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	98.648	1.352	480.31	800	0.96	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	86.838	13.162	98.094	1.906	66.35	600	0.949	bicubic
5	tf_efficientnet_b6_ns	86.462	13.538	97.884	2.116	43.04	528	0.942	bicubic
6	tf_efficientnet_b5_ns	86.08	13.92	97.754	2.246	30.39	456	0.934	bicubic
7	ig_resnext101_32x48d	85.442	14.558	97.572	2.428	828.41	224	0.875	bilinear
8	tf_efficientnet_b8	85.37	14.63	97.392	2.608	87.41	672	0.954	bicubic
9	tf_efficientnet_b8_ap	85.368	14.632	97.294	2.706	87.41	672	0.954	bicubic
10	tf_efficientnet_b4_ns	85.158	14.842	97.468	2.532	19.34	380	0.922	bicubic
11	tf_efficientnet_b7_ap	85.118	14.882	97.252	2.748	66.35	600	0.949	bicubic
12	ig_resnext101_32x32d	85.092	14.908	97.436	2.564	468.53	224	0.875	bilinear
13	tf_efficientnet_b7	84.932	15.068	97.208	2.792	66.35	600	0.949	bicubic
14	tf_efficientnet_b6_ap	84.786	15.214	97.138	2.862	43.04	528	0.942	bicubic
15	swsl_resnext101_32x8d	84.294	15.706	97.174	2.826	88.79	224	0.875	bilinear
16	tf_efficientnet_b5_ap	84.254	15.746	96.976	3.024	30.39	456	0.934	bicubic
17	resnest269e	84.186	15.814	96.922	3.078	110.93	416	0.875	bilinear
18	ig_resnext101_32x16d	84.176	15.824	97.196	2.804	194.03	224	0.875	bilinear
19	tf_efficientnet_b6	84.112	15.888	96.884	3.116	43.04	528	0.942	bicubic
20	tf_efficientnet_b3_ns	84.054	15.946	96.912	3.088	12.23	300	0.904	bicubic
21	resnest200e	83.834	16.166	96.838	3.162	70.2	320	0.875	bilinear
22	tf_efficientnet_b5	83.816	16.184	96.75	3.25	30.39	456	0.934	bicubic
23	swsl_resnext101_32x16d	83.338	16.662	96.852	3.148	194.03	224	0.875	bilinear
24	tf_efficientnet_b4_ap	83.248	16.752	96.388	3.612	19.34	380	0.922	bicubic
25	swsl_resnext101_32x4d	83.234	16.766	96.756	3.244	44.18	224	0.875	bilinear
26	tresnet_xl_448	83.048	16.952	96.174	3.826	78.44	448	0.875	bilinear
27	tf_efficientnet_b4	83.016	16.984	96.298	3.702	19.34	380	0.922	bicubic
28	resnest101e	82.89	17.11	96.324	3.676	48.28	256	0.875	bilinear
29	pnasnet5large	82.74	17.26	96.04	3.96	86.06	331	0.875	bicubic
30	ig_resnext101_32x8d	82.688	17.312	96.632	3.368	88.79	224	0.875	bilinear
31	nasnetalarge	82.558	17.442	96.036	3.964	88.75	331	0.875	bicubic
32	tf_efficientnet_b2_ns	82.38	17.62	96.252	3.748	9.11	260	0.89	bicubic
33	tresnet_l_448	82.268	17.732	95.978	4.022	55.99	448	0.875	bilinear
34	swsl_resnext50_32x4d	82.18	17.82	96.228	3.772	25.03	224	0.875	bilinear
35	ecaresnet101d	82.166	17.834	96.052	3.948	44.57	224	0.875	bicubic
36	tresnet_xl	82.07	17.93	95.928	4.072	78.44	224	0.875	bilinear
37	efficientnet_b3a	81.874	18.126	95.84	4.16	12.23	320	1.0	bicubic
38	ssl_resnext101_32x16d	81.836	18.164	96.094	3.906	194.03	224	0.875	bilinear
39	tf_efficientnet_b3_ap	81.828	18.172	95.624	4.376	12.23	300	0.904	bicubic
40	tresnet_m_448	81.712	18.288	95.57	4.43	31.39	448	0.875	bilinear
41	tf_efficientnet_b3	81.64	18.36	95.722	4.278	12.23	300	0.904	bicubic
42	ssl_resnext101_32x8d	81.626	18.374	96.038	3.962	88.79	224	0.875	bilinear
43	tf_efficientnet_lite4	81.528	18.472	95.668	4.332	13.01	380	0.92	bilinear
44	efficientnet_b3	81.498	18.502	95.718	4.282	12.23	300	0.904	bicubic
45	tresnet_l	81.488	18.512	95.628	4.372	55.99	224	0.875	bilinear
46	tf_efficientnet_b1_ns	81.386	18.614	95.738	4.262	7.79	240	0.882	bicubic
47	senet154	81.304	18.696	95.498	4.502	115.09	224	0.875	bilinear
48	gluon_senet154	81.224	18.776	95.356	4.644	115.09	224	0.875	bicubic
49	swsl_resnet50	81.18	18.82	95.986	4.014	25.56	224	0.875	bilinear
50	resnest50d_4s2x40d	81.114	18.886	95.568	4.432	30.42	224	0.875	bicubic
51	gluon_resnet152_v1s	81.012	18.988	95.416	4.584	60.32	224	0.875	bicubic
52	resnest50d_1s4x24d	80.99	19.01	95.322	4.678	25.68	224	0.875	bicubic
53	resnest50d	80.958	19.042	95.382	4.618	27.48	224	0.875	bilinear
54	ssl_resnext101_32x4d	80.928	19.072	95.728	4.272	44.18	224	0.875	bilinear
55	gluon_seresnext101_32x4d	80.902	19.098	95.294	4.706	48.96	224	0.875	bicubic
56	gluon_seresnext101_64x4d	80.89	19.11	95.304	4.696	88.23	224	0.875	bicubic
57	efficientnet_b3_pruned	80.856	19.144	95.24	4.76	9.86	300	0.904	bicubic
58	regnety_320	80.814	19.186	95.24	4.76	145.05	224	0.875	bicubic
59	ecaresnet101d_pruned	80.808	19.192	95.628	4.372	24.88	224	0.875	bicubic
60	tresnet_m	80.796	19.204	94.856	5.144	31.39	224	0.875	bilinear
61	efficientnet_b2a	80.608	19.392	95.31	4.69	9.11	288	1.0	bicubic
62	ecaresnet50d	80.604	19.396	95.322	4.678	25.58	224	0.875	bicubic
63	gluon_resnext101_64x4d	80.602	19.398	94.994	5.006	83.46	224	0.875	bicubic
64	mixnet_xl	80.478	19.522	94.932	5.068	11.9	224	0.875	bicubic
65	gluon_resnet152_v1d	80.47	19.53	95.206	4.794	60.21	224	0.875	bicubic
66	inception_resnet_v2	80.46	19.54	95.31	4.69	55.84	299	0.8975	bicubic
67	ecaresnetlight	80.454	19.546	95.256	4.744	30.16	224	0.875	bicubic
68	tf_efficientnet_el	80.448	19.552	95.16	4.84	10.59	300	0.904	bicubic
69	gluon_resnet101_v1d	80.424	19.576	95.02	4.98	44.57	224	0.875	bicubic
70	efficientnet_b2	80.402	19.598	95.076	4.924	9.11	260	0.875	bicubic
71	regnety_120	80.382	19.618	95.128	4.872	51.82	224	0.875	bicubic
72	gluon_resnext101_32x4d	80.334	19.666	94.926	5.074	44.18	224	0.875	bicubic
73	ssl_resnext50_32x4d	80.328	19.672	95.404	4.596	25.03	224	0.875	bilinear
74	tf_efficientnet_b2_ap	80.306	19.694	95.028	4.972	9.11	260	0.89	bicubic
75	gluon_resnet101_v1s	80.3	19.7	95.15	4.85	44.67	224	0.875	bicubic
76	regnety_160	80.3	19.7	94.962	5.038	83.59	224	0.875	bicubic
77	regnetx_320	80.246	19.754	95.022	4.978	107.81	224	0.875	bicubic
78	seresnext101_32x4d	80.236	19.764	95.028	4.972	48.96	224	0.875	bilinear
79	dpn107	80.164	19.836	94.912	5.088	86.92	224	0.875	bicubic
80	inception_v4	80.156	19.844	94.974	5.026	42.68	299	0.875	bicubic
81	skresnext50_32x4d	80.15	19.85	94.644	5.356	27.48	224	0.875	bicubic
82	tf_efficientnet_b2	80.09	19.91	94.906	5.094	9.11	260	0.89	bicubic
83	dpn92	80.016	19.984	94.838	5.162	37.67	224	0.875	bicubic
84	ens_adv_inception_resnet_v2	79.976	20.024	94.946	5.054	55.84	299	0.8975	bicubic
85	efficientnet_b2_pruned	79.918	20.082	94.848	5.152	8.31	260	0.89	bicubic
86	gluon_resnet152_v1c	79.916	20.084	94.842	5.158	60.21	224	0.875	bicubic
87	gluon_seresnext50_32x4d	79.912	20.088	94.818	5.182	27.56	224	0.875	bicubic
88	regnety_080	79.868	20.132	94.832	5.168	39.18	224	0.875	bicubic
89	regnetx_160	79.866	20.134	94.828	5.172	54.28	224	0.875	bicubic
90	dpn131	79.828	20.172	94.704	5.296	79.25	224	0.875	bicubic
91	tf_efficientnet_lite3	79.812	20.188	94.914	5.086	8.2	300	0.904	bilinear
92	resnext50_32x4d	79.762	20.238	94.6	5.4	25.03	224	0.875	bicubic
93	ecaresnet50d_pruned	79.718	20.282	94.89	5.11	19.94	224	0.875	bicubic
94	regnety_064	79.712	20.288	94.774	5.226	30.58	224	0.875	bicubic
95	gluon_resnet152_v1b	79.692	20.308	94.738	5.262	60.19	224	0.875	bicubic
96	resnext50d_32x4d	79.674	20.326	94.868	5.132	25.05	224	0.875	bicubic
97	dpn98	79.636	20.364	94.594	5.406	61.57	224	0.875	bicubic
98	gluon_xception65	79.604	20.396	94.748	5.252	39.92	299	0.875	bicubic
99	regnetx_120	79.59	20.41	94.74	5.26	46.11	224	0.875	bicubic
100	gluon_resnet101_v1c	79.544	20.456	94.586	5.414	44.57	224	0.875	bicubic
101	hrnet_w64	79.472	20.528	94.65	5.35	128.06	224	0.875	bilinear
102	dla102x2	79.452	20.548	94.644	5.356	41.75	224	0.875	bilinear
103	gluon_resnext50_32x4d	79.356	20.644	94.424	5.576	25.03	224	0.875	bicubic
104	ese_vovnet39b	79.32	20.68	94.71	5.29	24.57	224	0.875	bicubic
105	resnext101_32x8d	79.312	20.688	94.526	5.474	88.79	224	0.875	bilinear
106	hrnet_w48	79.31	20.69	94.518	5.482	77.47	224	0.875	bilinear
107	gluon_resnet101_v1b	79.304	20.696	94.524	5.476	44.55	224	0.875	bicubic
108	tf_efficientnet_cc_b1_8e	79.298	20.702	94.364	5.636	39.72	240	0.882	bicubic
109	resnetblur50	79.29	20.71	94.632	5.368	25.56	224	0.875	bicubic
110	tf_efficientnet_b1_ap	79.278	20.722	94.308	5.692	7.79	240	0.882	bicubic
111	ssl_resnet50	79.228	20.772	94.832	5.168	25.56	224	0.875	bilinear
112	regnety_040	79.222	20.778	94.656	5.344	20.65	224	0.875	bicubic
113	res2net50_26w_8s	79.21	20.79	94.362	5.638	48.4	224	0.875	bilinear
114	regnetx_080	79.198	20.802	94.558	5.442	39.57	224	0.875	bicubic
115	res2net101_26w_4s	79.196	20.804	94.44	5.56	45.21	224	0.875	bilinear
116	seresnext50_32x4d	79.076	20.924	94.434	5.566	27.56	224	0.875	bilinear
117	gluon_resnet50_v1d	79.074	20.926	94.476	5.524	25.58	224	0.875	bicubic
118	regnetx_064	79.066	20.934	94.456	5.544	26.21	224	0.875	bicubic
119	xception	79.048	20.952	94.392	5.608	22.86	299	0.8975	bicubic
120	resnet50	79.032	20.968	94.384	5.616	25.56	224	0.875	bicubic
121	mixnet_l	78.976	21.024	94.184	5.816	7.33	224	0.875	bicubic
122	hrnet_w40	78.934	21.066	94.466	5.534	57.56	224	0.875	bilinear
123	hrnet_w44	78.894	21.106	94.37	5.63	67.06	224	0.875	bilinear
124	regnety_032	78.87	21.13	94.402	5.598	19.44	224	0.875	bicubic
125	wide_resnet101_2	78.846	21.154	94.284	5.716	126.89	224	0.875	bilinear
126	tf_efficientnet_b1	78.832	21.168	94.196	5.804	7.79	240	0.882	bicubic
127	gluon_inception_v3	78.804	21.196	94.38	5.62	23.83	299	0.875	bicubic
128	tf_mixnet_l	78.77	21.23	94.004	5.996	7.33	224	0.875	bicubic
129	gluon_resnet50_v1s	78.712	21.288	94.242	5.758	25.68	224	0.875	bicubic
130	dla169	78.71	21.29	94.338	5.662	53.99	224	0.875	bilinear
131	efficientnet_b1	78.698	21.302	94.152	5.848	7.79	240	0.875	bicubic
132	tf_efficientnet_em	78.698	21.302	94.32	5.68	6.9	240	0.882	bicubic
133	seresnet152	78.658	21.342	94.374	5.626	66.82	224	0.875	bilinear
134	tf_efficientnet_b0_ns	78.652	21.348	94.368	5.632	5.29	224	0.875	bicubic
135	res2net50_26w_6s	78.574	21.426	94.126	5.874	37.05	224	0.875	bilinear
136	dla102x	78.508	21.492	94.234	5.766	26.77	224	0.875	bilinear
137	regnetx_040	78.486	21.514	94.242	5.758	22.12	224	0.875	bicubic
138	resnest26d	78.482	21.518	94.29	5.71	17.07	224	0.875	bilinear
139	dla60_res2net	78.472	21.528	94.204	5.796	21.15	224	0.875	bilinear
140	wide_resnet50_2	78.468	21.532	94.086	5.914	68.88	224	0.875	bilinear
141	dla60_res2next	78.448	21.552	94.144	5.856	17.33	224	0.875	bilinear
142	hrnet_w32	78.448	21.552	94.188	5.812	41.23	224	0.875	bilinear
143	selecsls60b	78.418	21.582	94.166	5.834	32.77	224	0.875	bicubic
144	seresnet101	78.396	21.604	94.258	5.742	49.33	224	0.875	bilinear
145	resnet152	78.312	21.688	94.046	5.954	60.19	224	0.875	bilinear
146	dla60x	78.242	21.758	94.022	5.978	17.65	224	0.875	bilinear
147	efficientnet_b1_pruned	78.242	21.758	93.832	6.168	6.33	240	0.882	bicubic
148	res2next50	78.242	21.758	93.892	6.108	24.67	224	0.875	bilinear
149	hrnet_w30	78.196	21.804	94.22	5.78	37.71	224	0.875	bilinear
150	regnetx_032	78.166	21.834	94.08	5.92	15.3	224	0.875	bicubic
151	res2net50_14w_8s	78.152	21.848	93.842	6.158	25.06	224	0.875	bilinear
152	efficientnet_es	78.054	21.946	93.93	6.07	5.44	224	0.875	bicubic
153	dla102	78.026	21.974	93.95	6.05	33.73	224	0.875	bilinear
154	gluon_resnet50_v1c	78.01	21.99	93.988	6.012	25.58	224	0.875	bicubic
155	seresnext26tn_32x4d	77.99	22.01	93.748	6.252	16.81	224	0.875	bicubic
156	seresnext26t_32x4d	77.988	22.012	93.706	6.294	16.82	224	0.875	bicubic
157	selecsls60	77.982	22.018	93.832	6.168	30.67	224	0.875	bicubic
158	res2net50_26w_4s	77.946	22.054	93.852	6.148	25.7	224	0.875	bilinear
159	tf_efficientnet_cc_b0_8e	77.908	22.092	93.656	6.344	24.01	224	0.875	bicubic
160	tf_inception_v3	77.856	22.144	93.644	6.356	23.83	299	0.875	bicubic
161	regnety_016	77.852	22.148	93.716	6.284	11.2	224	0.875	bicubic
162	efficientnet_b0	77.692	22.308	93.532	6.468	5.29	224	0.875	bicubic
163	seresnet50	77.636	22.364	93.752	6.248	28.09	224	0.875	bilinear
164	tv_resnext50_32x4d	77.618	22.382	93.698	6.302	25.03	224	0.875	bilinear
165	seresnext26d_32x4d	77.604	22.396	93.612	6.388	16.81	224	0.875	bicubic
166	adv_inception_v3	77.58	22.42	93.724	6.276	23.83	299	0.875	bicubic
167	gluon_resnet50_v1b	77.578	22.422	93.718	6.282	25.56	224	0.875	bicubic
168	dpn68b	77.514	22.486	93.822	6.178	12.61	224	0.875	bicubic
169	res2net50_48w_2s	77.514	22.486	93.548	6.452	25.29	224	0.875	bilinear
170	tf_efficientnet_lite2	77.46	22.54	93.746	6.254	6.09	260	0.89	bicubic
171	inception_v3	77.436	22.564	93.476	6.524	23.83	299	0.875	bicubic
172	resnet101	77.374	22.626	93.546	6.454	44.55	224	0.875	bilinear
173	densenet161	77.348	22.652	93.648	6.352	28.68	224	0.875	bicubic
174	tf_efficientnet_cc_b0_4e	77.304	22.696	93.332	6.668	13.31	224	0.875	bicubic
175	mobilenetv2_120d	77.294	22.706	93.502	6.498	5.83	224	0.875	bicubic
176	densenet201	77.29	22.71	93.478	6.522	20.01	224	0.875	bicubic
177	tf_efficientnet_es	77.264	22.736	93.6	6.4	5.44	224	0.875	bicubic
178	mixnet_m	77.256	22.744	93.418	6.582	5.01	224	0.875	bicubic
179	selecsls42b	77.176	22.824	93.392	6.608	32.46	224	0.875	bicubic
180	seresnext26_32x4d	77.1	22.9	93.31	6.69	16.79	224	0.875	bicubic
181	tf_efficientnet_b0_ap	77.084	22.916	93.254	6.746	5.29	224	0.875	bicubic
182	dla60	77.024	22.976	93.308	6.692	22.33	224	0.875	bilinear
183	tf_mixnet_m	76.95	23.05	93.156	6.844	5.01	224	0.875	bicubic
184	regnetx_016	76.93	23.07	93.418	6.582	9.19	224	0.875	bicubic
185	skresnet34	76.91	23.09	93.316	6.684	22.28	224	0.875	bicubic
186	tf_efficientnet_b0	76.84	23.16	93.226	6.774	5.29	224	0.875	bicubic
187	hrnet_w18	76.756	23.244	93.442	6.558	21.3	224	0.875	bilinear
188	resnet26d	76.68	23.32	93.166	6.834	16.01	224	0.875	bicubic
189	tf_efficientnet_lite1	76.638	23.362	93.232	6.768	5.42	240	0.882	bicubic
190	densenetblur121d	76.576	23.424	93.19	6.81	8.0	224	0.875	bicubic
191	mobilenetv2_140	76.524	23.476	92.99	7.01	6.11	224	0.875	bicubic
192	regnety_008	76.314	23.686	93.062	6.938	6.26	224	0.875	bicubic
193	dpn68	76.306	23.694	92.97	7.03	12.61	224	0.875	bicubic
194	tv_resnet50	76.13	23.87	92.862	7.138	25.56	224	0.875	bilinear
195	mixnet_s	75.988	24.012	92.794	7.206	4.13	224	0.875	bicubic
196	densenet169	75.912	24.088	93.024	6.976	14.15	224	0.875	bicubic
197	mobilenetv3_large_100	75.768	24.232	92.54	7.46	5.48	224	0.875	bicubic
198	tf_mixnet_s	75.648	24.352	92.636	7.364	4.13	224	0.875	bicubic
199	mobilenetv3_rw	75.628	24.372	92.71	7.29	5.48	224	0.875	bicubic
200	densenet121	75.574	24.426	92.656	7.344	7.98	224	0.875	bicubic
201	tf_mobilenetv3_large_100	75.516	24.484	92.6	7.4	5.48	224	0.875	bilinear
202	resnest14d	75.504	24.496	92.514	7.486	10.61	224	0.875	bilinear
203	semnasnet_100	75.456	24.544	92.592	7.408	3.89	224	0.875	bicubic
204	resnet26	75.292	24.708	92.57	7.43	16.0	224	0.875	bicubic
205	regnety_006	75.26	24.74	92.528	7.472	6.06	224	0.875	bicubic
206	hrnet_w18_small_v2	75.126	24.874	92.416	7.584	15.6	224	0.875	bilinear
207	fbnetc_100	75.12	24.88	92.386	7.614	5.57	224	0.875	bilinear
208	resnet34	75.112	24.888	92.288	7.712	21.8	224	0.875	bilinear
209	mobilenetv2_110d	75.052	24.948	92.18	7.82	4.52	224	0.875	bicubic
210	regnetx_008	75.022	24.978	92.344	7.656	7.26	224	0.875	bicubic
211	tf_efficientnet_lite0	74.842	25.158	92.17	7.83	4.65	224	0.875	bicubic
212	seresnet34	74.808	25.192	92.126	7.874	21.96	224	0.875	bilinear
213	tv_densenet121	74.752	25.248	92.152	7.848	7.98	224	0.875	bicubic
214	mnasnet_100	74.656	25.344	92.126	7.874	4.38	224	0.875	bicubic
215	dla34	74.636	25.364	92.064	7.936	15.78	224	0.875	bilinear
216	gluon_resnet34_v1b	74.58	25.42	91.988	8.012	21.8	224	0.875	bicubic
217	spnasnet_100	74.08	25.92	91.832	8.168	4.42	224	0.875	bilinear
218	regnety_004	74.026	25.974	91.748	8.252	4.34	224	0.875	bicubic
219	regnetx_006	73.862	26.138	91.68	8.32	6.2	224	0.875	bicubic
220	tf_mobilenetv3_large_075	73.442	26.558	91.352	8.648	3.99	224	0.875	bilinear
221	tv_resnet34	73.314	26.686	91.42	8.58	21.8	224	0.875	bilinear
222	swsl_resnet18	73.286	26.714	91.732	8.268	11.69	224	0.875	bilinear
223	skresnet18	73.044	26.956	91.178	8.822	11.96	224	0.875	bicubic
224	mobilenetv2_100	72.978	27.022	91.016	8.984	3.5	224	0.875	bicubic
225	ssl_resnet18	72.6	27.4	91.416	8.584	11.69	224	0.875	bilinear
226	regnetx_004	72.406	27.594	90.83	9.17	5.16	224	0.875	bicubic
227	hrnet_w18_small	72.342	27.658	90.672	9.328	13.19	224	0.875	bilinear
228	tf_mobilenetv3_large_minimal_100	72.244	27.756	90.636	9.364	3.92	224	0.875	bilinear
229	seresnet18	71.758	28.242	90.334	9.666	11.78	224	0.875	bicubic
230	gluon_resnet18_v1b	70.83	29.17	89.756	10.244	11.69	224	0.875	bicubic
231	regnety_002	70.282	29.718	89.54	10.46	3.16	224	0.875	bicubic
232	resnet18	69.758	30.242	89.078	10.922	11.69	224	0.875	bilinear
233	regnetx_002	68.754	31.246	88.548	11.452	2.68	224	0.875	bicubic
234	tf_mobilenetv3_small_100	67.918	32.082	87.662	12.338	2.54	224	0.875	bilinear
235	dla60x_c	67.908	32.092	88.434	11.566	1.34	224	0.875	bilinear
236	dla46x_c	65.98	34.02	86.98	13.02	1.08	224	0.875	bilinear
237	tf_mobilenetv3_small_075	65.718	34.282	86.136	13.864	2.04	224	0.875	bilinear
238	dla46_c	64.878	35.122	86.286	13.714	1.31	224	0.875	bilinear
239	tf_mobilenetv3_small_minimal_100	62.898	37.102	84.23	15.77	2.04	224	0.875	bilinear