segformer-b0-finetuned-segments-sidewalk-2

eungitoto/segformer-b0-finetuned-segments-sidewalk-2

segformer-b0-finetuned-segments-sidewalk-2 is a image segmentation model from eungitoto. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: Dec 20, 2023
Updated: Dec 20, 2023
SHA: 0f5d3d44

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

segformer-b0-finetuned-segments-sidewalk-2

This model is a fine-tuned version of nvidia/mit-b0 on the segments/sidewalk-semantic dataset. It achieves the following results on the evaluation set:

Loss: 0.6351
Mean Iou: 0.2834
Mean Accuracy: 0.3374
Overall Accuracy: 0.8443
Accuracy Unlabeled: nan
Accuracy Flat-road: 0.9045
Accuracy Flat-sidewalk: 0.9530
Accuracy Flat-crosswalk: 0.6075
Accuracy Flat-cyclinglane: 0.7798
Accuracy Flat-parkingdriveway: 0.3400
Accuracy Flat-railtrack: 0.0
Accuracy Flat-curb: 0.5121
Accuracy Human-person: 0.6170
Accuracy Human-rider: 0.0
Accuracy Vehicle-car: 0.9458
Accuracy Vehicle-truck: 0.0
Accuracy Vehicle-bus: 0.0
Accuracy Vehicle-tramtrain: 0.0
Accuracy Vehicle-motorcycle: 0.0
Accuracy Vehicle-bicycle: 0.6956
Accuracy Vehicle-caravan: 0.0
Accuracy Vehicle-cartrailer: 0.0
Accuracy Construction-building: 0.9045
Accuracy Construction-door: 0.0
Accuracy Construction-wall: 0.4037
Accuracy Construction-fenceguardrail: 0.3503
Accuracy Construction-bridge: 0.0
Accuracy Construction-tunnel: 0.0
Accuracy Construction-stairs: 0.0
Accuracy Object-pole: 0.3679
Accuracy Object-trafficsign: 0.0
Accuracy Object-trafficlight: 0.0
Accuracy Nature-vegetation: 0.9274
Accuracy Nature-terrain: 0.8889
Accuracy Sky: 0.9722
Accuracy Void-ground: 0.0
Accuracy Void-dynamic: 0.0119
Accuracy Void-static: 0.2879
Accuracy Void-unclear: 0.0
Iou Unlabeled: nan
Iou Flat-road: 0.7249
Iou Flat-sidewalk: 0.8500
Iou Flat-crosswalk: 0.5367
Iou Flat-cyclinglane: 0.7300
Iou Flat-parkingdriveway: 0.2828
Iou Flat-railtrack: 0.0
Iou Flat-curb: 0.4008
Iou Human-person: 0.4039
Iou Human-rider: 0.0
Iou Vehicle-car: 0.8291
Iou Vehicle-truck: 0.0
Iou Vehicle-bus: 0.0
Iou Vehicle-tramtrain: 0.0
Iou Vehicle-motorcycle: 0.0
Iou Vehicle-bicycle: 0.5268
Iou Vehicle-caravan: 0.0
Iou Vehicle-cartrailer: 0.0
Iou Construction-building: 0.7142
Iou Construction-door: 0.0
Iou Construction-wall: 0.3242
Iou Construction-fenceguardrail: 0.2450
Iou Construction-bridge: 0.0
Iou Construction-tunnel: 0.0
Iou Construction-stairs: 0.0
Iou Object-pole: 0.3031
Iou Object-trafficsign: 0.0
Iou Object-trafficlight: 0.0
Iou Nature-vegetation: 0.8429
Iou Nature-terrain: 0.7587
Iou Sky: 0.9308
Iou Void-ground: 0.0
Iou Void-dynamic: 0.0117
Iou Void-static: 0.2194
Iou Void-unclear: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 6e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Flat-road	Accuracy Flat-sidewalk	Accuracy Flat-crosswalk	Accuracy Flat-cyclinglane	Accuracy Flat-parkingdriveway	Accuracy Flat-curb	Accuracy Human-person	Accuracy Vehicle-car	Accuracy Vehicle-truck	Accuracy Vehicle-bicycle	Accuracy Construction-building	Accuracy Construction-wall	Accuracy Construction-fenceguardrail	Accuracy Object-pole	Accuracy Nature-vegetation	Accuracy Nature-terrain	Accuracy Sky	Accuracy Void-static	Iou Unlabeled	Iou Flat-road	Iou Flat-sidewalk	Iou Flat-crosswalk	Iou Flat-cyclinglane	Iou Flat-parkingdriveway	Iou Flat-curb	Iou Human-person	Iou Vehicle-car	Iou Vehicle-truck	Iou Vehicle-bicycle	Iou Construction-building	Iou Construction-wall	Iou Construction-fenceguardrail	Iou Object-pole	Iou Nature-vegetation	Iou Nature-terrain	Iou Sky	Iou Void-static
2.6363	0.4	20	3.0746	0.0958	0.1387	0.6097	nan	0.4923	0.9140	0.0023	0.0115	0.0163	0.0012	0.0	0.7446	0.0010	0.0	0.9002	0.0074	0.0	0.0	0.8330	0.0676	0.7219	0.0033	nan	0.3615	0.6272	0.0023	0.0115	0.0138	0.0012	0.0	0.4781	0.0004	0.0	0.3994	0.0072	0.0	0.0	0.6074	0.0646	0.6789	0.0033
2.1728	0.8	40	2.1331	0.1057	0.1504	0.6493	nan	0.7183	0.9087	0.0	0.0011	0.0031	0.0002	0.0	0.7912	0.0	0.0	0.8617	0.0025	0.0	0.0	0.9374	0.0054	0.8823	0.0004	nan	0.4086	0.6905	0.0	0.0011	0.0030	0.0002	0.0	0.5711	0.0	0.0	0.4771	0.0025	0.0	0.0	0.6142	0.0053	0.8190	0.0004
1.8992	1.2	60	1.7800	0.1102	0.1549	0.6621	nan	0.6924	0.9401	0.0	0.0144	0.0013	0.0000	0.0	0.8627	0.0	0.0	0.8730	0.0008	0.0	0.0	0.9193	0.0615	0.9003	0.0	nan	0.4255	0.6860	0.0	0.0144	0.0013	0.0000	0.0	0.5819	0.0	0.0	0.4994	0.0008	0.0	0.0	0.6468	0.0608	0.8313	0.0
1.8919	1.6	80	1.6335	0.1201	0.1629	0.6809	nan	0.7313	0.9424	0.0	0.0501	0.0008	0.0000	0.0	0.8569	0.0	0.0	0.8876	0.0002	0.0	0.0	0.9397	0.2331	0.8972	0.0	nan	0.4467	0.7033	0.0	0.0501	0.0008	0.0000	0.0	0.6179	0.0	0.0	0.5237	0.0002	0.0	0.0	0.6657	0.2237	0.8501	0.0
1.63	2.0	100	1.4813	0.1342	0.1756	0.7089	nan	0.8218	0.9389	0.0	0.2047	0.0006	0.0	0.0	0.8384	0.0	0.0	0.8802	0.0001	0.0	0.0	0.9479	0.4267	0.9098	0.0	nan	0.4844	0.7364	0.0	0.2025	0.0006	0.0	0.0	0.6453	0.0	0.0	0.5371	0.0001	0.0	0.0	0.6948	0.4056	0.8548	0.0
1.3523	2.4	120	1.3727	0.1467	0.1884	0.7335	nan	0.8524	0.9382	0.0	0.4096	0.0009	0.0	0.0	0.8653	0.0	0.0	0.8659	0.0002	0.0	0.0	0.9450	0.5996	0.9273	0.0	nan	0.5341	0.7489	0.0	0.4011	0.0009	0.0	0.0	0.6377	0.0	0.0	0.5535	0.0002	0.0	0.0	0.7173	0.5393	0.8549	0.0
1.2951	2.8	140	1.2957	0.1511	0.1932	0.7407	nan	0.8465	0.9414	0.0	0.4159	0.0029	0.0	0.0	0.8951	0.0	0.0	0.8775	0.0001	0.0	0.0	0.9327	0.7282	0.9275	0.0	nan	0.5327	0.7570	0.0	0.4072	0.0029	0.0	0.0	0.6595	0.0	0.0	0.5523	0.0001	0.0	0.0	0.7399	0.6208	0.8658	0.0
1.3024	3.2	160	1.2389	0.1536	0.1941	0.7464	nan	0.8844	0.9356	0.0	0.5074	0.0044	0.0	0.0	0.8589	0.0	0.0	0.8984	0.0000	0.0	0.0	0.9380	0.6688	0.9035	0.0	nan	0.5543	0.7672	0.0	0.4812	0.0043	0.0	0.0	0.6749	0.0	0.0	0.5517	0.0000	0.0	0.0	0.7351	0.5888	0.8655	0.0
1.3291	3.6	180	1.1719	0.1582	0.1970	0.7516	nan	0.7975	0.9658	0.0001	0.5346	0.0113	0.0	0.0	0.8905	0.0	0.0	0.9044	0.0003	0.0	0.0	0.9127	0.7531	0.9290	0.0	nan	0.5791	0.7373	0.0001	0.5120	0.0111	0.0	0.0	0.6910	0.0	0.0	0.5522	0.0003	0.0	0.0	0.7708	0.6519	0.8725	0.0
1.171	4.0	200	1.1129	0.1583	0.1982	0.7564	nan	0.8861	0.9498	0.0	0.5324	0.0266	0.0	0.0	0.8824	0.0	0.0	0.8648	0.0001	0.0	0.0	0.9478	0.7150	0.9343	0.0	nan	0.5772	0.7708	0.0	0.5090	0.0259	0.0	0.0	0.6945	0.0	0.0	0.5713	0.0001	0.0	0.0	0.7383	0.6220	0.8744	0.0
1.2553	4.4	220	1.0982	0.1597	0.2022	0.7524	nan	0.9524	0.8937	0.0	0.5760	0.0539	0.0000	0.0	0.8626	0.0	0.0	0.9018	0.0006	0.0	0.0	0.9364	0.7568	0.9400	0.0	nan	0.5187	0.7967	0.0	0.5249	0.0509	0.0000	0.0	0.6982	0.0	0.0	0.5609	0.0006	0.0	0.0	0.7580	0.6483	0.8736	0.0
0.9428	4.8	240	1.0357	0.1662	0.2074	0.7694	nan	0.9300	0.9359	0.0074	0.6225	0.0780	0.0007	0.0	0.8966	0.0	0.0	0.9012	0.0023	0.0	0.0	0.9207	0.8155	0.9398	0.0	nan	0.5795	0.7982	0.0074	0.5725	0.0727	0.0007	0.0	0.7107	0.0	0.0	0.5673	0.0023	0.0	0.0	0.7794	0.6826	0.8785	0.0
0.9843	5.2	260	0.9881	0.1689	0.2087	0.7706	nan	0.8682	0.9574	0.0704	0.6251	0.0810	0.0020	0.0	0.9139	0.0	0.0	0.8783	0.0051	0.0	0.0	0.9202	0.8331	0.9406	0.0	nan	0.6115	0.7686	0.0704	0.5919	0.0731	0.0020	0.0	0.7004	0.0	0.0	0.5797	0.0050	0.0	0.0	0.7766	0.6863	0.8784	0.0
0.9274	5.6	280	0.9701	0.1738	0.2166	0.7794	nan	0.9171	0.9276	0.1062	0.7376	0.1365	0.0097	0.0	0.9144	0.0	0.0	0.8870	0.0102	0.0	0.0	0.9297	0.8383	0.9493	0.0	nan	0.6165	0.8027	0.1059	0.6193	0.1201	0.0096	0.0	0.6958	0.0	0.0	0.5848	0.0101	0.0	0.0	0.7777	0.6882	0.8794	0.0
0.8762	6.0	300	0.9369	0.1850	0.2257	0.7864	nan	0.9056	0.9452	0.4152	0.6530	0.1945	0.0313	0.0	0.9224	0.0	0.0	0.8770	0.0269	0.0	0.0	0.9266	0.8372	0.9387	0.0	nan	0.6408	0.8042	0.3904	0.6126	0.1521	0.0310	0.0	0.6888	0.0	0.0	0.5874	0.0257	0.0	0.0	0.7821	0.6954	0.8809	0.0
0.8044	6.4	320	0.9197	0.1903	0.2308	0.7896	nan	0.9174	0.9437	0.5151	0.6212	0.2095	0.0733	0.0	0.9091	0.0	0.0	0.8953	0.0558	0.0	0.0	0.9174	0.8372	0.9511	0.0	nan	0.6400	0.8072	0.4651	0.5881	0.1706	0.0714	0.0	0.7168	0.0	0.0	0.5855	0.0512	0.0	0.0	0.7905	0.7010	0.8817	0.0
0.7438	6.8	340	0.8776	0.1934	0.2344	0.7940	nan	0.9134	0.9414	0.5616	0.6671	0.2014	0.0966	0.0	0.9162	0.0	0.0	0.9011	0.0716	0.0	0.0	0.9231	0.8347	0.9422	0.0	nan	0.6545	0.8114	0.4818	0.6313	0.1657	0.0933	0.0	0.7053	0.0	0.0	0.5874	0.0639	0.0	0.0	0.7945	0.6990	0.8886	0.0
0.9671	7.2	360	0.8704	0.1975	0.2399	0.7955	nan	0.8871	0.9408	0.5863	0.6940	0.2363	0.1439	0.0	0.9029	0.0	0.0	0.8684	0.1670	0.0	0.0	0.9291	0.8532	0.9471	0.0	nan	0.6532	0.8126	0.4632	0.6345	0.1855	0.1361	0.0	0.7283	0.0	0.0	0.5977	0.1406	0.0	0.0	0.7862	0.6935	0.8840	0.0
0.8191	7.6	380	0.8422	0.2048	0.2442	0.8033	nan	0.9159	0.9441	0.5265	0.7238	0.2684	0.1784	0.0003	0.8799	0.0	0.0	0.8603	0.2762	0.0	0.0000	0.9402	0.8318	0.9551	0.0005	nan	0.6939	0.8112	0.4965	0.6614	0.2087	0.1667	0.0003	0.7490	0.0	0.0	0.6063	0.2037	0.0	0.0000	0.7830	0.7000	0.8823	0.0005
0.8005	8.0	400	0.8414	0.1996	0.2372	0.7972	nan	0.9003	0.9492	0.5198	0.6659	0.1888	0.2424	0.0000	0.9048	0.0	0.0	0.9291	0.1105	0.0	0.0001	0.9216	0.7883	0.9434	0.0001	nan	0.6719	0.8049	0.4991	0.6372	0.1537	0.2152	0.0000	0.7254	0.0	0.0	0.5841	0.0940	0.0	0.0001	0.8047	0.7032	0.8927	0.0001
0.9294	8.4	420	0.8182	0.2036	0.2430	0.8029	nan	0.9269	0.9482	0.5270	0.6550	0.2482	0.2108	0.0002	0.9167	0.0	0.0	0.8894	0.2316	0.0	0.0004	0.9295	0.8273	0.9512	0.0007	nan	0.6841	0.8133	0.4924	0.6336	0.1979	0.1916	0.0002	0.7197	0.0	0.0	0.6065	0.1800	0.0	0.0004	0.8014	0.7111	0.8901	0.0007
0.7301	8.8	440	0.8036	0.2086	0.2527	0.8061	nan	0.9223	0.9419	0.5814	0.6931	0.2747	0.2847	0.0053	0.9361	0.0	0.0	0.8273	0.3837	0.0	0.0001	0.9300	0.8531	0.9561	0.0008	nan	0.6964	0.8218	0.5116	0.6603	0.2195	0.2440	0.0053	0.6847	0.0	0.0	0.6037	0.2526	0.0	0.0001	0.7979	0.7074	0.8852	0.0008
0.6754	9.2	460	0.7868	0.2083	0.2482	0.8070	nan	0.9098	0.9432	0.5608	0.7545	0.2089	0.2884	0.0073	0.9000	0.0	0.0	0.8991	0.2473	0.0	0.0001	0.9193	0.8499	0.9478	0.0023	nan	0.6748	0.8194	0.5305	0.6745	0.1787	0.2438	0.0073	0.7486	0.0	0.0	0.6100	0.1831	0.0	0.0001	0.8067	0.7069	0.8942	0.0023
0.7499	9.6	480	0.7756	0.2112	0.2511	0.8109	nan	0.9109	0.9429	0.5288	0.7550	0.2927	0.2838	0.0126	0.9117	0.0	0.0	0.9054	0.2797	0.0	0.0005	0.9263	0.8295	0.9522	0.0039	nan	0.7098	0.8209	0.4936	0.7004	0.2259	0.2461	0.0126	0.7399	0.0	0.0	0.6058	0.1980	0.0	0.0005	0.8077	0.7226	0.8942	0.0039
0.5878	10.0	500	0.7564	0.2131	0.2568	0.8123	nan	0.9099	0.9388	0.5922	0.7452	0.3135	0.2995	0.0235	0.9165	0.0	0.0	0.8776	0.3744	0.0000	0.0008	0.9301	0.8555	0.9495	0.0047	nan	0.6945	0.8339	0.4657	0.6925	0.2436	0.2602	0.0235	0.7350	0.0	0.0	0.6171	0.2630	0.0000	0.0008	0.7991	0.7150	0.8956	0.0046
0.874	10.4	520	0.7601	0.2169	0.2584	0.8133	nan	0.9144	0.9378	0.5474	0.7449	0.3350	0.3237	0.0738	0.9292	0.0	0.0	0.8918	0.3508	0.0002	0.0019	0.9232	0.8450	0.9579	0.0086	nan	0.7030	0.8214	0.5211	0.6962	0.2497	0.2740	0.0735	0.7398	0.0	0.0	0.6252	0.2396	0.0002	0.0019	0.8120	0.7134	0.8942	0.0084
0.5957	10.8	540	0.7557	0.2115	0.2534	0.8114	nan	0.8494	0.9518	0.6034	0.7916	0.2467	0.3290	0.0558	0.9140	0.0	0.0	0.9268	0.2114	0.0	0.0043	0.9189	0.8608	0.9472	0.0041	nan	0.7069	0.8234	0.4749	0.6717	0.2108	0.2916	0.0557	0.7444	0.0	0.0	0.6064	0.1714	0.0	0.0043	0.8108	0.7131	0.9005	0.0040
0.5981	11.2	560	0.7396	0.2223	0.2641	0.8176	nan	0.8798	0.9418	0.5376	0.8258	0.2915	0.3517	0.1215	0.9240	0.0	0.0	0.8754	0.4492	0.0029	0.0095	0.9420	0.8361	0.9583	0.0309	nan	0.7188	0.8224	0.5170	0.7030	0.2402	0.2981	0.1202	0.7507	0.0	0.0	0.6314	0.3022	0.0028	0.0095	0.8028	0.7141	0.8963	0.0295
0.5177	11.6	580	0.7403	0.2227	0.2665	0.8144	nan	0.9070	0.9314	0.6047	0.7349	0.3815	0.3395	0.1778	0.9082	0.0	0.0	0.8715	0.4334	0.0040	0.0100	0.9464	0.8180	0.9571	0.0353	nan	0.6983	0.8321	0.4714	0.6965	0.2653	0.2899	0.1731	0.7622	0.0	0.0	0.6327	0.2963	0.0038	0.0100	0.7972	0.7113	0.8992	0.0334
0.5689	12.0	600	0.7382	0.2237	0.2642	0.8176	nan	0.9339	0.9440	0.5055	0.7365	0.3006	0.3610	0.1763	0.9328	0.0	0.0000	0.8772	0.4224	0.0153	0.0108	0.9320	0.8401	0.9553	0.0391	nan	0.7077	0.8244	0.4863	0.7017	0.2403	0.3038	0.1720	0.7422	0.0	0.0000	0.6333	0.2928	0.0142	0.0108	0.8130	0.7274	0.8999	0.0366
0.6379	12.4	620	0.7284	0.2260	0.2674	0.8171	nan	0.8613	0.9554	0.5848	0.7909	0.2547	0.3498	0.2235	0.9240	0.0	0.0011	0.8959	0.4200	0.0197	0.0173	0.9153	0.8660	0.9535	0.0598	nan	0.7209	0.8117	0.5001	0.7144	0.2080	0.3020	0.2141	0.7682	0.0	0.0011	0.6390	0.2812	0.0188	0.0172	0.8154	0.7159	0.9029	0.0546
0.5772	12.8	640	0.7187	0.2317	0.2755	0.8213	nan	0.9200	0.9479	0.5902	0.7480	0.2776	0.3621	0.3136	0.9321	0.0	0.0023	0.8618	0.4991	0.0422	0.0430	0.9282	0.8676	0.9574	0.0742	nan	0.7049	0.8337	0.4961	0.7056	0.2336	0.3085	0.2828	0.7610	0.0	0.0023	0.6438	0.3241	0.0375	0.0427	0.8137	0.7203	0.9018	0.0667
0.6958	13.2	660	0.6981	0.2346	0.2795	0.8243	nan	0.9034	0.9373	0.6079	0.8121	0.3564	0.3662	0.3246	0.9333	0.0	0.0022	0.8780	0.4743	0.0491	0.0335	0.9305	0.8584	0.9573	0.0779	nan	0.7277	0.8370	0.4877	0.7263	0.2627	0.3095	0.2965	0.7655	0.0	0.0022	0.6538	0.3213	0.0434	0.0333	0.8126	0.7263	0.9021	0.0692
0.6015	13.6	680	0.7058	0.2382	0.2808	0.8256	nan	0.9422	0.9404	0.5065	0.7814	0.3153	0.3763	0.3868	0.9294	0.0	0.0052	0.9027	0.4368	0.1332	0.0725	0.9198	0.8596	0.9627	0.0749	nan	0.7195	0.8358	0.4934	0.7243	0.2502	0.3068	0.3232	0.7693	0.0	0.0052	0.6496	0.3222	0.1099	0.0713	0.8216	0.7279	0.9005	0.0679
0.5698	14.0	700	0.6973	0.2374	0.2806	0.8240	nan	0.9140	0.9468	0.5788	0.7557	0.3021	0.3873	0.3988	0.9359	0.0	0.0113	0.9088	0.3731	0.1032	0.0816	0.9156	0.8763	0.9563	0.0937	nan	0.7136	0.8338	0.4892	0.7176	0.2411	0.3250	0.3327	0.7658	0.0	0.0113	0.6525	0.3009	0.0915	0.0804	0.8157	0.7135	0.9056	0.0825
0.6438	14.4	720	0.6984	0.2417	0.2849	0.8258	nan	0.9185	0.9511	0.5585	0.7586	0.3002	0.3864	0.4324	0.9399	0.0	0.0168	0.8707	0.4506	0.1372	0.0670	0.9270	0.8638	0.9586	0.1479	nan	0.7374	0.8238	0.5275	0.7116	0.2414	0.3184	0.3475	0.7622	0.0	0.0167	0.6636	0.3196	0.1092	0.0661	0.8193	0.7246	0.9037	0.1249
0.4882	14.8	740	0.6937	0.2419	0.2838	0.8280	nan	0.9320	0.9493	0.5035	0.7776	0.2815	0.4022	0.4547	0.9293	0.0	0.0157	0.9167	0.3765	0.1535	0.0903	0.9199	0.8638	0.9618	0.1214	nan	0.7364	0.8293	0.4922	0.7276	0.2350	0.3321	0.3528	0.7749	0.0	0.0157	0.6534	0.2906	0.1250	0.0889	0.8270	0.7322	0.9064	0.1054
0.4693	15.2	760	0.6931	0.2437	0.2883	0.8248	nan	0.9276	0.9436	0.5805	0.7401	0.3161	0.4023	0.4731	0.9225	0.0	0.0212	0.8888	0.4353	0.1921	0.0994	0.9260	0.8468	0.9584	0.1281	nan	0.7061	0.8324	0.5132	0.7048	0.2545	0.3326	0.3620	0.7827	0.0	0.0212	0.6548	0.3164	0.1357	0.0970	0.8211	0.7338	0.9070	0.1113
0.5884	15.6	780	0.6870	0.2460	0.2919	0.8280	nan	0.8965	0.9478	0.5938	0.7779	0.3113	0.4136	0.5281	0.9223	0.0	0.0379	0.9103	0.3960	0.1587	0.1163	0.9203	0.8756	0.9641	0.1551	nan	0.7291	0.8308	0.5095	0.7130	0.2456	0.3393	0.3730	0.7832	0.0	0.0378	0.6676	0.3097	0.1280	0.1127	0.8267	0.7249	0.9050	0.1296
0.4822	16.0	800	0.6822	0.2490	0.2929	0.8277	nan	0.8592	0.9535	0.5867	0.8150	0.2845	0.4140	0.5151	0.9363	0.0	0.0563	0.8924	0.3955	0.2003	0.1470	0.9358	0.8603	0.9569	0.1481	nan	0.7180	0.8218	0.5548	0.7288	0.2424	0.3294	0.3797	0.7752	0.0	0.0562	0.6685	0.3157	0.1505	0.1400	0.8201	0.7296	0.9095	0.1267
0.4741	16.4	820	0.6827	0.2488	0.2926	0.8283	nan	0.8902	0.9524	0.5983	0.7742	0.3112	0.4137	0.4934	0.9314	0.0	0.0730	0.8856	0.4433	0.1811	0.1122	0.9397	0.8325	0.9600	0.1564	nan	0.7279	0.8282	0.5455	0.7332	0.2494	0.3343	0.3734	0.7841	0.0	0.0729	0.6686	0.3175	0.1309	0.1090	0.8181	0.7275	0.9094	0.1289
0.5164	16.8	840	0.6803	0.2488	0.2928	0.8309	nan	0.9067	0.9498	0.5655	0.8037	0.3081	0.4061	0.5493	0.9276	0.0	0.0686	0.9156	0.3162	0.1933	0.1543	0.9273	0.8698	0.9604	0.1324	nan	0.7404	0.8309	0.5307	0.7191	0.2548	0.3371	0.3740	0.7897	0.0	0.0685	0.6642	0.2698	0.1508	0.1469	0.8258	0.7322	0.9105	0.1132
0.4384	17.2	860	0.6711	0.2512	0.2978	0.8313	nan	0.9294	0.9412	0.5986	0.7805	0.3288	0.4120	0.5585	0.9350	0.0	0.0621	0.8890	0.4228	0.1557	0.1642	0.9272	0.8743	0.9600	0.1852	nan	0.7282	0.8363	0.5214	0.7324	0.2651	0.3417	0.3806	0.7894	0.0	0.0620	0.6730	0.3112	0.1257	0.1559	0.8215	0.7310	0.9109	0.1533
0.4316	17.6	880	0.6659	0.2556	0.3047	0.8338	nan	0.9368	0.9390	0.5718	0.8247	0.3282	0.4395	0.5804	0.9423	0.0	0.0993	0.8502	0.4347	0.2537	0.2004	0.9375	0.8574	0.9656	0.1969	nan	0.7368	0.8437	0.5323	0.7437	0.2656	0.3588	0.3788	0.7690	0.0	0.0989	0.6726	0.3185	0.1661	0.1845	0.8227	0.7293	0.9084	0.1607
0.4505	18.0	900	0.6758	0.2542	0.2989	0.8298	nan	0.9136	0.9505	0.5574	0.7432	0.2982	0.4386	0.5360	0.9437	0.0	0.1767	0.9093	0.4136	0.2006	0.1824	0.9305	0.8321	0.9575	0.1794	nan	0.7194	0.8331	0.5212	0.7112	0.2453	0.3458	0.3758	0.7782	0.0	0.1753	0.6756	0.3193	0.1549	0.1715	0.8259	0.7307	0.9115	0.1480
0.4388	18.4	920	0.6661	0.2565	0.3072	0.8297	nan	0.8822	0.9428	0.6160	0.8143	0.3081	0.4454	0.5414	0.9279	0.0	0.2064	0.8709	0.4429	0.2824	0.1963	0.9268	0.8822	0.9626	0.1975	nan	0.7157	0.8393	0.4520	0.7274	0.2555	0.3630	0.3766	0.8002	0.0	0.2041	0.6728	0.3199	0.1873	0.1827	0.8220	0.7298	0.9113	0.1622
0.361	18.8	940	0.6628	0.2605	0.3096	0.8323	nan	0.8951	0.9452	0.5626	0.8170	0.3278	0.4493	0.5721	0.9407	0.0	0.2403	0.8579	0.4486	0.2506	0.1961	0.9287	0.8857	0.9658	0.2412	nan	0.7357	0.8323	0.5378	0.7362	0.2625	0.3491	0.3683	0.7867	0.0	0.2364	0.6806	0.3224	0.1758	0.1821	0.8223	0.7321	0.9113	0.1866
0.3828	19.2	960	0.6739	0.2605	0.3097	0.8287	nan	0.8388	0.9556	0.5834	0.8373	0.2736	0.4234	0.6044	0.9343	0.0	0.2668	0.8799	0.4288	0.2738	0.2310	0.9154	0.8914	0.9607	0.2327	nan	0.7156	0.8243	0.5543	0.6957	0.2336	0.3482	0.3805	0.7961	0.0	0.2613	0.6838	0.3288	0.1820	0.2107	0.8227	0.7190	0.9134	0.1857
0.6092	19.6	980	0.6651	0.2619	0.3102	0.8331	nan	0.9454	0.9455	0.5339	0.7741	0.3170	0.4542	0.6123	0.9329	0.0	0.2972	0.9051	0.3950	0.2431	0.2317	0.9022	0.8711	0.9631	0.2214	nan	0.7209	0.8382	0.5155	0.7300	0.2616	0.3551	0.3647	0.7986	0.0	0.2900	0.6842	0.3113	0.1817	0.2123	0.8260	0.7207	0.9135	0.1808
0.4141	20.0	1000	0.6641	0.2647	0.3139	0.8316	nan	0.9264	0.9481	0.5341	0.7649	0.3226	0.4334	0.5668	0.9405	0.0	0.3605	0.8534	0.4698	0.2992	0.2259	0.9166	0.8909	0.9625	0.2556	nan	0.7208	0.8365	0.5058	0.7259	0.2609	0.3563	0.3898	0.7969	0.0	0.3435	0.6834	0.3347	0.1917	0.2066	0.8200	0.7153	0.9160	0.1970
0.4172	20.4	1020	0.6580	0.2638	0.3124	0.8320	nan	0.8716	0.9580	0.6106	0.7824	0.2688	0.4657	0.5675	0.9364	0.0	0.3450	0.8929	0.4323	0.3108	0.2097	0.9226	0.8574	0.9667	0.2240	nan	0.7318	0.8241	0.5236	0.7430	0.2310	0.3535	0.3745	0.8019	0.0	0.3327	0.6804	0.3154	0.2001	0.1933	0.8345	0.7404	0.9137	0.1768
0.4116	20.8	1040	0.6727	0.2634	0.3088	0.8344	nan	0.8931	0.9598	0.6058	0.7902	0.2737	0.4378	0.5670	0.9385	0.0	0.3090	0.8957	0.3829	0.2471	0.2405	0.9260	0.8616	0.9612	0.2085	nan	0.7426	0.8232	0.5412	0.7417	0.2388	0.3514	0.3729	0.7984	0.0	0.2989	0.6842	0.3072	0.1826	0.2174	0.8303	0.7357	0.9163	0.1736

The model card is truncated. Read the rest on Hugging Face.

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Dec 20, 2023
Updated: Dec 20, 2023