segformer-finetuned-sidewalk-10k-steps

adolf669/segformer-finetuned-sidewalk-10k-steps

segformer-finetuned-sidewalk-10k-steps is a image segmentation model from adolf669. 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. --

Downloads · 30 days

4% of all-time downloads

All-time downloads

874

Public

Parameters

3.7M

2.7 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors14.9 MB · 87%

At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: Nov 23, 2024
Updated: Nov 24, 2024
SHA: 2cddf891

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: 0.5890
Mean Iou: 0.3100
Mean Accuracy: 0.3785
Overall Accuracy: 0.8340
Accuracy Unlabeled: nan
Accuracy Flat-road: 0.7750
Accuracy Flat-sidewalk: 0.9476
Accuracy Flat-crosswalk: 0.7198
Accuracy Flat-cyclinglane: 0.8649
Accuracy Flat-parkingdriveway: 0.2833
Accuracy Flat-railtrack: nan
Accuracy Flat-curb: 0.4461
Accuracy Human-person: 0.6623
Accuracy Human-rider: 0.0
Accuracy Vehicle-car: 0.9432
Accuracy Vehicle-truck: 0.0
Accuracy Vehicle-bus: 0.0
Accuracy Vehicle-tramtrain: 0.0
Accuracy Vehicle-motorcycle: 0.0
Accuracy Vehicle-bicycle: 0.7612
Accuracy Vehicle-caravan: 0.0
Accuracy Vehicle-cartrailer: 0.0
Accuracy Construction-building: 0.8657
Accuracy Construction-door: 0.0
Accuracy Construction-wall: 0.5605
Accuracy Construction-fenceguardrail: 0.5325
Accuracy Construction-bridge: 0.0
Accuracy Construction-tunnel: nan
Accuracy Construction-stairs: 0.0
Accuracy Object-pole: 0.3362
Accuracy Object-trafficsign: 0.0
Accuracy Object-trafficlight: 0.0
Accuracy Nature-vegetation: 0.8960
Accuracy Nature-terrain: 0.8673
Accuracy Sky: 0.9590
Accuracy Void-ground: 0.0
Accuracy Void-dynamic: 0.3077
Accuracy Void-static: 0.3834
Accuracy Void-unclear: 0.0
Iou Unlabeled: nan
Iou Flat-road: 0.6597
Iou Flat-sidewalk: 0.8220
Iou Flat-crosswalk: 0.6669
Iou Flat-cyclinglane: 0.7094
Iou Flat-parkingdriveway: 0.2634
Iou Flat-railtrack: nan
Iou Flat-curb: 0.2962
Iou Human-person: 0.4612
Iou Human-rider: 0.0
Iou Vehicle-car: 0.8019
Iou Vehicle-truck: 0.0
Iou Vehicle-bus: 0.0
Iou Vehicle-tramtrain: 0.0
Iou Vehicle-motorcycle: 0.0
Iou Vehicle-bicycle: 0.4166
Iou Vehicle-caravan: 0.0
Iou Vehicle-cartrailer: 0.0
Iou Construction-building: 0.6806
Iou Construction-door: 0.0
Iou Construction-wall: 0.4268
Iou Construction-fenceguardrail: 0.4087
Iou Construction-bridge: 0.0
Iou Construction-tunnel: nan
Iou Construction-stairs: 0.0
Iou Object-pole: 0.2241
Iou Object-trafficsign: 0.0
Iou Object-trafficlight: 0.0
Iou Nature-vegetation: 0.8381
Iou Nature-terrain: 0.7739
Iou Sky: 0.9036
Iou Void-ground: 0.0
Iou Void-dynamic: 0.2473
Iou Void-static: 0.3211
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: 3407
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: polynomial
training_steps: 10000

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-dynamic	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-dynamic	Iou Void-static
2.6262	1.0	107	1.8030	0.1150	0.1631	0.6678	nan	0.4682	0.9266	0.0	0.1510	0.0020	nan	0.0000	0.0	0.8961	0.0	0.7523	0.0	0.0	nan	0.0000	0.9321	0.7060	0.3833	0.0	0.0	nan	0.3811	0.6887	0.0	0.1495	0.0020	nan	0.0000	0.0	0.4861	0.0	0.4729	0.0	0.0	nan	0.0000	0.6066	0.5402	0.3543	0.0	0.0
1.8747	2.0	214	1.5625	0.1290	0.1774	0.6759	nan	0.5144	0.9502	0.0	0.2435	0.0107	nan	0.0000	0.0	0.8290	0.0	0.8706	0.0	0.0	nan	0.0	0.6522	0.8882	0.7181	0.0	0.0	nan	0.4081	0.6930	0.0	0.2399	0.0106	nan	0.0000	0.0	0.6241	0.0	0.5101	0.0	0.0	nan	0.0	0.5405	0.4174	0.6840	0.0	0.0
1.4981	3.0	321	1.2528	0.1500	0.2000	0.7230	nan	0.7317	0.9017	0.0	0.5385	0.0352	nan	0.0	0.0	0.9288	0.0	0.7741	0.0001	0.0	nan	0.0000	0.8453	0.8460	0.7985	0.0	0.0	nan	0.4742	0.7460	0.0	0.4950	0.0322	nan	0.0	0.0	0.5423	0.0	0.5264	0.0001	0.0	nan	0.0000	0.6792	0.5807	0.7242	0.0	0.0
1.3616	4.0	428	1.1121	0.1538	0.2064	0.7329	nan	0.6492	0.9195	0.0	0.6889	0.0578	nan	0.0	0.0	0.9435	0.0	0.7840	0.0000	0.0	nan	0.0008	0.8478	0.8760	0.8387	0.0	0.0	nan	0.4697	0.7686	0.0	0.5062	0.0538	nan	0.0	0.0	0.5448	0.0	0.5363	0.0000	0.0	nan	0.0008	0.6882	0.5835	0.7687	0.0	0.0
1.2402	5.0	535	0.9807	0.1617	0.2044	0.7432	nan	0.6175	0.9496	0.0	0.6074	0.0402	nan	0.0	0.0	0.9149	0.0	0.9186	0.0000	0.0	nan	0.0	0.8532	0.7998	0.8388	0.0	0.0	nan	0.5019	0.7449	0.0	0.5470	0.0378	nan	0.0	0.0	0.6501	0.0	0.5055	0.0000	0.0	nan	0.0	0.7337	0.6708	0.7837	0.0	0.0
1.1318	6.0	642	1.0385	0.1477	0.2019	0.7068	nan	0.4984	0.9470	0.0	0.7702	0.0691	nan	0.0	0.0	0.9543	0.0	0.8840	0.0178	0.0	nan	0.0005	0.6212	0.8926	0.8047	0.0	0.0	nan	0.4191	0.7292	0.0	0.5835	0.0601	nan	0.0	0.0	0.6061	0.0	0.5407	0.0177	0.0	nan	0.0005	0.5770	0.4410	0.7513	0.0	0.0
1.0574	7.0	749	0.9046	0.1690	0.2127	0.7531	nan	0.6171	0.9520	0.0115	0.7032	0.0985	nan	0.0020	0.0	0.9373	0.0	0.8779	0.0486	0.0	nan	0.0169	0.8670	0.8317	0.8423	0.0	0.0	nan	0.4908	0.7535	0.0115	0.6164	0.0845	nan	0.0020	0.0	0.6419	0.0	0.5622	0.0479	0.0	nan	0.0166	0.7327	0.6574	0.7922	0.0	0.0
0.9759	8.0	856	0.8881	0.1756	0.2189	0.7547	nan	0.5985	0.9566	0.1262	0.7070	0.0835	nan	0.0258	0.0	0.9402	0.0	0.8847	0.1283	0.0001	nan	0.0597	0.8756	0.7936	0.8249	0.0	0.0	nan	0.5068	0.7552	0.1260	0.5858	0.0748	nan	0.0248	0.0	0.6569	0.0	0.5553	0.1171	0.0001	nan	0.0558	0.7294	0.6463	0.7841	0.0	0.0
0.9478	9.0	963	0.8427	0.1792	0.2281	0.7627	nan	0.6444	0.9385	0.1576	0.8233	0.1084	nan	0.0637	0.0	0.9471	0.0	0.9072	0.1206	0.0010	nan	0.0478	0.8482	0.8364	0.8557	0.0	0.0001	nan	0.5283	0.7850	0.1503	0.5470	0.0989	nan	0.0594	0.0	0.6174	0.0	0.5622	0.1114	0.0010	nan	0.0438	0.7500	0.6754	0.8027	0.0	0.0001
0.9357	10.0	1070	0.8261	0.1919	0.2394	0.7663	nan	0.7330	0.9060	0.2756	0.7705	0.0660	nan	0.1561	0.0018	0.9329	0.0039	0.8534	0.2518	0.0002	nan	0.0967	0.9051	0.8362	0.8711	0.0	0.0002	nan	0.5551	0.7720	0.2581	0.6407	0.0623	nan	0.1264	0.0018	0.6682	0.0039	0.5674	0.2233	0.0002	nan	0.0776	0.7281	0.6464	0.8107	0.0	0.0002
0.8472	11.0	1177	0.7976	0.2078	0.2573	0.7708	nan	0.6694	0.9321	0.6020	0.7892	0.0857	nan	0.1836	0.0318	0.9266	0.0	0.8658	0.4413	0.0004	nan	0.1099	0.8505	0.8369	0.9076	0.0	0.0022	nan	0.5349	0.7639	0.5201	0.6244	0.0777	nan	0.1394	0.0313	0.6994	0.0	0.5838	0.3358	0.0004	nan	0.0885	0.7588	0.6643	0.8232	0.0	0.0022
0.8613	12.0	1284	0.7624	0.2053	0.2580	0.7782	nan	0.7226	0.9281	0.1215	0.7176	0.1899	nan	0.3386	0.0810	0.9500	0.0216	0.8083	0.5341	0.0030	nan	0.2061	0.8630	0.8930	0.8579	0.0	0.0188	nan	0.5747	0.7922	0.1206	0.6327	0.1671	nan	0.2062	0.0747	0.6546	0.0214	0.6156	0.3586	0.0030	nan	0.1199	0.7451	0.6452	0.8198	0.0	0.0183
0.7847	13.0	1391	0.7713	0.2170	0.2694	0.7725	nan	0.6374	0.9509	0.6615	0.5478	0.1946	nan	0.3358	0.2063	0.9425	0.0670	0.8683	0.4287	0.0321	nan	0.1353	0.8484	0.8816	0.8796	0.0	0.0039	nan	0.5472	0.7772	0.5301	0.4776	0.1689	nan	0.2091	0.1927	0.6819	0.0665	0.6125	0.3472	0.0320	nan	0.1017	0.7452	0.6313	0.8206	0.0	0.0039
0.8041	14.0	1498	0.7236	0.2310	0.2877	0.7880	nan	0.6190	0.9472	0.5927	0.8157	0.1877	nan	0.3897	0.3524	0.9307	0.1085	0.7989	0.5597	0.0130	nan	0.1964	0.9106	0.8640	0.9053	0.0	0.0136	nan	0.5518	0.7940	0.4508	0.6548	0.1720	nan	0.2188	0.3054	0.7232	0.1064	0.6219	0.3678	0.0129	nan	0.1153	0.7713	0.6756	0.8352	0.0	0.0133
0.74	15.0	1605	0.7429	0.2275	0.2771	0.7791	nan	0.6285	0.9519	0.4719	0.6291	0.1591	nan	0.3397	0.4511	0.9334	0.1813	0.8426	0.4337	0.0407	nan	0.1488	0.9095	0.8395	0.9037	0.0	0.0042	nan	0.5371	0.7690	0.4183	0.5169	0.1449	nan	0.2088	0.3547	0.7256	0.1607	0.6329	0.3753	0.0401	nan	0.1064	0.7613	0.6850	0.8378	0.0	0.0042
0.7184	16.0	1712	0.6646	0.2439	0.2964	0.8029	nan	0.7431	0.9484	0.4972	0.8103	0.2001	nan	0.3258	0.4629	0.9401	0.1821	0.8279	0.6112	0.0110	nan	0.2345	0.8917	0.8616	0.9063	0.0	0.0313	nan	0.6165	0.8048	0.4637	0.6925	0.1798	nan	0.2280	0.3680	0.7181	0.1722	0.6472	0.3937	0.0109	nan	0.1451	0.7831	0.7086	0.8424	0.0	0.0293
0.7496	17.0	1819	0.7000	0.2385	0.2948	0.7852	nan	0.6870	0.9552	0.5478	0.8104	0.2046	nan	0.3326	0.5163	0.9477	0.1966	0.8765	0.5327	0.0835	nan	0.2037	0.7682	0.8842	0.8746	0.0	0.0112	nan	0.6047	0.7973	0.4943	0.6625	0.1800	nan	0.2414	0.3971	0.7056	0.1848	0.6271	0.4151	0.0821	nan	0.1296	0.7041	0.5693	0.8255	0.0	0.0103
0.6723	18.0	1926	0.6689	0.2487	0.3028	0.8022	nan	0.7140	0.9462	0.5937	0.8259	0.1957	nan	0.3702	0.5214	0.9200	0.2293	0.8539	0.4865	0.1947	nan	0.1763	0.9082	0.8340	0.9089	0.0	0.0120	nan	0.5970	0.8087	0.4665	0.6640	0.1781	nan	0.2503	0.3889	0.7549	0.2088	0.6258	0.3857	0.1777	nan	0.1182	0.7836	0.6927	0.8458	0.0	0.0116
0.6711	19.0	2033	0.7171	0.2410	0.2989	0.7914	nan	0.6550	0.9565	0.2743	0.8302	0.1406	nan	0.2934	0.6023	0.9349	0.2585	0.8100	0.6473	0.1674	nan	0.2790	0.8745	0.8440	0.9106	0.0	0.0875	nan	0.5597	0.7818	0.2558	0.6593	0.1321	nan	0.1980	0.3907	0.7384	0.2201	0.6550	0.4454	0.1541	nan	0.1459	0.7737	0.6716	0.8494	0.0	0.0804
0.6843	20.0	2140	0.6734	0.2490	0.3017	0.7990	nan	0.6756	0.9455	0.4783	0.7881	0.2300	nan	0.3708	0.5272	0.9268	0.3415	0.8824	0.5309	0.1064	nan	0.1958	0.8984	0.8616	0.8828	0.0	0.0131	nan	0.5749	0.8016	0.4521	0.6371	0.2040	nan	0.2474	0.4068	0.7496	0.2855	0.6350	0.3958	0.1030	nan	0.1338	0.7849	0.6948	0.8482	0.0	0.0127
0.6635	21.0	2247	0.6890	0.2588	0.3264	0.7921	nan	0.8326	0.8628	0.5588	0.8419	0.2679	nan	0.3243	0.6557	0.9472	0.3776	0.7708	0.5574	0.1780	nan	0.3384	0.9255	0.8385	0.8964	0.0	0.2726	nan	0.5749	0.7876	0.4791	0.6054	0.2392	nan	0.1911	0.4287	0.7368	0.2660	0.6472	0.3842	0.1686	nan	0.2159	0.7949	0.7123	0.8570	0.0	0.1917
0.6789	22.0	2354	0.6569	0.2518	0.3098	0.8048	nan	0.6906	0.9488	0.2921	0.8276	0.2066	nan	0.3660	0.7073	0.9234	0.2937	0.8247	0.6251	0.1025	nan	0.2306	0.9155	0.8941	0.8789	0.0	0.1853	nan	0.5897	0.7929	0.2851	0.7088	0.1866	nan	0.2519	0.3796	0.7649	0.2501	0.6571	0.4087	0.0996	nan	0.1627	0.7933	0.7197	0.8451	0.0	0.1610
0.6454	23.0	2461	0.6744	0.2605	0.3209	0.8028	nan	0.7072	0.9467	0.5200	0.8210	0.1523	nan	0.3109	0.6300	0.8984	0.5537	0.8196	0.5994	0.2228	nan	0.3040	0.9410	0.7925	0.9118	0.0	0.1383	nan	0.5906	0.8004	0.4780	0.7242	0.1412	nan	0.2191	0.3835	0.7780	0.3617	0.6282	0.3930	0.2002	nan	0.1673	0.7889	0.7080	0.8552	0.0	0.1194
0.6038	24.0	2568	0.6785	0.2519	0.3080	0.7982	nan	0.6396	0.9585	0.4631	0.8241	0.1844	nan	0.3288	0.6904	0.9496	0.2838	0.8668	0.5447	0.1331	nan	0.1784	0.8765	0.8686	0.8889	0.0	0.1761	nan	0.5546	0.7909	0.4552	0.6615	0.1639	nan	0.2402	0.4092	0.7445	0.2344	0.6467	0.3978	0.1283	nan	0.1413	0.7854	0.7015	0.8537	0.0	0.1505
0.5843	25.0	2675	0.6425	0.2625	0.3200	0.8138	nan	0.7555	0.9393	0.5554	0.8420	0.1744	nan	0.3761	0.6702	0.9562	0.2860	0.8611	0.5607	0.1917	nan	0.1636	0.9036	0.8870	0.9333	0.0	0.1841	nan	0.6111	0.8171	0.5276	0.6873	0.1643	nan	0.2403	0.4126	0.7284	0.2312	0.6629	0.4188	0.1843	nan	0.1315	0.8117	0.7419	0.8673	0.0	0.1604
0.6123	26.0	2782	0.6211	0.2684	0.3346	0.8108	nan	0.7087	0.9396	0.7111	0.8640	0.2795	nan	0.3913	0.6719	0.9391	0.5103	0.8288	0.5326	0.1613	nan	0.2742	0.8939	0.9020	0.9356	0.0	0.1632	nan	0.6169	0.8093	0.5850	0.6558	0.2548	nan	0.2581	0.4340	0.7676	0.3224	0.6583	0.3977	0.1580	nan	0.1779	0.7857	0.6936	0.8708	0.0	0.1444
0.6164	27.0	2889	0.6278	0.2692	0.3328	0.8106	nan	0.7301	0.9259	0.4546	0.8241	0.2859	nan	0.4266	0.7477	0.9314	0.4932	0.8171	0.6465	0.2815	nan	0.2226	0.9394	0.8207	0.9307	0.0	0.1704	nan	0.5995	0.8124	0.4500	0.6896	0.2528	nan	0.2576	0.4422	0.7626	0.3378	0.6537	0.4146	0.2460	nan	0.1643	0.7946	0.7199	0.8725	0.0	0.1457
0.5928	28.0	2996	0.6444	0.2560	0.3123	0.8032	nan	0.7225	0.9455	0.5826	0.7252	0.2540	nan	0.3636	0.6262	0.9521	0.4389	0.8869	0.5355	0.2178	nan	0.1197	0.9124	0.7629	0.8912	0.0	0.0572	nan	0.6153	0.7979	0.4936	0.6398	0.2297	nan	0.2420	0.4290	0.7238	0.2985	0.6188	0.3818	0.1974	nan	0.1012	0.8042	0.7110	0.8555	0.0	0.0540
0.6063	29.0	3103	0.6164	0.2670	0.3287	0.8098	nan	0.7636	0.9203	0.5298	0.8515	0.2476	nan	0.3554	0.6410	0.9332	0.5947	0.8756	0.4557	0.1954	nan	0.1901	0.9170	0.8145	0.9374	0.0	0.2956	nan	0.6094	0.8098	0.4908	0.6464	0.2266	nan	0.2439	0.4621	0.7694	0.3324	0.6464	0.3436	0.1845	nan	0.1395	0.8088	0.7230	0.8753	0.0	0.2309
0.5813	30.0	3210	0.6119	0.2729	0.3411	0.8105	nan	0.6853	0.9401	0.6264	0.8606	0.2528	nan	0.4579	0.5719	0.9117	0.6665	0.7954	0.7055	0.1902	nan	0.2144	0.9307	0.8167	0.9228	0.0	0.3674	nan	0.6009	0.8068	0.5336	0.6663	0.2257	nan	0.2688	0.4321	0.7877	0.3381	0.6567	0.3964	0.1782	nan	0.1573	0.8086	0.7333	0.8815	0.0	0.2611
0.5753	31.0	3317	0.6142	0.2692	0.3382	0.8144	nan	0.7397	0.9468	0.1591	0.8381	0.2301	nan	0.4275	0.6882	0.9288	0.6825	0.8008	0.5789	0.3769	nan	0.3456	0.9055	0.8430	0.9436	0.0	0.3874	nan	0.6312	0.8057	0.1547	0.6974	0.2115	nan	0.2538	0.4668	0.7752	0.3349	0.6634	0.4402	0.3100	nan	0.1839	0.8163	0.7392	0.8800	0.0	0.2488
0.5493	32.0	3424	0.6291	0.2726	0.3368	0.8115	nan	0.6741	0.9459	0.5440	0.8585	0.2403	nan	0.3326	0.6183	0.9290	0.6009	0.8325	0.6410	0.3244	nan	0.2637	0.9228	0.8354	0.9401	0.0	0.2739	nan	0.5865	0.8026	0.5007	0.6228	0.2209	nan	0.2419	0.4515	0.7720	0.3170	0.6730	0.4396	0.2779	nan	0.1709	0.8131	0.7372	0.8849	0.0	0.2112
0.572	33.0	3531	0.6095	0.2716	0.3339	0.8132	nan	0.7679	0.9161	0.4917	0.8535	0.2678	nan	0.3628	0.6298	0.9277	0.5765	0.8717	0.5620	0.3133	nan	0.2658	0.9195	0.8374	0.9406	0.0	0.1813	nan	0.6048	0.8106	0.4751	0.6478	0.2494	nan	0.2390	0.4547	0.7739	0.3014	0.6518	0.4310	0.2716	nan	0.1825	0.8197	0.7451	0.8871	0.0	0.1444
0.5659	34.0	3638	0.5995	0.2738	0.3390	0.8154	nan	0.7757	0.9180	0.4547	0.8543	0.2850	nan	0.4562	0.6517	0.9198	0.6006	0.8648	0.5829	0.3047	nan	0.3037	0.9198	0.7874	0.9499	0.0	0.2188	nan	0.6275	0.8164	0.4468	0.6083	0.2625	nan	0.2727	0.4371	0.7805	0.3290	0.6634	0.4357	0.2797	nan	0.2018	0.8151	0.7264	0.8810	0.0	0.1772
0.5575	35.0	3745	0.5962	0.2682	0.3311	0.8191	nan	0.7740	0.9371	0.2343	0.8567	0.2454	nan	0.3847	0.7019	0.9294	0.6050	0.8382	0.5856	0.2783	nan	0.2568	0.9207	0.8675	0.9434	0.0	0.2367	nan	0.6334	0.8124	0.2298	0.6599	0.2273	nan	0.2663	0.4582	0.7808	0.3277	0.6675	0.4400	0.2565	nan	0.1763	0.8190	0.7467	0.8883	0.0	0.1938
0.5385	36.0	3852	0.6016	0.2774	0.3421	0.8201	nan	0.7738	0.9329	0.5348	0.8502	0.2559	nan	0.4350	0.6830	0.9382	0.5540	0.8252	0.5325	0.3373	nan	0.2487	0.9255	0.8700	0.9223	0.0	0.3264	nan	0.6329	0.8225	0.5163	0.6751	0.2349	nan	0.2794	0.4422	0.7515	0.2940	0.6535	0.4284	0.2885	nan	0.1702	0.8221	0.7615	0.8847	0.0	0.2205
0.5514	37.0	3959	0.5875	0.2765	0.3385	0.8182	nan	0.7511	0.9456	0.7456	0.8527	0.1887	nan	0.3801	0.6007	0.9364	0.5184	0.8594	0.5793	0.3400	nan	0.2364	0.9123	0.8157	0.9486	0.0005	0.2218	nan	0.6242	0.8136	0.6078	0.6635	0.1786	nan	0.2639	0.4478	0.7892	0.2984	0.6629	0.4149	0.2929	nan	0.1679	0.8203	0.7379	0.8733	0.0005	0.1913
0.5646	38.0	4066	0.5851	0.2778	0.3461	0.8213	nan	0.7679	0.9433	0.2984	0.8542	0.2606	nan	0.4306	0.6745	0.9418	0.6483	0.7969	0.6172	0.4199	nan	0.3028	0.9174	0.8176	0.9435	0.0	0.4390	nan	0.6480	0.8126	0.2820	0.6944	0.2379	nan	0.2893	0.4644	0.7608	0.3057	0.6647	0.4662	0.3524	nan	0.2084	0.8224	0.7383	0.8829	0.0	0.2589
0.5159	39.0	4173	0.5972	0.2695	0.3261	0.8223	nan	0.8123	0.9386	0.1507	0.8524	0.2827	nan	0.3794	0.5939	0.9299	0.5320	0.8163	0.5226	0.2399	nan	0.2565	0.9301	0.8507	0.9229	0.0343	0.3888	nan	0.6372	0.8230	0.1498	0.7153	0.2585	nan	0.2692	0.4527	0.7899	0.3226	0.6551	0.4115	0.2302	nan	0.1851	0.8199	0.7428	0.8828	0.0338	0.2433
0.5437	40.0	4280	0.6458	0.2638	0.3251	0.8133	nan	0.7190	0.9530	0.1568	0.8506	0.2216	nan	0.3876	0.6859	0.9265	0.5604	0.8024	0.5051	0.3324	nan	0.3104	0.9478	0.7896	0.9378	0.0034	0.3133	nan	0.6243	0.8034	0.1541	0.6898	0.2043	nan	0.2718	0.4106	0.7866	0.3329	0.6448	0.3972	0.2899	nan	0.2032	0.8065	0.7190	0.8874	0.0033	0.2121
0.4939	41.0	4387	0.5953	0.2727	0.3344	0.8254	nan	0.7959	0.9461	0.1852	0.8392	0.2900	nan	0.4223	0.6795	0.9282	0.6097	0.8611	0.4823	0.3292	nan	0.3134	0.9086	0.8670	0.9295	0.0145	0.2979	nan	0.6661	0.8216	0.1796	0.7319	0.2653	nan	0.2834	0.4419	0.7931	0.3199	0.6450	0.3787	0.2909	nan	0.2106	0.8306	0.7667	0.8830	0.0140	0.2050
0.506	42.0	4494	0.5911	0.2708	0.3345	0.8198	nan	0.7873	0.9425	0.2025	0.8426	0.2298	nan	0.4588	0.6948	0.9262	0.6237	0.8128	0.5311	0.3261	nan	0.2602	0.9298	0.8085	0.9480	0.0	0.3804	nan	0.6450	0.8105	0.1975	0.7161	0.2125	nan	0.2897	0.4452	0.7978	0.3305	0.6536	0.3841	0.2815	nan	0.1810	0.8288	0.7434	0.8883	0.0	0.2588
0.509	43.0	4601	0.5833	0.2868	0.3498	0.8205	nan	0.7739	0.9379	0.5441	0.8511	0.2662	nan	0.4565	0.6319	0.9412	0.5537	0.8590	0.4568	0.4407	nan	0.3014	0.8854	0.8643	0.9519	0.2006	0.2775	nan	0.6424	0.8171	0.5156	0.6938	0.2412	nan	0.2817	0.4313	0.7883	0.3691	0.6494	0.3882	0.3200	nan	0.1917	0.8231	0.7458	0.8888	0.1764	0.2126
0.492	44.0	4708	0.5778	0.2894	0.3492	0.8279	nan	0.7784	0.9384	0.4728	0.8394	0.3692	nan	0.4454	0.6222	0.9326	0.6000	0.8719	0.5171	0.3511	nan	0.2849	0.9081	0.8644	0.9380	0.1613	0.2784	nan	0.6517	0.8181	0.4574	0.7044	0.3303	nan	0.2926	0.4394	0.7927	0.3677	0.6662	0.3997	0.2946	nan	0.1834	0.8346	0.7660	0.8938	0.1488	0.2201
0.4965	45.0	4815	0.5756	0.2907	0.3584	0.8280	nan	0.7832	0.9404	0.5044	0.8364	0.3479	nan	0.4872	0.6981	0.9539	0.5872	0.8024	0.5819	0.4517	nan	0.3394	0.9036	0.8622	0.9505	0.0307	0.4088	nan	0.6637	0.8233	0.4888	0.7297	0.3113	nan	0.2962	0.4542	0.7496	0.3476	0.6544	0.4196	0.3478	nan	0.2141	0.8337	0.7634	0.8923	0.0300	0.2841
0.5002	46.0	4922	0.5911	0.2876	0.3519	0.8241	nan	0.7498	0.9490	0.6335	0.8538	0.2570	nan	0.4053	0.6984	0.9179	0.6869	0.8449	0.5818	0.3487	nan	0.3070	0.9241	0.8325	0.9416	0.0284	0.2998	nan	0.6405	0.8102	0.5883	0.7132	0.2382	nan	0.2768	0.4374	0.8038	0.3840	0.6677	0.4052	0.2988	nan	0.2030	0.8288	0.7556	0.8939	0.0275	0.2317
0.4593	47.0	5029	0.5917	0.2826	0.3528	0.8187	nan	0.7586	0.9405	0.7273	0.8595	0.2065	nan	0.4141	0.6501	0.9297	0.7871	0.8608	0.5563	0.4812	nan	0.2866	0.9116	0.7873	0.9549	0.0086	0.1702	nan	0.6428	0.8118	0.6553	0.6713	0.1926	nan	0.2664	0.4467	0.7903	0.3458	0.6574	0.4026	0.3809	nan	0.1806	0.8257	0.7325	0.8904	0.0085	0.1427
0.4918	48.0	5136	0.5844	0.2867	0.3512	0.8249	nan	0.7452	0.9517	0.6479	0.8534	0.2971	nan	0.4271	0.6779	0.9265	0.6756	0.8596	0.5569	0.3076	nan	0.2851	0.9064	0.8252	0.9511	0.0297	0.3125	nan	0.6504	0.8138	0.5866	0.6861	0.2693	nan	0.2809	0.4518	0.7985	0.3514	0.6628	0.3947	0.2834	nan	0.1980	0.8343	0.7573	0.8914	0.0293	0.2353
0.4964	49.0	5243	0.6075	0.2763	0.3394	0.8260	nan	0.8158	0.9484	0.1481	0.8338	0.2194	nan	0.4162	0.6461	0.9305	0.6198	0.8643	0.6049	0.5862	nan	0.3021	0.8990	0.8118	0.9415	0.0430	0.2289	nan	0.6691	0.8134	0.1461	0.7553	0.2065	nan	0.2807	0.4379	0.7924	0.3316	0.6698	0.4370	0.4026	nan	0.2042	0.8254	0.7464	0.8863	0.0412	0.1961
0.5269	50.0	5350	0.5908	0.2872	0.3517	0.8275	nan	0.7844	0.9384	0.4184	0.8534	0.2576	nan	0.4853	0.6334	0.9291	0.7341	0.8757	0.5056	0.4892	nan	0.3070	0.9109	0.8654	0.9529	0.0719	0.2414	nan	0.6483	0.8192	0.4170	0.6947	0.2399	nan	0.2972	0.4607	0.7964	0.3577	0.6746	0.4162	0.3866	nan	0.2110	0.8339	0.7680	0.8941	0.0691	0.2074
0.4802	51.0	5457	0.5712	0.2837	0.3464	0.8255	nan	0.8403	0.9234	0.5830	0.8358	0.3140	nan	0.4449	0.6503	0.9308	0.7235	0.8929	0.5109	0.3872	nan	0.2343	0.9138	0.7883	0.9594	0.0271	0.1250	nan	0.6763	0.8123	0.5638	0.6999	0.2848	nan	0.2960	0.4551	0.7899	0.3364	0.6579	0.4071	0.3440	nan	0.1751	0.8265	0.7311	0.8846	0.0266	0.1127
0.4695	52.0	5564	0.5993	0.2815	0.3477	0.8202	nan	0.7433	0.9466	0.3654	0.8687	0.2254	nan	0.4466	0.6632	0.9326	0.7149	0.8300	0.5175	0.4682	nan	0.3419	0.9250	0.8074	0.9329	0.0434	0.3532	nan	0.6338	0.8101	0.3587	0.6763	0.2116	nan	0.2961	0.4354	0.7837	0.3688	0.6543	0.4152	0.3928	nan	0.2239	0.8275	0.7419	0.8949	0.0419	0.2411

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

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Nov 23, 2024
Updated: Nov 24, 2024