segformer-b0-finetuned-segments-sidewalk-oct-22

hcdolm/segformer-b0-finetuned-segments-sidewalk-oct-22

segformer-b0-finetuned-segments-sidewalk-oct-22 is a image segmentation model from hcdolm. 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: Jul 24, 2025
Updated: Jul 24, 2025
SHA: 3b9e7ab9

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

segformer-b0-finetuned-segments-sidewalk-oct-22

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: 0.5610
Mean Iou: 0.3348
Mean Accuracy: 0.4014
Overall Accuracy: 0.8658
Accuracy Unlabeled: nan
Accuracy Flat-road: 0.9169
Accuracy Flat-sidewalk: 0.9533
Accuracy Flat-crosswalk: 0.8682
Accuracy Flat-cyclinglane: 0.8532
Accuracy Flat-parkingdriveway: 0.5622
Accuracy Flat-railtrack: nan
Accuracy Flat-curb: 0.6472
Accuracy Human-person: 0.7021
Accuracy Human-rider: 0.0
Accuracy Vehicle-car: 0.9415
Accuracy Vehicle-truck: 0.0
Accuracy Vehicle-bus: 0.0
Accuracy Vehicle-tramtrain: 0.0
Accuracy Vehicle-motorcycle: 0.0
Accuracy Vehicle-bicycle: 0.7166
Accuracy Vehicle-caravan: 0.0
Accuracy Vehicle-cartrailer: 0.0
Accuracy Construction-building: 0.9008
Accuracy Construction-door: 0.0390
Accuracy Construction-wall: 0.4542
Accuracy Construction-fenceguardrail: 0.5200
Accuracy Construction-bridge: 0.0
Accuracy Construction-tunnel: nan
Accuracy Construction-stairs: 0.0002
Accuracy Object-pole: 0.3901
Accuracy Object-trafficsign: 0.0002
Accuracy Object-trafficlight: 0.0
Accuracy Nature-vegetation: 0.9345
Accuracy Nature-terrain: 0.8414
Accuracy Sky: 0.9709
Accuracy Void-ground: 0.0564
Accuracy Void-dynamic: 0.1721
Accuracy Void-static: 0.4028
Accuracy Void-unclear: 0.0
Iou Unlabeled: nan
Iou Flat-road: 0.7966
Iou Flat-sidewalk: 0.8867
Iou Flat-crosswalk: 0.7573
Iou Flat-cyclinglane: 0.7814
Iou Flat-parkingdriveway: 0.4545
Iou Flat-railtrack: nan
Iou Flat-curb: 0.4940
Iou Human-person: 0.4052
Iou Human-rider: 0.0
Iou Vehicle-car: 0.8295
Iou Vehicle-truck: 0.0
Iou Vehicle-bus: 0.0
Iou Vehicle-tramtrain: 0.0
Iou Vehicle-motorcycle: 0.0
Iou Vehicle-bicycle: 0.4977
Iou Vehicle-caravan: 0.0
Iou Vehicle-cartrailer: 0.0
Iou Construction-building: 0.7150
Iou Construction-door: 0.0377
Iou Construction-wall: 0.3664
Iou Construction-fenceguardrail: 0.4217
Iou Construction-bridge: 0.0
Iou Construction-tunnel: nan
Iou Construction-stairs: 0.0002
Iou Object-pole: 0.2928
Iou Object-trafficsign: 0.0002
Iou Object-trafficlight: 0.0
Iou Nature-vegetation: 0.8600
Iou Nature-terrain: 0.6971
Iou Sky: 0.9232
Iou Void-ground: 0.0541
Iou Void-dynamic: 0.1464
Iou Void-static: 0.2966
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: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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-railtrack	Accuracy Flat-curb	Accuracy Human-person	Accuracy Vehicle-car	Accuracy Vehicle-bicycle	Accuracy Construction-building	Accuracy Construction-wall	Accuracy Construction-fenceguardrail	Accuracy Construction-tunnel	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-railtrack	Iou Flat-curb	Iou Human-person	Iou Vehicle-car	Iou Vehicle-bicycle	Iou Construction-building	Iou Construction-wall	Iou Construction-fenceguardrail	Iou Construction-tunnel	Iou Object-pole	Iou Nature-vegetation	Iou Nature-terrain	Iou Sky	Iou Void-static
1.8799	0.2	20	1.5300	0.1382	0.1814	0.7072	nan	0.7788	0.9437	0.0	0.1378	0.0001	nan	0.0006	0.0	0.8049	0.0	0.8884	0.0	0.0001	nan	0.0	0.9475	0.4312	0.8730	0.0	nan	0.4916	0.7387	0.0	0.1375	0.0001	nan	0.0006	0.0	0.6198	0.0	0.4880	0.0	0.0001	nan	0.0	0.7316	0.3960	0.8178	0.0
1.8326	0.4	40	1.4090	0.1469	0.1915	0.7259	nan	0.8096	0.9514	0.0	0.3031	0.0000	nan	0.0005	0.0	0.8685	0.0	0.8697	0.0	0.0	nan	0.0	0.9471	0.4620	0.9145	0.0	nan	0.5338	0.7510	0.0	0.2999	0.0000	nan	0.0005	0.0	0.6020	0.0	0.5188	0.0	0.0	nan	0.0	0.7450	0.4270	0.8236	0.0
1.6385	0.6	60	1.3235	0.1527	0.1974	0.7332	nan	0.8433	0.9447	0.0	0.3349	0.0002	nan	0.0001	0.0	0.8728	0.0	0.8878	0.0	0.0	nan	0.0	0.9341	0.6193	0.8797	0.0	nan	0.5256	0.7694	0.0	0.3297	0.0002	nan	0.0001	0.0	0.6190	0.0	0.5257	0.0	0.0	nan	0.0	0.7599	0.5233	0.8322	0.0
1.4929	0.8	80	1.2860	0.1582	0.2055	0.7431	nan	0.8700	0.9425	0.0	0.4093	0.0020	nan	0.0000	0.0	0.9093	0.0	0.8643	0.0	0.0	nan	0.0	0.9240	0.7174	0.9358	0.0	nan	0.5376	0.7824	0.0	0.4015	0.0020	nan	0.0000	0.0	0.6012	0.0	0.5358	0.0	0.0	nan	0.0	0.7770	0.5902	0.8339	0.0
1.611	1.0	100	1.2357	0.1606	0.2084	0.7445	nan	0.8814	0.9273	0.0	0.4821	0.0065	nan	0.0001	0.0	0.9154	0.0	0.8473	0.0	0.0	nan	0.0	0.9351	0.7537	0.9186	0.0	nan	0.5313	0.7858	0.0	0.4599	0.0065	nan	0.0001	0.0	0.6012	0.0	0.5483	0.0	0.0	nan	0.0	0.7635	0.5986	0.8435	0.0
1.8268	1.2	120	1.1484	0.1602	0.2092	0.7464	nan	0.8819	0.9366	0.0	0.4357	0.0105	nan	0.0027	0.0	0.9180	0.0	0.8642	0.0000	0.0	nan	0.0	0.9192	0.7870	0.9371	0.0	nan	0.5421	0.7882	0.0	0.4216	0.0104	nan	0.0027	0.0	0.6090	0.0	0.5598	0.0000	0.0	nan	0.0	0.7633	0.5827	0.8457	0.0
1.2303	1.4	140	1.1846	0.1647	0.2119	0.7536	nan	0.8928	0.9375	0.0	0.4878	0.0195	nan	0.0014	0.0	0.8765	0.0	0.8982	0.0	0.0	nan	0.0	0.9274	0.8070	0.9327	0.0	nan	0.5550	0.7996	0.0	0.4723	0.0192	nan	0.0014	0.0	0.6626	0.0	0.5437	0.0	0.0	nan	0.0	0.7716	0.5946	0.8510	0.0
1.3754	1.6	160	1.0874	0.1659	0.2140	0.7547	nan	0.8935	0.9326	0.0	0.5321	0.0195	nan	0.0027	0.0	0.9133	0.0	0.8829	0.0	0.0	nan	0.0	0.9248	0.8013	0.9447	0.0	nan	0.5505	0.7952	0.0	0.5106	0.0193	nan	0.0027	0.0	0.6441	0.0	0.5497	0.0	0.0	nan	0.0	0.7849	0.6073	0.8450	0.0
1.5062	1.8	180	1.0693	0.1710	0.2182	0.7648	nan	0.8862	0.9485	0.0	0.6774	0.0278	nan	0.0027	0.0	0.9110	0.0	0.8999	0.0	0.0	nan	0.0	0.9059	0.8104	0.9113	0.0	nan	0.5911	0.8042	0.0	0.6061	0.0270	nan	0.0027	0.0	0.6579	0.0	0.5468	0.0	0.0	nan	0.0	0.7834	0.5952	0.8581	0.0
1.1767	2.0	200	1.0072	0.1708	0.2161	0.7634	nan	0.8771	0.9459	0.0	0.6307	0.0322	nan	0.0081	0.0	0.9111	0.0	0.8849	0.0	0.0	nan	0.0	0.9418	0.7488	0.9350	0.0	nan	0.5966	0.7908	0.0	0.5981	0.0314	nan	0.0080	0.0	0.6415	0.0	0.5535	0.0	0.0	nan	0.0	0.7738	0.6187	0.8532	0.0
1.296	2.2	220	0.9950	0.1740	0.2187	0.7674	nan	0.8772	0.9534	0.0	0.6955	0.0494	nan	0.0138	0.0	0.8710	0.0	0.9169	0.0	0.0	nan	0.0	0.9139	0.8233	0.8832	0.0000	nan	0.5975	0.7987	0.0	0.6432	0.0476	nan	0.0136	0.0	0.6905	0.0	0.5370	0.0	0.0	nan	0.0	0.7949	0.6121	0.8340	0.0000
0.9493	2.4	240	0.9963	0.1664	0.2120	0.7545	nan	0.9024	0.9467	0.0	0.4394	0.0549	nan	0.0157	0.0	0.9166	0.0	0.8716	0.0001	0.0	nan	0.0	0.9194	0.7730	0.9431	0.0	nan	0.5491	0.7874	0.0	0.4318	0.0523	nan	0.0155	0.0	0.6607	0.0	0.5659	0.0001	0.0	nan	0.0	0.7937	0.6116	0.8554	0.0
1.0047	2.6	260	0.9605	0.1784	0.2302	0.7684	nan	0.8735	0.9182	0.0	0.7425	0.1512	nan	0.1497	0.0	0.9360	0.0	0.8947	0.0003	0.0	nan	0.0	0.9171	0.8304	0.9532	0.0	nan	0.5879	0.8154	0.0	0.5656	0.1352	nan	0.1337	0.0	0.6419	0.0	0.5573	0.0003	0.0	nan	0.0	0.8000	0.6185	0.8532	0.0
1.0766	2.8	280	0.9365	0.1791	0.2244	0.7714	nan	0.8684	0.9571	0.0	0.5460	0.1133	nan	0.1979	0.0	0.9238	0.0	0.9034	0.0002	0.0	nan	0.0	0.9359	0.8060	0.9273	0.0002	nan	0.6089	0.8036	0.0	0.5322	0.1028	nan	0.1751	0.0	0.6554	0.0	0.5630	0.0002	0.0	nan	0.0	0.7990	0.6231	0.8662	0.0002
1.3337	3.0	300	0.8935	0.1850	0.2293	0.7772	nan	0.8133	0.9560	0.0	0.7660	0.1561	nan	0.2527	0.0	0.8936	0.0	0.8957	0.0023	0.0	nan	0.0000	0.9604	0.6985	0.9426	0.0005	nan	0.6093	0.8148	0.0	0.6230	0.1403	nan	0.2103	0.0	0.6999	0.0	0.5542	0.0023	0.0	nan	0.0000	0.7824	0.6156	0.8681	0.0005
1.0744	3.2	320	0.8695	0.1844	0.2310	0.7777	nan	0.9055	0.9452	0.0	0.6364	0.1505	nan	0.2400	0.0	0.9322	0.0	0.8795	0.0109	0.0	nan	0.0001	0.9316	0.7978	0.9602	0.0004	nan	0.6067	0.8214	0.0	0.6028	0.1336	nan	0.2058	0.0	0.6662	0.0	0.5659	0.0107	0.0	nan	0.0001	0.7976	0.6309	0.8596	0.0004
1.0612	3.4	340	0.8719	0.1838	0.2304	0.7764	nan	0.9142	0.9451	0.0	0.6186	0.1507	nan	0.2335	0.0	0.9347	0.0	0.8687	0.0241	0.0002	nan	0.0009	0.9289	0.8030	0.9475	0.0017	nan	0.6043	0.8155	0.0	0.5849	0.1343	nan	0.2048	0.0	0.6435	0.0	0.5827	0.0237	0.0002	nan	0.0009	0.7982	0.6200	0.8673	0.0017
1.0999	3.6	360	0.8474	0.1929	0.2414	0.7839	nan	0.8855	0.9347	0.0	0.6642	0.3808	nan	0.3074	0.0	0.9337	0.0	0.8936	0.0268	0.0002	nan	0.0004	0.9290	0.8220	0.9447	0.0024	nan	0.6384	0.8318	0.0	0.6311	0.2329	nan	0.2537	0.0	0.6656	0.0	0.5779	0.0258	0.0002	nan	0.0004	0.8047	0.6379	0.8714	0.0024
0.816	3.8	380	0.8442	0.1917	0.2366	0.7831	nan	0.9172	0.9295	0.0015	0.7493	0.2377	nan	0.2120	0.0	0.9061	0.0	0.9053	0.0378	0.0003	nan	0.0009	0.9321	0.7829	0.9548	0.0026	nan	0.5939	0.8257	0.0015	0.6699	0.1996	nan	0.1907	0.0	0.7177	0.0	0.5648	0.0360	0.0003	nan	0.0009	0.8150	0.6483	0.8674	0.0025
0.9003	4.0	400	0.8233	0.1919	0.2370	0.7848	nan	0.8892	0.9518	0.0	0.6647	0.1693	nan	0.3036	0.0	0.9404	0.0	0.9003	0.0910	0.0000	nan	0.0013	0.9331	0.7968	0.9397	0.0022	nan	0.6287	0.8128	0.0	0.6271	0.1557	nan	0.2609	0.0	0.6628	0.0	0.5880	0.0818	0.0000	nan	0.0013	0.8126	0.6325	0.8758	0.0022
0.7778	4.2	420	0.7925	0.1972	0.2454	0.7892	nan	0.9090	0.9347	0.0001	0.7361	0.2301	nan	0.3810	0.0	0.9340	0.0	0.8904	0.1266	0.0	nan	0.0012	0.9272	0.8235	0.9520	0.0076	nan	0.6246	0.8376	0.0001	0.6689	0.1986	nan	0.3035	0.0	0.6892	0.0	0.5862	0.1070	0.0	nan	0.0012	0.7986	0.6204	0.8685	0.0075
0.899	4.4	440	0.7606	0.2060	0.2531	0.7973	nan	0.8648	0.9434	0.1829	0.8042	0.2714	nan	0.3663	0.0	0.9308	0.0	0.8921	0.1161	0.0003	nan	0.0027	0.9508	0.8108	0.9477	0.0137	nan	0.6480	0.8419	0.1826	0.6841	0.2257	nan	0.3034	0.0	0.6903	0.0	0.6016	0.1035	0.0003	nan	0.0027	0.7878	0.6293	0.8779	0.0132
0.6841	4.6	460	0.7973	0.2014	0.2483	0.7873	nan	0.9204	0.9272	0.1547	0.6196	0.3628	nan	0.2988	0.0	0.9301	0.0001	0.9242	0.1209	0.0002	nan	0.0029	0.9145	0.8211	0.9346	0.0120	nan	0.6063	0.8454	0.1545	0.6009	0.2465	nan	0.2563	0.0	0.7049	0.0001	0.5786	0.1054	0.0002	nan	0.0029	0.8180	0.6326	0.8801	0.0117
1.2605	4.8	480	0.7424	0.2123	0.2568	0.8034	nan	0.9291	0.9391	0.1931	0.7621	0.3437	nan	0.3891	0.0	0.8815	0.0	0.9208	0.1542	0.0001	nan	0.0048	0.9384	0.7947	0.9571	0.0105	nan	0.6587	0.8549	0.1928	0.6922	0.2696	nan	0.3224	0.0	0.7415	0.0	0.5842	0.1243	0.0001	nan	0.0048	0.8124	0.6504	0.8750	0.0101
0.994	5.0	500	0.7333	0.2170	0.2643	0.8052	nan	0.8760	0.9535	0.3456	0.7921	0.2858	nan	0.4148	0.0	0.9352	0.0002	0.9037	0.2191	0.0003	nan	0.0100	0.9152	0.8444	0.9473	0.0153	nan	0.6761	0.8452	0.3432	0.6936	0.2347	nan	0.3366	0.0	0.7100	0.0002	0.6097	0.1733	0.0003	nan	0.0099	0.8032	0.6107	0.8816	0.0147
0.7321	5.2	520	0.7160	0.2263	0.2736	0.8111	nan	0.9443	0.9291	0.6147	0.7516	0.3484	nan	0.3060	0.0	0.9343	0.0005	0.8990	0.2796	0.0000	nan	0.0136	0.9349	0.8179	0.9613	0.0189	nan	0.6707	0.8587	0.5867	0.6890	0.2695	nan	0.2547	0.0	0.6997	0.0005	0.6224	0.2093	0.0000	nan	0.0134	0.8189	0.6546	0.8752	0.0179
0.9296	5.4	540	0.7147	0.2204	0.2647	0.8066	nan	0.9196	0.9432	0.4123	0.7239	0.3169	nan	0.3739	0.0	0.9316	0.0012	0.8809	0.2266	0.0001	nan	0.0165	0.9516	0.7844	0.9520	0.0347	nan	0.6619	0.8529	0.4076	0.6882	0.2496	nan	0.3105	0.0	0.7040	0.0012	0.6195	0.1740	0.0001	nan	0.0163	0.7996	0.6519	0.8824	0.0318
0.9382	5.6	560	0.7137	0.2204	0.2637	0.8095	nan	0.9066	0.9550	0.3288	0.7654	0.2762	nan	0.3545	0.0000	0.9185	0.0013	0.8888	0.3129	0.0006	nan	0.0216	0.9551	0.7446	0.9564	0.0509	nan	0.6831	0.8469	0.3263	0.6973	0.2386	nan	0.3021	0.0000	0.7270	0.0013	0.6265	0.2280	0.0006	nan	0.0212	0.7953	0.6342	0.8766	0.0471
0.6986	5.8	580	0.6882	0.2345	0.2822	0.8170	nan	0.8645	0.9527	0.7182	0.7709	0.3762	nan	0.4519	0.0	0.9442	0.0023	0.8869	0.3314	0.0015	nan	0.0172	0.9455	0.7779	0.9483	0.0392	nan	0.7165	0.8569	0.6653	0.6990	0.2755	nan	0.3416	0.0	0.6888	0.0023	0.6298	0.2303	0.0015	nan	0.0171	0.8159	0.6428	0.8860	0.0351
0.8972	6.0	600	0.6787	0.2443	0.2940	0.8236	nan	0.8802	0.9427	0.8767	0.8092	0.3877	nan	0.4968	0.0150	0.9157	0.0035	0.8847	0.3532	0.0032	nan	0.0320	0.9481	0.8204	0.9580	0.0800	nan	0.7281	0.8594	0.7577	0.7131	0.2961	nan	0.3790	0.0150	0.7459	0.0035	0.6331	0.2472	0.0032	nan	0.0312	0.8075	0.6465	0.8810	0.0708
0.75	6.2	620	0.6978	0.2311	0.2768	0.8138	nan	0.9277	0.9356	0.4812	0.7453	0.3771	nan	0.3586	0.0109	0.9178	0.0070	0.9106	0.3588	0.0139	nan	0.0577	0.9386	0.8142	0.9568	0.0455	nan	0.6669	0.8588	0.4726	0.7026	0.2905	nan	0.3022	0.0108	0.7412	0.0070	0.6253	0.2459	0.0138	nan	0.0554	0.8239	0.6538	0.8827	0.0416
0.7238	6.4	640	0.6921	0.2331	0.2800	0.8147	nan	0.9216	0.9352	0.4890	0.7484	0.4188	nan	0.4427	0.0266	0.9355	0.0106	0.8999	0.3275	0.0267	nan	0.0543	0.9387	0.7734	0.9589	0.0513	nan	0.6714	0.8640	0.4757	0.6803	0.3131	nan	0.3628	0.0265	0.7130	0.0106	0.6219	0.2316	0.0263	nan	0.0523	0.8257	0.6586	0.8795	0.0466
0.5833	6.6	660	0.6680	0.2434	0.2907	0.8209	nan	0.9182	0.9398	0.7576	0.7565	0.3848	nan	0.3953	0.0343	0.9269	0.0134	0.8750	0.4709	0.0278	nan	0.0491	0.9433	0.8060	0.9492	0.0546	nan	0.6967	0.8553	0.6921	0.7087	0.3081	nan	0.3278	0.0342	0.7304	0.0134	0.6424	0.2905	0.0273	nan	0.0473	0.8193	0.6601	0.8867	0.0487
0.5218	6.8	680	0.6726	0.2413	0.2860	0.8175	nan	0.8930	0.9496	0.6173	0.7536	0.3542	nan	0.4279	0.1277	0.9206	0.0246	0.9026	0.3169	0.0265	nan	0.0621	0.9440	0.8055	0.9424	0.0839	nan	0.6802	0.8508	0.5782	0.6998	0.2820	nan	0.3461	0.1228	0.7390	0.0246	0.6346	0.2385	0.0264	nan	0.0593	0.8214	0.6545	0.8884	0.0741
0.5955	7.0	700	0.6468	0.2564	0.3087	0.8262	nan	0.8771	0.9432	0.8264	0.8013	0.4458	nan	0.4818	0.1418	0.9521	0.0656	0.8580	0.4580	0.0650	nan	0.0640	0.9304	0.8343	0.9563	0.1774	nan	0.7212	0.8625	0.7193	0.7127	0.3183	nan	0.3855	0.1368	0.7055	0.0648	0.6549	0.3069	0.0633	nan	0.0613	0.8251	0.6505	0.8825	0.1340
0.5739	7.2	720	0.6434	0.2587	0.3113	0.8291	nan	0.8944	0.9434	0.9029	0.7922	0.3975	nan	0.4644	0.1910	0.9402	0.0626	0.8690	0.4932	0.0647	nan	0.0688	0.9346	0.8511	0.9603	0.1304	nan	0.7325	0.8656	0.7542	0.7109	0.3125	nan	0.3797	0.1839	0.7246	0.0619	0.6469	0.3013	0.0613	nan	0.0656	0.8326	0.6516	0.8848	0.1093
0.6027	7.4	740	0.6557	0.2556	0.2999	0.8262	nan	0.8995	0.9631	0.7892	0.7427	0.3508	nan	0.3713	0.2315	0.9317	0.0584	0.8991	0.3681	0.0825	nan	0.0979	0.9371	0.7934	0.9561	0.1230	nan	0.7203	0.8467	0.7120	0.7129	0.2943	nan	0.3196	0.2146	0.7289	0.0578	0.6533	0.2772	0.0802	nan	0.0905	0.8306	0.6513	0.8871	0.1006
0.8635	7.6	760	0.6398	0.2613	0.3157	0.8290	nan	0.9072	0.9301	0.9185	0.8533	0.3920	nan	0.4355	0.3284	0.9269	0.0599	0.8617	0.4597	0.0480	nan	0.0968	0.9496	0.8371	0.9551	0.1431	nan	0.7332	0.8639	0.7654	0.6976	0.3201	nan	0.3539	0.2469	0.7554	0.0592	0.6527	0.2922	0.0473	nan	0.0884	0.8129	0.6549	0.8908	0.1266
0.6496	7.8	780	0.6365	0.2629	0.3127	0.8290	nan	0.8686	0.9465	0.7677	0.8536	0.4537	nan	0.4583	0.3666	0.9369	0.1020	0.8909	0.3822	0.0318	nan	0.1149	0.9481	0.7742	0.9603	0.1502	nan	0.7294	0.8625	0.7022	0.7239	0.3302	nan	0.3684	0.3024	0.7376	0.0990	0.6554	0.2685	0.0316	nan	0.1029	0.8192	0.6604	0.8895	0.1284
0.6041	8.0	800	0.6289	0.2690	0.3187	0.8306	nan	0.8860	0.9554	0.7871	0.7839	0.4422	nan	0.5050	0.3687	0.9286	0.1653	0.9036	0.4388	0.1136	nan	0.1061	0.9162	0.8208	0.9398	0.1389	nan	0.7384	0.8597	0.7174	0.7281	0.3427	nan	0.3879	0.3043	0.7494	0.1608	0.6435	0.2856	0.1065	nan	0.0981	0.8360	0.6405	0.8932	0.1161
0.6099	8.2	820	0.6338	0.2653	0.3147	0.8302	nan	0.9012	0.9499	0.8518	0.7988	0.4303	nan	0.4579	0.3921	0.9365	0.1505	0.9113	0.3259	0.0905	nan	0.1020	0.9264	0.8126	0.9546	0.0767	nan	0.7325	0.8630	0.7540	0.7230	0.3324	nan	0.3795	0.3205	0.7310	0.1447	0.6351	0.2476	0.0880	nan	0.0946	0.8309	0.6540	0.8918	0.0685
0.6858	8.4	840	0.6176	0.2727	0.3272	0.8315	nan	0.8970	0.9361	0.6210	0.8360	0.5020	nan	0.4828	0.5011	0.9481	0.2708	0.8869	0.4442	0.1712	nan	0.1149	0.9375	0.8185	0.9484	0.1527	nan	0.7263	0.8637	0.5873	0.7529	0.3376	nan	0.3895	0.3386	0.7353	0.2448	0.6696	0.3168	0.1550	nan	0.1039	0.8367	0.6538	0.8927	0.1232
0.6531	8.6	860	0.6370	0.2644	0.3128	0.8258	nan	0.9324	0.9343	0.5194	0.7938	0.3908	nan	0.4002	0.4282	0.9271	0.2175	0.9178	0.3614	0.2248	nan	0.1156	0.9408	0.8006	0.9496	0.1566	nan	0.6934	0.8602	0.5038	0.7359	0.3133	nan	0.3111	0.3246	0.7598	0.2058	0.6486	0.2861	0.2026	nan	0.1050	0.8320	0.6571	0.8937	0.1294
0.5632	8.8	880	0.6063	0.2706	0.3212	0.8333	nan	0.8873	0.9528	0.6705	0.8456	0.3799	nan	0.4931	0.4676	0.9319	0.1946	0.9060	0.4150	0.1442	nan	0.1152	0.9369	0.8201	0.9555	0.1624	nan	0.7309	0.8593	0.6114	0.7686	0.3150	nan	0.3780	0.3287	0.7604	0.1880	0.6545	0.3036	0.1366	nan	0.1053	0.8320	0.6560	0.8926	0.1392
0.4938	9.0	900	0.5913	0.2811	0.3380	0.8400	nan	0.9149	0.9453	0.8592	0.8568	0.4296	nan	0.5092	0.5560	0.9324	0.1780	0.8727	0.5077	0.1659	nan	0.1450	0.9255	0.8496	0.9553	0.2134	nan	0.7534	0.8710	0.7813	0.7691	0.3445	nan	0.4054	0.3232	0.7709	0.1689	0.6761	0.3299	0.1513	nan	0.1275	0.8278	0.6306	0.8937	0.1716
0.6084	9.2	920	0.6219	0.2720	0.3252	0.8306	nan	0.9198	0.9455	0.5757	0.8045	0.4044	nan	0.4738	0.4906	0.9459	0.2000	0.8611	0.5321	0.1744	nan	0.1593	0.9196	0.8566	0.9539	0.1906	nan	0.7067	0.8681	0.5550	0.7480	0.3208	nan	0.3844	0.3881	0.7384	0.1840	0.6832	0.3374	0.1623	nan	0.1378	0.8286	0.6204	0.8947	0.1474
0.5805	9.4	940	0.6033	0.2867	0.3480	0.8397	nan	0.8840	0.9532	0.8587	0.8534	0.4369	nan	0.5326	0.5907	0.9450	0.2965	0.8207	0.5159	0.3006	nan	0.2309	0.9335	0.8432	0.9674	0.1719	nan	0.7478	0.8640	0.7454	0.7692	0.3472	nan	0.4128	0.3069	0.7446	0.2557	0.6807	0.3544	0.2698	nan	0.1808	0.8311	0.6403	0.8859	0.1388
0.4958	9.6	960	0.5846	0.2840	0.3419	0.8392	nan	0.8722	0.9386	0.7446	0.9280	0.4916	nan	0.5107	0.5636	0.9397	0.2787	0.8970	0.4487	0.2418	nan	0.1890	0.9323	0.8306	0.9605	0.1744	nan	0.7488	0.8719	0.6737	0.7609	0.3558	nan	0.4104	0.3626	0.7518	0.25	0.6659	0.3196	0.2210	nan	0.1581	0.8361	0.6639	0.8925	0.1459
0.416	9.8	980	0.5922	0.2879	0.3410	0.8405	nan	0.9014	0.9449	0.7773	0.8275	0.5238	nan	0.4849	0.5017	0.9515	0.2970	0.8585	0.4794	0.2724	nan	0.1701	0.9464	0.8089	0.9515	0.2160	nan	0.7563	0.8703	0.6971	0.7671	0.3722	nan	0.3951	0.4059	0.7363	0.2624	0.6771	0.3319	0.2444	nan	0.1450	0.8332	0.6615	0.8961	0.1610
0.6568	10.0	1000	0.6196	0.2829	0.3402	0.8339	nan	0.9294	0.9465	0.5724	0.7751	0.3923	nan	0.4631	0.5738	0.9311	0.3993	0.8545	0.5548	0.3041	nan	0.1759	0.9261	0.8513	0.9579	0.2784	nan	0.6917	0.8729	0.5430	0.7282	0.3262	nan	0.3755	0.3570	0.7781	0.3427	0.6869	0.3621	0.2653	nan	0.1499	0.8342	0.6394	0.8956	0.2050
0.9212	10.2	1020	0.5826	0.2895	0.3511	0.8386	nan	0.8980	0.9412	0.7761	0.8219	0.5323	nan	0.5409	0.5867	0.9415	0.3908	0.8639	0.5240	0.2341	nan	0.1964	0.9138	0.8470	0.9613	0.2644	nan	0.7342	0.8731	0.7084	0.7225	0.3868	nan	0.4194	0.3600	0.7585	0.3250	0.6847	0.3390	0.2138	nan	0.1674	0.8369	0.6443	0.8959	0.1930
0.7189	10.4	1040	0.5878	0.2942	0.3532	0.8435	nan	0.8554	0.9567	0.8247	0.9302	0.4438	nan	0.5043	0.5802	0.9436	0.4169	0.8659	0.4856	0.3351	nan	0.2105	0.9270	0.8323	0.9661	0.2226	nan	0.7523	0.8647	0.7360	0.7761	0.3501	nan	0.3984	0.3679	0.7655	0.3453	0.6895	0.3496	0.2909	nan	0.1737	0.8411	0.6511	0.8906	0.1714

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

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Jul 24, 2025
Updated: Jul 24, 2025