segformer-finetuned-sidewalk-10k-steps

s246216/segformer-finetuned-sidewalk-10k-steps

segformer-finetuned-sidewalk-10k-steps is a image segmentation model from s246216. 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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1.4 GB on disk

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At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: Oct 6, 2024
Updated: Oct 10, 2024
SHA: e68c0a7f

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

segformer-finetuned-sidewalk-10k-steps

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: 0.5870
Mean Iou: 0.2962
Mean Accuracy: 0.3656
Overall Accuracy: 0.8302
Accuracy Unlabeled: nan
Accuracy Flat-road: 0.7752
Accuracy Flat-sidewalk: 0.9460
Accuracy Flat-crosswalk: 0.8223
Accuracy Flat-cyclinglane: 0.7550
Accuracy Flat-parkingdriveway: 0.2805
Accuracy Flat-railtrack: nan
Accuracy Flat-curb: 0.5378
Accuracy Human-person: 0.6477
Accuracy Human-rider: 0.0
Accuracy Vehicle-car: 0.9354
Accuracy Vehicle-truck: 0.0
Accuracy Vehicle-bus: 0.0
Accuracy Vehicle-tramtrain: 0.0
Accuracy Vehicle-motorcycle: 0.0
Accuracy Vehicle-bicycle: 0.5094
Accuracy Vehicle-caravan: 0.0
Accuracy Vehicle-cartrailer: 0.0
Accuracy Construction-building: 0.8737
Accuracy Construction-door: 0.0
Accuracy Construction-wall: 0.5689
Accuracy Construction-fenceguardrail: 0.5286
Accuracy Construction-bridge: 0.0
Accuracy Construction-tunnel: nan
Accuracy Construction-stairs: 0.0
Accuracy Object-pole: 0.4050
Accuracy Object-trafficsign: 0.0
Accuracy Object-trafficlight: 0.0
Accuracy Nature-vegetation: 0.9220
Accuracy Nature-terrain: 0.8417
Accuracy Sky: 0.9603
Accuracy Void-ground: 0.0
Accuracy Void-dynamic: 0.0091
Accuracy Void-static: 0.3817
Accuracy Void-unclear: 0.0
Iou Unlabeled: nan
Iou Flat-road: 0.6953
Iou Flat-sidewalk: 0.8257
Iou Flat-crosswalk: 0.6744
Iou Flat-cyclinglane: 0.5831
Iou Flat-parkingdriveway: 0.2594
Iou Flat-railtrack: nan
Iou Flat-curb: 0.3720
Iou Human-person: 0.4758
Iou Human-rider: 0.0
Iou Vehicle-car: 0.7439
Iou Vehicle-truck: 0.0
Iou Vehicle-bus: 0.0
Iou Vehicle-tramtrain: 0.0
Iou Vehicle-motorcycle: 0.0
Iou Vehicle-bicycle: 0.2578
Iou Vehicle-caravan: 0.0
Iou Vehicle-cartrailer: 0.0
Iou Construction-building: 0.6847
Iou Construction-door: 0.0
Iou Construction-wall: 0.4535
Iou Construction-fenceguardrail: 0.4437
Iou Construction-bridge: 0.0
Iou Construction-tunnel: nan
Iou Construction-stairs: 0.0
Iou Object-pole: 0.2822
Iou Object-trafficsign: 0.0
Iou Object-trafficlight: 0.0
Iou Nature-vegetation: 0.8452
Iou Nature-terrain: 0.7081
Iou Sky: 0.9161
Iou Void-ground: 0.0
Iou Void-dynamic: 0.0090
Iou Void-static: 0.2470
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: 8
eval_batch_size: 8
seed: 1337
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: polynomial
training_steps: 10000

Training results

Training Loss	Epoch	Step	Accuracy Construction-building	Accuracy Construction-fenceguardrail	Accuracy Construction-tunnel	Accuracy Construction-wall	Accuracy Flat-crosswalk	Accuracy Flat-curb	Accuracy Flat-cyclinglane	Accuracy Flat-parkingdriveway	Accuracy Flat-railtrack	Accuracy Flat-road	Accuracy Flat-sidewalk	Accuracy Human-person	Accuracy Nature-terrain	Accuracy Nature-vegetation	Accuracy Object-pole	Accuracy Sky	Accuracy Unlabeled	Accuracy Vehicle-bicycle	Accuracy Vehicle-car	Accuracy Vehicle-tramtrain	Accuracy Void-dynamic	Accuracy Void-static	Iou Construction-building	Iou Construction-fenceguardrail	Iou Construction-tunnel	Iou Construction-wall	Iou Flat-crosswalk	Iou Flat-curb	Iou Flat-cyclinglane	Iou Flat-parkingdriveway	Iou Flat-railtrack	Iou Flat-road	Iou Flat-sidewalk	Iou Human-person	Iou Nature-terrain	Iou Nature-vegetation	Iou Object-pole	Iou Sky	Iou Unlabeled	Iou Vehicle-bicycle	Iou Vehicle-car	Iou Vehicle-tramtrain	Iou Void-dynamic	Iou Void-static	Validation Loss	Mean Accuracy	Mean Iou	Overall Accuracy
2.5976	1.0	107	0.8716	0.0	nan	0.0	0.0	0.0000	0.0340	0.0059	nan	0.7126	0.8829	0.0	0.7639	0.8401	0.0	0.5274	nan	0.0	0.7375	nan	0.0	0.0	0.4078	0.0	nan	0.0	0.0	0.0000	0.0335	0.0058	nan	0.4342	0.7303	0.0	0.4971	0.6088	0.0	0.5238	nan	0.0	0.5006	nan	0.0	0.0	1.8167	0.1734	0.1207	0.6649
1.7804	2.0	214	0.8645	0.0	nan	0.0	0.0	0.0000	0.4088	0.0091	nan	0.4849	0.9320	0.0	0.7240	0.8760	0.0	0.6529	nan	0.0	0.7975	nan	0.0	0.0	0.4432	0.0	nan	0.0	0.0	0.0000	0.3873	0.0090	nan	0.3862	0.7022	0.0	0.5454	0.6380	0.0	0.6448	nan	0.0	0.5313	nan	0.0	0.0	1.5213	0.1855	0.1383	0.6885
1.4506	3.0	321	0.8987	0.0	nan	0.0	0.0	0.0010	0.5240	0.0117	nan	0.5295	0.9284	0.0	0.8090	0.8123	0.0	0.8372	nan	0.0	0.8111	nan	0.0	0.0	0.4566	0.0	nan	0.0	0.0	0.0010	0.4336	0.0116	nan	0.4384	0.7208	0.0	0.5342	0.6543	0.0	0.7963	nan	0.0	0.5375	nan	0.0	0.0	1.3304	0.1988	0.1479	0.7053
1.2854	4.0	428	0.8395	0.0	nan	0.0	0.0	0.0013	0.5963	0.0190	nan	0.5613	0.9518	0.0	0.8063	0.7245	0.0	0.9043	nan	0.0	0.9129	nan	0.0	0.0	0.5325	0.0	nan	0.0	0.0	0.0013	0.4682	0.0187	nan	0.4473	0.7302	0.0	0.4632	0.6076	0.0	0.8239	nan	0.0	0.5643	nan	0.0	0.0	1.1582	0.2038	0.1502	0.7119
1.1642	5.0	535	0.8254	0.0	nan	0.0	0.0	0.0063	0.7528	0.0587	nan	0.6286	0.9087	0.0	0.8256	0.8157	0.0000	0.9404	nan	0.0	0.9277	nan	0.0	0.0	0.5305	0.0	nan	0.0	0.0	0.0062	0.4925	0.0546	nan	0.4666	0.7665	0.0	0.5518	0.6739	0.0000	0.8213	nan	0.0	0.5415	nan	0.0	0.0	1.1097	0.2158	0.1582	0.7293
1.0799	6.0	642	0.8431	0.0	nan	0.0	0.0	0.0122	0.6784	0.0697	nan	0.5980	0.9488	0.0	0.8225	0.8262	0.0008	0.9372	nan	0.0	0.9414	nan	0.0	0.0	0.5299	0.0	nan	0.0	0.0	0.0117	0.5230	0.0649	nan	0.4718	0.7595	0.0	0.5885	0.7045	0.0008	0.8205	nan	0.0	0.5774	nan	0.0	0.0	1.0014	0.2154	0.1630	0.7393
1.0072	7.0	749	0.8738	0.0	nan	0.0042	0.0070	0.2003	0.6716	0.1430	nan	0.6910	0.9306	0.0	0.8153	0.8074	0.0017	0.9013	nan	0.0	0.9354	nan	0.0	0.0003	0.5090	0.0	nan	0.0041	0.0070	0.1458	0.6067	0.1168	nan	0.5294	0.7917	0.0	0.5533	0.6821	0.0017	0.8340	nan	0.0	0.5637	nan	0.0	0.0003	0.9490	0.2253	0.1724	0.7464
0.984	8.0	856	0.8566	0.0	nan	0.0314	0.1486	0.1743	0.7371	0.1348	nan	0.6086	0.9221	0.0	0.6871	0.8991	0.0205	0.9047	nan	0.0	0.9382	nan	0.0	0.0001	0.5408	0.0	nan	0.0307	0.1485	0.1336	0.4415	0.1161	nan	0.4910	0.7736	0.0	0.6197	0.7323	0.0202	0.8432	nan	0.0	0.6013	nan	0.0	0.0001	0.9205	0.2278	0.1772	0.7460
0.915	9.0	963	0.8404	0.0	nan	0.1437	0.5864	0.3057	0.6835	0.1982	nan	0.7090	0.9415	0.0	0.8255	0.8329	0.0645	0.9328	nan	0.0	0.9341	nan	0.0	0.0053	0.5652	0.0	nan	0.1308	0.4699	0.1767	0.6121	0.1550	nan	0.5848	0.8019	0.0	0.5785	0.6993	0.0597	0.8524	nan	0.0	0.6370	nan	0.0	0.0051	0.8332	0.2582	0.2041	0.7702
0.8824	10.0	1070	0.8843	0.0	nan	0.0371	0.7441	0.2783	0.7581	0.1750	nan	0.8493	0.7731	0.0	0.7427	0.9100	0.1120	0.9336	nan	0.0	0.9236	nan	0.0	0.0131	0.5406	0.0	nan	0.0352	0.5175	0.1624	0.4615	0.1452	nan	0.5509	0.7306	0.0	0.6595	0.7475	0.0968	0.8444	nan	0.0	0.6323	nan	0.0	0.0123	0.9102	0.2624	0.1980	0.7420
0.8133	11.0	1177	0.8471	0.0001	nan	0.2570	0.6660	0.3263	0.7662	0.2418	nan	0.6984	0.9167	0.0308	0.7725	0.8677	0.1876	0.9201	nan	0.0	0.9386	nan	0.0	0.0227	0.5412	0.0001	nan	0.1887	0.5137	0.1982	0.5765	0.1849	nan	0.5743	0.7964	0.0299	0.6809	0.7657	0.1367	0.8434	nan	0.0	0.6371	nan	0.0	0.0212	0.8147	0.2729	0.2158	0.7737
0.8029	12.0	1284	0.8274	0.0001	nan	0.2257	0.7924	0.3257	0.8064	0.3262	nan	0.4170	0.9044	0.1800	0.8542	0.8370	0.1968	0.9124	nan	0.0	0.9401	nan	0.0	0.0575	0.5649	0.0001	nan	0.1804	0.4960	0.1876	0.4040	0.2183	nan	0.3817	0.7994	0.1545	0.5926	0.7280	0.1465	0.8639	nan	0.0	0.6549	nan	0.0	0.0486	0.8597	0.2775	0.2071	0.7427
0.8166	13.0	1391	0.8364	0.0	nan	0.2578	0.6942	0.2631	0.7621	0.2267	nan	0.5905	0.9075	0.2544	0.7529	0.9264	0.2317	0.9297	nan	0.0	0.9342	nan	0.0	0.0362	0.5759	0.0	nan	0.2117	0.5555	0.1845	0.4370	0.1793	nan	0.5142	0.7828	0.2029	0.6831	0.7646	0.1479	0.8628	nan	0.0	0.6656	nan	0.0	0.0336	0.8034	0.2775	0.2194	0.7655
0.7582	14.0	1498	0.8060	0.0022	nan	0.4223	0.7450	0.3414	0.7468	0.2863	nan	0.6522	0.9323	0.2355	0.8710	0.8169	0.2442	0.9435	nan	0.0	0.8890	nan	0.0	0.0539	0.5605	0.0022	nan	0.2575	0.5183	0.2118	0.5597	0.2211	nan	0.5628	0.8109	0.1857	0.5691	0.7164	0.1531	0.8665	nan	0.0	0.6934	nan	0.0	0.0498	0.7747	0.2900	0.2238	0.7727
0.7669	15.0	1605	0.7878	0.0034	nan	0.3742	0.7369	0.3506	0.6943	0.2288	nan	0.5781	0.9404	0.2633	0.8169	0.8762	0.3000	0.9231	nan	0.0	0.9461	nan	0.0	0.0484	0.5657	0.0034	nan	0.2425	0.4899	0.1978	0.4820	0.1886	nan	0.5133	0.8055	0.2088	0.6658	0.7638	0.1512	0.8597	nan	0.0	0.6478	nan	0.0	0.0436	0.7869	0.2861	0.2203	0.7690
0.6652	16.0	1712	0.8814	0.0004	nan	0.3337	0.8311	0.3079	0.7933	0.2521	nan	0.6354	0.9192	0.4108	0.7857	0.9223	0.2649	0.9252	nan	0.0	0.8721	nan	0.0	0.0474	0.5338	0.0004	nan	0.2333	0.5449	0.1959	0.5722	0.2055	nan	0.5614	0.8214	0.2604	0.7013	0.7777	0.1648	0.8747	nan	0.0	0.6819	nan	0.0	0.0437	0.7644	0.2962	0.2314	0.7832
0.6706	17.0	1819	0.8498	0.0101	nan	0.3778	0.7270	0.2322	0.8303	0.2801	nan	0.5029	0.9083	0.5548	0.8575	0.8799	0.2880	0.9585	nan	0.0	0.9107	nan	0.0	0.0766	0.5856	0.0101	nan	0.2506	0.5817	0.1612	0.4110	0.2289	nan	0.4506	0.7961	0.3049	0.6819	0.7806	0.1801	0.8821	nan	0.0	0.7249	nan	0.0	0.0693	0.7996	0.2982	0.2290	0.7649
0.6466	18.0	1926	0.8108	0.0262	nan	0.4841	0.8584	0.2654	0.8431	0.3039	nan	0.4422	0.8782	0.5326	0.8432	0.9130	0.2361	0.9411	nan	0.0	0.9447	nan	0.0	0.1762	0.5962	0.0259	nan	0.2776	0.5696	0.1869	0.3526	0.2396	nan	0.4058	0.7978	0.3165	0.7060	0.7897	0.1815	0.8873	nan	0.0	0.6949	nan	0.0	0.1423	0.8046	0.3064	0.2313	0.7562
0.652	19.0	2033	0.8059	0.0161	nan	0.5654	0.7580	0.2439	0.7384	0.2594	nan	0.4601	0.9339	0.6299	0.8739	0.8663	0.2749	0.9341	nan	0.0	0.9147	nan	0.0	0.1054	0.6110	0.0161	nan	0.3079	0.5175	0.1772	0.4120	0.2180	nan	0.4140	0.7907	0.3186	0.6320	0.7572	0.1810	0.8871	nan	0.0	0.7379	nan	0.0	0.0937	0.8110	0.3026	0.2281	0.7623
0.6547	20.0	2140	0.8135	0.0793	nan	0.3920	0.8563	0.3291	0.7943	0.3934	nan	0.6505	0.9035	0.6328	0.8299	0.9087	0.3951	0.9350	nan	0.0	0.9440	nan	0.0	0.1874	0.6299	0.0758	nan	0.2870	0.5098	0.2266	0.4864	0.2733	nan	0.5700	0.8166	0.3297	0.7015	0.7944	0.1770	0.8913	nan	0.0	0.7049	nan	0.0	0.1436	0.7205	0.3240	0.2457	0.7885
0.6278	21.0	2247	0.7191	0.1114	nan	0.5394	0.7069	0.4743	0.8021	0.4035	nan	0.6842	0.9158	0.7155	0.8750	0.8706	0.3563	0.9442	nan	0.0	0.9386	nan	0.0	0.2143	0.6040	0.1003	nan	0.3067	0.5481	0.2581	0.5635	0.2724	nan	0.5997	0.8250	0.3280	0.6375	0.7686	0.1893	0.8921	nan	0.0	0.7233	nan	0.0	0.1503	0.7129	0.3313	0.2506	0.7905
0.5872	22.0	2354	0.7515	0.0535	nan	0.5099	0.7462	0.3655	0.7844	0.3205	nan	0.6225	0.9094	0.7130	0.8558	0.9015	0.2839	0.9401	nan	0.0	0.9209	nan	0.0	0.2068	0.6130	0.0516	nan	0.2994	0.5161	0.2294	0.4419	0.2491	nan	0.5430	0.8100	0.3168	0.6703	0.7680	0.2037	0.8899	nan	0.0	0.7347	nan	0.0	0.1663	0.7458	0.3189	0.2420	0.7798
0.6228	23.0	2461	0.7653	0.1850	nan	0.4119	0.7566	0.3355	0.8048	0.3356	nan	0.6472	0.8888	0.7324	0.8906	0.8384	0.3526	0.9624	nan	0.0	0.9423	nan	0.0	0.2648	0.6293	0.1631	nan	0.2881	0.4781	0.2163	0.4550	0.2538	nan	0.5476	0.8075	0.3276	0.5909	0.7407	0.1998	0.8925	nan	0.0	0.7182	nan	0.0	0.1918	0.7450	0.3263	0.2419	0.7736
0.6222	24.0	2568	0.8326	0.1325	nan	0.3981	0.7508	0.3212	0.7890	0.3020	nan	0.5528	0.9168	0.6682	0.8718	0.8591	0.2781	0.9459	nan	0.0	0.9338	nan	0.0	0.1607	0.6097	0.1219	nan	0.2596	0.4342	0.2183	0.4341	0.2483	nan	0.4997	0.8057	0.3521	0.6371	0.7705	0.2118	0.8957	nan	0.0	0.7237	nan	0.0	0.1366	0.7382	0.3133	0.2374	0.7739
0.6091	25.0	2675	0.8422	0.1438	nan	0.3359	0.7425	0.4027	0.7658	0.2776	nan	0.6930	0.9233	0.7489	0.8170	0.9120	0.3705	0.9583	nan	0.0000	0.9408	nan	0.0	0.2414	0.6450	0.1331	nan	0.2660	0.4921	0.2546	0.5285	0.2306	nan	0.5936	0.8118	0.3397	0.7058	0.8024	0.2199	0.9035	nan	0.0000	0.7310	nan	0.0	0.1903	0.6769	0.3263	0.2532	0.7990
0.6221	26.0	2782	0.7736	0.2123	nan	0.4579	0.7598	0.3519	0.8172	0.2849	nan	0.6024	0.8967	0.7217	0.8619	0.9313	0.3190	0.9649	nan	0.0016	0.9282	nan	0.0	0.2119	0.6215	0.1824	nan	0.2864	0.4723	0.2471	0.4266	0.2423	nan	0.5268	0.8065	0.3466	0.7278	0.8029	0.2185	0.9007	nan	0.0016	0.7237	nan	0.0	0.1676	0.7356	0.3257	0.2484	0.7831
0.5454	27.0	2889	0.8401	0.1746	nan	0.3947	0.7176	0.3235	0.6758	0.2731	nan	0.6905	0.9550	0.6696	0.8600	0.8809	0.3356	0.9397	nan	0.0079	0.9271	nan	0.0	0.2391	0.6194	0.1594	nan	0.2701	0.5271	0.2303	0.5649	0.2321	nan	0.6150	0.7982	0.3531	0.6901	0.7922	0.2254	0.8969	nan	0.0078	0.7279	nan	0.0	0.1801	0.6964	0.3195	0.2545	0.7991
0.5709	28.0	2996	0.8184	0.2241	nan	0.4355	0.7343	0.3770	0.7834	0.3074	nan	0.6394	0.9416	0.6648	0.8821	0.8885	0.3578	0.9442	nan	0.0342	0.9282	nan	0.0	0.3020	0.6371	0.1905	nan	0.2831	0.5172	0.2496	0.5331	0.2495	nan	0.5704	0.8268	0.3605	0.6862	0.7927	0.2284	0.9028	nan	0.0340	0.7422	nan	0.0	0.2106	0.6863	0.3311	0.2585	0.7998
0.5664	29.0	3103	0.8023	0.3131	nan	0.3598	0.7123	0.3470	0.7990	0.2892	nan	0.5688	0.9470	0.7599	0.8637	0.8557	0.3526	0.9613	nan	0.0695	0.9391	nan	0.0	0.3811	0.6435	0.2397	nan	0.2619	0.5396	0.2235	0.4799	0.2494	nan	0.5071	0.8211	0.3648	0.6522	0.7766	0.2406	0.9013	nan	0.0682	0.7594	nan	0.0	0.2344	0.7072	0.3329	0.2569	0.7891
0.542	30.0	3210	0.7592	0.2181	nan	0.4753	0.7425	0.3047	0.8342	0.3012	nan	0.6422	0.9135	0.7422	0.8181	0.9551	0.3815	0.9605	nan	0.1002	0.9221	nan	0.0	0.2309	0.6302	0.1828	nan	0.3013	0.5331	0.2196	0.4606	0.2513	nan	0.5443	0.8263	0.3693	0.7289	0.8015	0.2259	0.9066	nan	0.0988	0.7698	nan	0.0	0.1811	0.7051	0.3323	0.2591	0.7947
0.5375	31.0	3317	0.7617	0.1755	nan	0.5301	0.8719	0.3344	0.7952	0.3352	nan	0.5278	0.9229	0.6944	0.9046	0.9200	0.3532	0.9511	nan	0.1426	0.9275	nan	0.0	0.3034	0.6345	0.1584	nan	0.3094	0.4748	0.2310	0.4504	0.2700	nan	0.4846	0.8235	0.3834	0.6851	0.7904	0.2308	0.9074	nan	0.1389	0.7458	nan	0.0	0.2131	0.7305	0.3371	0.2559	0.7863
0.535	32.0	3424	0.7739	0.3066	nan	0.5520	0.8096	0.4133	0.7600	0.3220	nan	0.6451	0.9327	0.8020	0.8559	0.9102	0.2987	0.9566	nan	0.0770	0.9368	nan	0.0	0.3188	0.6316	0.2293	nan	0.3036	0.4555	0.2616	0.5372	0.2513	nan	0.5613	0.8315	0.3445	0.7326	0.8180	0.2302	0.9071	nan	0.0752	0.7486	nan	0.0	0.2221	0.6733	0.3442	0.2626	0.8012
0.5636	33.0	3531	0.8092	0.2053	nan	0.5336	0.7694	0.4192	0.8019	0.3084	nan	0.7065	0.9194	0.6938	0.8313	0.9391	0.3518	0.9488	nan	0.1731	0.9437	nan	0.0	0.2363	0.6529	0.1906	nan	0.3369	0.4765	0.2642	0.5526	0.2401	nan	0.5897	0.8382	0.3804	0.7367	0.8184	0.2337	0.9075	nan	0.1652	0.7330	nan	0.0	0.1834	0.6684	0.3416	0.2677	0.8084
0.5505	34.0	3638	0.8225	0.2114	nan	0.4930	0.7549	0.3676	0.8124	0.2890	nan	0.5729	0.9154	0.7762	0.8461	0.8935	0.3487	0.9644	nan	0.2165	0.9385	nan	0.0	0.2902	0.6439	0.1959	nan	0.3108	0.4893	0.2312	0.4534	0.2354	nan	0.5078	0.8100	0.3614	0.7042	0.8070	0.2385	0.9016	nan	0.1998	0.7485	nan	0.0	0.2243	0.7332	0.3391	0.2601	0.7873
0.4997	35.0	3745	0.7751	0.2318	nan	0.5303	0.7571	0.3386	0.7602	0.3260	nan	0.5502	0.9315	0.6972	0.8640	0.8844	0.3373	0.9589	nan	0.2345	0.9486	nan	0.0	0.3800	0.6395	0.2005	nan	0.3165	0.4231	0.2292	0.4485	0.2628	nan	0.4969	0.8142	0.3751	0.6729	0.7945	0.2428	0.9070	nan	0.2137	0.7350	nan	0.0	0.2580	0.7480	0.3389	0.2590	0.7855
0.5366	36.0	3852	0.7552	0.2691	nan	0.5338	0.7469	0.3836	0.8005	0.2835	nan	0.6501	0.9283	0.7427	0.8510	0.9043	0.3771	0.9554	nan	0.3942	0.9230	nan	0.0	0.3655	0.6322	0.2114	nan	0.3176	0.5020	0.2554	0.4912	0.2395	nan	0.5597	0.8241	0.4260	0.6891	0.7995	0.2546	0.9091	nan	0.3214	0.7661	nan	0.0	0.2469	0.6978	0.3505	0.2724	0.7977
0.4906	37.0	3959	0.8165	0.2961	nan	0.4623	0.7669	0.3306	0.8392	0.2410	nan	0.6486	0.8787	0.7101	0.8190	0.9264	0.3859	0.9419	nan	0.4669	0.9204	nan	0.0	0.2223	0.6432	0.2197	nan	0.3002	0.5329	0.2279	0.4188	0.2102	nan	0.5394	0.8015	0.4203	0.7085	0.8072	0.2377	0.9051	nan	0.3451	0.7588	nan	0.0	0.1770	0.7503	0.3443	0.2662	0.7841
0.5118	38.0	4066	0.8273	0.2801	nan	0.3642	0.7244	0.3013	0.7807	0.2551	nan	0.5729	0.9456	0.6684	0.8435	0.8640	0.3352	0.9518	nan	0.3851	0.9446	nan	0.0	0.3227	0.6429	0.2221	nan	0.2657	0.5411	0.2126	0.4916	0.2205	nan	0.5185	0.8029	0.4145	0.6285	0.7717	0.2425	0.9072	nan	0.3095	0.7423	nan	0.0	0.2407	0.7362	0.3344	0.2637	0.7879
0.4985	39.0	4173	0.8302	0.2901	nan	0.4468	0.7353	0.3697	0.8480	0.2743	nan	0.6099	0.8904	0.5992	0.8284	0.9398	0.3290	0.9471	nan	0.4215	0.9158	nan	0.0	0.2700	0.6305	0.2345	nan	0.2947	0.5318	0.2438	0.4409	0.2393	nan	0.5266	0.8018	0.3929	0.7316	0.8164	0.2406	0.9071	nan	0.3260	0.7450	nan	0.0	0.2110	0.7233	0.3402	0.2682	0.7881
0.4699	40.0	4280	0.8024	0.2990	nan	0.4394	0.7668	0.3949	0.8297	0.3961	nan	0.6314	0.8917	0.8516	0.8484	0.9336	0.3618	0.9286	nan	0.4776	0.8734	nan	0.0	0.3008	0.6335	0.2385	nan	0.2927	0.5027	0.2429	0.4659	0.2965	nan	0.5416	0.8156	0.3845	0.7224	0.8100	0.2540	0.9014	nan	0.3136	0.7560	nan	0.0	0.2002	0.7067	0.3557	0.2701	0.7910
0.4902	41.0	4387	0.7649	0.2691	nan	0.5976	0.7597	0.3178	0.8527	0.3826	nan	0.5802	0.8845	0.8739	0.8636	0.9068	0.3949	0.9478	nan	0.3965	0.9216	nan	0.0	0.4058	0.6407	0.2333	nan	0.3309	0.5259	0.2343	0.4046	0.2973	nan	0.5109	0.8126	0.3629	0.6980	0.8057	0.2607	0.9111	nan	0.3085	0.7619	nan	0.0	0.2455	0.7404	0.3587	0.2692	0.7830
0.4767	42.0	4494	0.8010	0.3051	nan	0.5965	0.7496	0.3448	0.7418	0.3449	nan	0.6851	0.9297	0.7722	0.8617	0.9151	0.3570	0.9490	nan	0.5528	0.9300	nan	0.0	0.2682	0.6404	0.2486	nan	0.3385	0.5237	0.2527	0.4808	0.2830	nan	0.5924	0.8285	0.4378	0.7287	0.8147	0.2532	0.9081	nan	0.3667	0.7672	nan	0.0	0.2032	0.6919	0.3582	0.2796	0.8064
0.4808	43.0	4601	0.8205	0.2740	nan	0.4271	0.7658	0.3968	0.7978	0.3431	nan	0.7343	0.9109	0.7423	0.8530	0.9224	0.3703	0.9610	nan	0.5331	0.9343	nan	0.0	0.3525	0.6496	0.2360	nan	0.2974	0.5224	0.2573	0.5367	0.2787	nan	0.6153	0.8280	0.4419	0.7256	0.8132	0.2641	0.9133	nan	0.3610	0.7656	nan	0.0	0.2293	0.6529	0.3593	0.2818	0.8101
0.4856	44.0	4708	0.7544	0.3635	nan	0.5563	0.7601	0.3744	0.8449	0.2588	nan	0.6798	0.9001	0.7376	0.8244	0.9442	0.3504	0.9559	nan	0.4988	0.9370	nan	0.0	0.3124	0.6420	0.2511	nan	0.3396	0.4741	0.2427	0.5032	0.2217	nan	0.5626	0.8144	0.4349	0.7435	0.8181	0.2577	0.9146	nan	0.3501	0.7634	nan	0.0	0.2363	0.6946	0.3565	0.2764	0.7992
0.4851	45.0	4815	0.7679	0.3934	nan	0.5722	0.7532	0.3503	0.7958	0.2108	nan	0.6574	0.9390	0.7433	0.8411	0.9406	0.3709	0.9444	nan	0.5928	0.9144	nan	0.0	0.2887	0.6408	0.2521	nan	0.3427	0.5218	0.2599	0.5058	0.1911	nan	0.5712	0.8248	0.4379	0.7368	0.8192	0.2649	0.9113	nan	0.3790	0.7827	nan	0.0	0.2172	0.6892	0.3573	0.2793	0.8059
0.4501	46.0	4922	0.7657	0.2218	nan	0.5302	0.7870	0.3808	0.7889	0.3163	nan	0.6432	0.9322	0.8010	0.8685	0.9145	0.3789	0.9582	nan	0.5823	0.9385	nan	0.0	0.3514	0.6477	0.1958	nan	0.3393	0.5376	0.2661	0.5080	0.2548	nan	0.5579	0.8203	0.4270	0.7028	0.8082	0.2580	0.9138	nan	0.3629	0.7802	nan	0.0	0.2406	0.6820	0.3600	0.2781	0.8030
0.4478	47.0	5029	0.7282	0.4742	nan	0.4257	0.7680	0.3652	0.8137	0.3156	nan	0.7054	0.8899	0.7185	0.8486	0.9437	0.3897	0.9545	nan	0.6559	0.9240	nan	0.0	0.3549	0.6341	0.2461	nan	0.3064	0.5210	0.2712	0.4584	0.2630	nan	0.5889	0.8045	0.4264	0.7302	0.8207	0.2608	0.9161	nan	0.3385	0.7758	nan	0.0	0.2488	0.7221	0.3637	0.2778	0.7967
0.4762	48.0	5136	0.7870	0.3175	nan	0.5524	0.7465	0.4107	0.7937	0.2813	nan	0.7275	0.9203	0.7740	0.8385	0.9237	0.3892	0.9705	nan	0.5589	0.9282	nan	0.0	0.3434	0.6576	0.2534	nan	0.3446	0.5270	0.2668	0.5230	0.2408	nan	0.6172	0.8257	0.4306	0.7306	0.8246	0.2651	0.9123	nan	0.3529	0.7532	nan	0.0	0.2384	0.6645	0.3633	0.2827	0.8107
0.4917	49.0	5243	0.8442	0.3261	nan	0.4818	0.7786	0.3815	0.8153	0.3339	nan	0.6644	0.9004	0.6652	0.8469	0.8852	0.4037	0.9598	nan	0.5722	0.9455	nan	0.0	0.3689	0.6639	0.2549	nan	0.3434	0.5596	0.2653	0.4531	0.2750	nan	0.5724	0.8112	0.4145	0.7003	0.8107	0.2607	0.9152	nan	0.3419	0.7500	nan	0.0	0.2599	0.7079	0.3604	0.2791	0.7981
0.4523	50.0	5350	0.7922	0.4293	nan	0.5745	0.7435	0.3628	0.8149	0.3005	nan	0.7184	0.9130	0.6609	0.8872	0.8609	0.3886	0.9617	nan	0.5839	0.9177	nan	0.0	0.3187	0.6541	0.2607	nan	0.3544	0.5365	0.2593	0.4960	0.2604	nan	0.6084	0.8243	0.4192	0.6482	0.7833	0.2651	0.9171	nan	0.3434	0.7757	nan	0.0	0.2391	0.7000	0.3622	0.2789	0.8017
0.4565	51.0	5457	0.8088	0.3499	nan	0.4947	0.7533	0.3353	0.8168	0.3336	nan	0.5536	0.9207	0.7255	0.8568	0.9100	0.4062	0.9548	nan	0.5423	0.9232	nan	0.0	0.3173	0.6558	0.2649	nan	0.3388	0.5413	0.2584	0.4239	0.2755	nan	0.5027	0.8115	0.4348	0.6949	0.8037	0.2735	0.9172	nan	0.3517	0.7631	nan	0.0	0.2376	0.7123	0.3549	0.2758	0.7915
0.4248	52.0	5564	0.8278	0.3435	nan	0.4859	0.7679	0.3571	0.7682	0.3031	nan	0.6239	0.9453	0.7205	0.8629	0.9189	0.3815	0.9586	nan	0.5404	0.9305	nan	0.0000	0.2831	0.6392	0.2749	nan	0.3280	0.5339	0.2642	0.5117	0.2578	nan	0.5560	0.8251	0.4317	0.7240	0.8207	0.2665	0.9173	nan	0.3624	0.7654	nan	0.0000	0.2209	0.6752	0.3555	0.2806	0.8075

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

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Oct 6, 2024
Updated: Oct 10, 2024