear
62	dla102x2	79.448	20.552	94.64	5.36	41.75	224	0.875	bilinear
63	gluon_resnext50_32x4d	79.354	20.646	94.426	5.574	25.03	224	0.875	bicubic
64	resnext101_32x8d	79.308	20.692	94.518	5.482	88.79	224	0.875	bilinear
65	tf_efficientnet_cc_b1_8e	79.308	20.692	94.37	5.63	39.72	240	0.882	bicubic
66	gluon_resnet101_v1b	79.306	20.694	94.524	5.476	44.55	224	0.875	bicubic
67	hrnet_w48	79.3	20.7	94.512	5.488	77.47	224	0.875	bilinear
68	tf_efficientnet_b1_ap	79.28	20.72	94.306	5.694	7.79	240	0.882	bicubic
69	ssl_resnet50	79.222	20.778	94.832	5.168	25.56	224	0.875	bilinear
70	res2net50_26w_8s	79.198	20.802	94.368	5.632	48.4	224	0.875	bilinear
71	res2net101_26w_4s	79.198	20.802	94.432	5.568	45.21	224	0.875	bilinear
72	seresnext50_32x4d	79.078	20.922	94.436	5.564	27.56	224	0.875	bilinear
73	gluon_resnet50_v1d	79.074	20.926	94.47	5.53	25.58	224	0.875	bicubic
74	xception	79.052	20.948	94.392	5.608	22.86	299	0.8975	bicubic
75	resnet50	79.038	20.962	94.39	5.61	25.56	224	0.875	bicubic
76	mixnet_l	78.976	21.024	94.182	5.818	7.33	224	0.875	bicubic
77	hrnet_w40	78.92	21.08	94.47	5.53	57.56	224	0.875	bilinear
78	hrnet_w44	78.896	21.104	94.368	5.632	67.06	224	0.875	bilinear
79	wide_resnet101_2	78.856	21.144	94.282	5.718	126.89	224	0.875	bilinear
80	tf_efficientnet_b1	78.826	21.174	94.198	5.802	7.79	240	0.882	bicubic
81	gluon_inception_v3	78.806	21.194	94.37	5.63	23.83	299	0.875	bicubic
82	tf_mixnet_l	78.774	21.226	93.998	6.002	7.33	224	0.875	bicubic
83	gluon_resnet50_v1s	78.712	21.288	94.238	5.762	25.68	224	0.875	bicubic
84	tf_efficientnet_em	78.708	21.292	94.314	5.686	6.9	240	0.882	bicubic
85	efficientnet_b1	78.698	21.302	94.144	5.856	7.79	240	0.875	bicubic
86	dla169	78.688	21.312	94.336	5.664	53.99	224	0.875	bilinear
87	seresnet152	78.66	21.34	94.37	5.63	66.82	224	0.875	bilinear
88	res2net50_26w_6s	78.57	21.43	94.124	5.876	37.05	224	0.875	bilinear
89	resnext50_32x4d	78.512	21.488	94.042	5.958	25.03	224	0.875	bicubic
90	dla102x	78.51	21.49	94.228	5.772	26.77	224	0.875	bilinear
91	wide_resnet50_2	78.478	21.522	94.094	5.906	68.88	224	0.875	bilinear
92	dla60_res2net	78.464	21.536	94.206	5.794	21.15	224	0.875	bilinear
93	hrnet_w32	78.45	21.55	94.186	5.814	41.23	224	0.875	bilinear
94	dla60_res2next	78.44	21.56	94.152	5.848	17.33	224	0.875	bilinear
95	selecsls60b	78.412	21.588	94.174	5.826	32.77	224	0.875	bicubic
96	seresnet101	78.382	21.618	94.264	5.736	49.33	224	0.875	bilinear
97	resnet152	78.312	21.688	94.038	5.962	60.19	224	0.875	bilinear
98	dla60x	78.246	21.754	94.018	5.982	17.65	224	0.875	bilinear
99	res2next50	78.246	21.754	93.892	6.108	24.67	224	0.875	bilinear
100	hrnet_w30	78.206	21.794	94.222	5.778	37.71	224	0.875	bilinear
101	res2net50_14w_8s	78.15	21.85	93.848	6.152	25.06	224	0.875	bilinear
102	dla102	78.032	21.968	93.946	6.054	33.73	224	0.875	bilinear
103	gluon_resnet50_v1c	78.012	21.988	93.988	6.012	25.58	224	0.875	bicubic
104	seresnext26t_32x4d	77.998	22.002	93.708	6.292	16.82	224	0.875	bicubic
105	seresnext26tn_32x4d	77.986	22.014	93.746	6.254	16.81	224	0.875	bicubic
106	selecsls60	77.982	22.018	93.828	6.172	30.67	224	0.875	bicubic
107	res2net50_26w_4s	77.964	22.036	93.854	6.146	25.7	224	0.875	bilinear
108	tf_efficientnet_cc_b0_8e	77.908	22.092	93.654	6.346	24.01	224	0.875	bicubic
109	tf_inception_v3	77.86	22.14	93.64	6.36	23.83	299	0.875	bicubic
110	efficientnet_b0	77.698	22.302	93.532	6.468	5.29	224	0.875	bicubic
111	seresnet50	77.63	22.37	93.748	6.252	28.09	224	0.875	bilinear
112	tv_resnext50_32x4d	77.62	22.38	93.696	6.304	25.03	224	0.875	bilinear
113	seresnext26d_32x4d	77.602	22.398	93.608	6.392	16.81	224	0.875	bicubic
114	adv_inception_v3	77.582	22.418	93.736	6.264	23.83	299	0.875	bicubic
115	gluon_resnet50_v1b	77.58	22.42	93.716	6.284	25.56	224	0.875	bicubic
116	res2net50_48w_2s	77.522	22.478	93.554	6.446	25.29	224	0.875	bilinear
117	dpn68b	77.512	22.488	93.822	6.178	12.61	224	0.875	bicubic
118	inception_v3	77.438	22.562	93.474	6.526	27.16	299	0.875	bicubic
119	resnet101	77.374	22.626	93.54	6.46	44.55	224	0.875	bilinear
120	densenet161	77.358	22.642	93.638	6.362	28.68	224	0.875	bicubic
121	tf_efficientnet_cc_b0_4e	77.306	22.694	93.334	6.666	13.31	224	0.875	bicubic
122	densenet201	77.286	22.714	93.478	6.522	20.01	224	0.875	bicubic
123	mixnet_m	77.26	22.74	93.424	6.576	5.01	224	0.875	bicubic
124	tf_efficientnet_es	77.258	22.742	93.594	6.406	5.44	224	0.875	bicubic
125	selecsls42b	77.174	22.826	93.39	6.61	32.46	224	0.875	bicubic
126	seresnext26_32x4d	77.104	22.896	93.316	6.684	16.79	224	0.875	bicubic
127	tf_efficientnet_b0_ap	77.086	22.914	93.256	6.744	5.29	224	0.875	bicubic
128	dla60	77.032	22.968	93.318	6.682	22.33	224	0.875	bilinear
129	tf_mixnet_m	76.942	23.058	93.152	6.848	5.01	224	0.875	bicubic
130	tf_efficientnet_b0	76.848	23.152	93.228	6.772	5.29	224	0.875	bicubic
131	hrnet_w18	76.758	23.242	93.444	6.556	21.3	224	0.875	bilinear
132	resnet26d	76.696	23.304	93.15	6.85	16.01	224	0.875	bicubic
133	dpn68	76.318	23.682	92.978	7.022	12.61	224	0.875	bicubic
134	tv_resnet50	76.138	23.862	92.864	7.136	25.56	224	0.875	bilinear
135	mixnet_s	75.992	24.008	92.796	7.204	4.13	224	0.875	bicubic
136	densenet169	75.906	24.094	93.026	6.974	14.15	224	0.875	bicubic
137	tf_mixnet_s	75.65	24.35	92.63	7.37	4.13	224	0.875	bicubic
138	mobilenetv3_rw	75.634	24.366	92.708	7.292	5.48	224	0.875	bicubic
139	tf_mobilenetv3_large_100	75.518	24.482	92.606	7.394	5.48	224	0.875	bilinear
140	semnasnet_100	75.448	24.552	92.604	7.396	3.89	224	0.875	bicubic
141	resnet26	75.292	24.708	92.57	7.43	16	224	0.875	bicubic
142	fbnetc_100	75.124	24.876	92.386	7.614	5.57	224	0.875	bilinear
143	hrnet_w18_small_v2	75.114	24.886	92.416	7.584	15.6	224	0.875	bilinear
144	resnet34	75.11	24.89	92.284	7.716	21.8	224	0.875	bilinear
145	seresnet34	74.808	25.192	92.124	7.876	21.96	224	0.875	bilinear
146	densenet121	74.738	25.262	92.15	7.85	7.98	224	0.875	bicubic
147	mnasnet_100	74.658	25.342	92.114	7.886	4.38	224	0.875	bicubic
148	dla34	74.63	25.37	92.078	7.922	15.78	224	0.875	bilinear
149	gluon_resnet34_v1b	74.588	25.412	91.99	8.01	21.8	224	0.875	bicubic
150	spnasnet_100	74.084	25.916	91.818	8.182	4.42	224	0.875	bilinear
151	tf_mobilenetv3_large_075	73.438	26.562	91.35	8.65	3.99	224	0.875	bilinear
152	tv_resnet34	73.312	26.688	91.426	8.574	21.8	224	0.875	bilinear
153	swsl_resnet18	73.276	26.724	91.734	8.266	11.69	224	0.875	bilinear
154	ssl_resnet18	72.61	27.39	91.416	8.584	11.69	224	0.875	bilinear
155	hrnet_w18_small	72.342	27.658	90.678	9.322	13.19	224	0.875	bilinear
156	tf_mobilenetv3_large_minimal_100	72.248	27.752	90.63	9.37	3.92	224	0.875	bilinear
157	seresnet18	71.742	28.258	90.334	9.666	11.78	224	0.875	bicubic
158	gluon_resnet18_v1b	70.836	29.164	89.76	10.24	11.69	224	0.875	bicubic
159	resnet18	69.748	30.252	89.078	10.922	11.69	224	0.875	bilinear
160	tf_mobilenetv3_small_100	67.922	32.078	87.664	12.336	2.54	224	0.875	bilinear
161	dla60x_c	67.892	32.108	88.426	11.574	1.34	224	0.875	bilinear
162	dla46x_c	65.97	34.03	86.98	13.02	1.08	224	0.875	bilinear
163	tf_mobilenetv3_small_075	65.716	34.284	86.13	13.87	2.04	224	0.875	bilinear
164	dla46_c	64.866	35.134	86.292	13.708	1.31	224	0.875	bilinear
165	tf_mobilenetv3_small_minimal_100	62.906	37.094	84.23	15.77	2.04	224	0.875	bilinear