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karthik540/
segformer-b0-finetuned-segments-sidewalk-2

Name: segformer-b0-finetuned-segments-sidewalk-2
Availability: InStock

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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: 2.4429
Mean Iou: 0.0127
Mean Accuracy: 0.0289
Overall Accuracy: 0.2813
Accuracy Unlabeled: nan
Accuracy Flat-road: 0.0012
Accuracy Flat-sidewalk: 0.7342
Accuracy Flat-crosswalk: 0.0
Accuracy Flat-cyclinglane: 0.0
Accuracy Flat-parkingdriveway: 0.0
Accuracy Flat-railtrack: 0.0
Accuracy Flat-curb: 0.0
Accuracy Human-person: 0.0
Accuracy Human-rider: 0.0
Accuracy Vehicle-car: 0.0
Accuracy Vehicle-truck: 0.0
Accuracy Vehicle-bus: 0.0
Accuracy Vehicle-tramtrain: 0.0
Accuracy Vehicle-motorcycle: 0.0
Accuracy Vehicle-bicycle: 0.0
Accuracy Vehicle-caravan: 0.0
Accuracy Vehicle-cartrailer: 0.0
Accuracy Construction-building: 0.0538
Accuracy Construction-door: 0.0
Accuracy Construction-wall: 0.0
Accuracy Construction-fenceguardrail: 0.0
Accuracy Construction-bridge: 0.0
Accuracy Construction-tunnel: 0.0
Accuracy Construction-stairs: 0.0
Accuracy Object-pole: 0.0
Accuracy Object-trafficsign: 0.0
Accuracy Object-trafficlight: 0.0
Accuracy Nature-vegetation: 0.1770
Accuracy Nature-terrain: 0.0
Accuracy Sky: 0.0149
Accuracy Void-ground: 0.0
Accuracy Void-dynamic: 0.0
Accuracy Void-static: 0.0
Accuracy Void-unclear: 0.0
Iou Unlabeled: nan
Iou Flat-road: 0.0012
Iou Flat-sidewalk: 0.3016
Iou Flat-crosswalk: 0.0
Iou Flat-cyclinglane: 0.0
Iou Flat-parkingdriveway: 0.0
Iou Flat-railtrack: 0.0
Iou Flat-curb: 0.0
Iou Human-person: 0.0
Iou Human-rider: 0.0
Iou Vehicle-car: 0.0
Iou Vehicle-truck: 0.0
Iou Vehicle-bus: 0.0
Iou Vehicle-tramtrain: 0.0
Iou Vehicle-motorcycle: 0.0
Iou Vehicle-bicycle: 0.0
Iou Vehicle-caravan: 0.0
Iou Vehicle-cartrailer: 0.0
Iou Construction-building: 0.0318
Iou Construction-door: 0.0
Iou Construction-wall: 0.0
Iou Construction-fenceguardrail: 0.0
Iou Construction-bridge: 0.0
Iou Construction-tunnel: 0.0
Iou Construction-stairs: 0.0
Iou Object-pole: 0.0
Iou Object-trafficsign: 0.0
Iou Object-trafficlight: 0.0
Iou Nature-vegetation: 0.0859
Iou Nature-terrain: 0.0
Iou Sky: 0.0108
Iou Void-ground: 0.0
Iou Void-dynamic: 0.0
Iou Void-static: 0.0
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

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-bicycle	Accuracy Vehicle-caravan	Accuracy Vehicle-cartrailer	Accuracy Construction-building	Accuracy Construction-wall	Accuracy Construction-fenceguardrail	Accuracy Construction-bridge	Accuracy Construction-tunnel	Accuracy Construction-stairs	Accuracy Object-pole	Accuracy Object-trafficsign	Accuracy Object-trafficlight	Accuracy Nature-vegetation	Accuracy Nature-terrain	Accuracy Sky	Accuracy Void-ground	Accuracy Void-dynamic	Accuracy Void-static	Accuracy Void-unclear	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-bicycle	Iou Vehicle-caravan	Iou Vehicle-cartrailer	Iou Construction-building	Iou Construction-wall	Iou Construction-fenceguardrail	Iou Construction-bridge	Iou Construction-tunnel	Iou Construction-stairs	Iou Object-pole	Iou Object-trafficsign	Iou Object-trafficlight	Iou Nature-vegetation	Iou Nature-terrain	Iou Sky	Iou Void-ground	Iou Void-dynamic	Iou Void-static	Iou Void-unclear
3.5256	0.2	10	3.5147	0.0071	0.0401	0.1017	nan	0.0000	0.2861	0.0000	0.0000	0.0402	0.0011	0.0017	0.0035	0.0215	0.0236	0.0002	0.0010	0.0053	0.0162	0.0020	0.5432	0.0000	0.0815	0.0166	0.0172	0.0010	0.0000	0.0028	0.2620	0.0002	0.0060	0.0294	0.0	0.0000	0.1889	0.0000	0.0000	0.0173	0.0011	0.0005	0.0029	0.0026	0.0001	0.0000	0.0010	0.0038	0.0064	0.0001	0.0000	0.0000	0.0077	0.0010	0.0000	0.0010	0.0000	0.0027	0.0051	0.0002	0.0049	0.0002
3.3115	0.4	20	3.4349	0.0090	0.0293	0.1597	nan	0.0001	0.4536	0.0	0.0	0.0642	0.0002	0.0009	0.0008	0.0075	0.0213	0.0	0.0009	0.0059	0.0046	0.0	0.0782	0.0	0.1300	0.0102	0.0231	0.0046	0.0000	0.0016	0.1731	0.0	0.0044	0.0114	nan	0.0001	0.2507	0.0	0.0	0.0202	0.0002	0.0004	0.0008	0.0021	0.0001	0.0	0.0009	0.0038	0.0030	0.0	0.0000	0.0	0.0080	0.0012	0.0000	0.0044	0.0000	0.0016	0.0050	0.0	0.0038	0.0002
2.8003	0.6	30	3.3730	0.0087	0.0281	0.1245	nan	0.0054	0.3314	0.0000	0.0000	0.1290	0.0003	0.0031	0.0004	0.0023	0.0092	0.0	0.0011	0.0233	0.0022	0.0	0.0	0.0	0.1795	0.0126	0.0010	0.0239	0.0002	0.0046	0.2127	0.0	0.0075	0.0060	nan	0.0052	0.2092	0.0000	0.0000	0.0244	0.0003	0.0009	0.0004	0.0011	0.0001	0.0	0.0011	0.0078	0.0017	0.0	0.0	0.0	0.0079	0.0013	0.0000	0.0203	0.0002	0.0041	0.0050	0.0	0.0054	0.0004
3.2521	0.8	40	3.2736	0.0110	0.0292	0.1863	nan	0.0294	0.5083	0.0001	0.0001	0.1290	0.0004	0.0012	0.0011	0.0015	0.0016	0.0	0.0016	0.0127	0.0038	0.0	0.0	0.0000	0.1112	0.0033	0.0	0.0218	0.0002	0.0042	0.1371	0.0	0.0163	0.0076	nan	0.0243	0.2651	0.0001	0.0001	0.0253	0.0004	0.0005	0.0011	0.0009	0.0001	0.0	0.0016	0.0058	0.0028	0.0	0.0	0.0000	0.0080	0.0011	0.0	0.0185	0.0002	0.0037	0.0049	0.0	0.0083	0.0011
2.9043	1.0	50	3.2220	0.0132	0.0291	0.1739	nan	0.1252	0.3934	0.0003	0.0003	0.1066	0.0063	0.0008	0.0068	0.0007	0.0	0.0	0.0075	0.0098	0.0044	0.0	0.0	0.0	0.0582	0.0006	0.0	0.1309	0.0006	0.0081	0.1208	0.0	0.0094	0.0001	nan	0.0664	0.2317	0.0003	0.0003	0.0241	0.0053	0.0004	0.0057	0.0005	0.0	0.0	0.0068	0.0052	0.0033	0.0	0.0	0.0	0.0085	0.0004	0.0	0.0710	0.0006	0.0064	0.0046	0.0	0.0061	0.0000
2.8893	1.2	60	3.1323	0.0128	0.0301	0.1824	nan	0.1147	0.2779	0.0000	0.0002	0.0638	0.0002	0.0001	0.0066	0.0001	0.0	0.0	0.0111	0.0017	0.0009	0.0	0.0	0.0	0.0052	0.0000	0.0	0.4865	0.0005	0.0062	0.0445	0.0	0.0025	0.0	nan	0.0637	0.1900	0.0000	0.0002	0.0202	0.0002	0.0001	0.0052	0.0001	0.0	0.0	0.0091	0.0014	0.0009	0.0	0.0	0.0	0.0033	0.0000	0.0	0.1301	0.0005	0.0050	0.0041	0.0	0.0022	0.0
2.8221	1.4	70	3.0049	0.0138	0.0298	0.2481	nan	0.0664	0.5578	0.0	0.0001	0.0184	0.0	0.0	0.0015	0.0	0.0	0.0	0.0101	0.0002	0.0000	0.0	0.0	0.0	0.0007	0.0	0.0	0.3322	0.0001	0.0147	0.0097	0.0	0.0000	0.0	nan	0.0443	0.2727	0.0	0.0001	0.0109	0.0	0.0	0.0014	0.0	0.0	0.0	0.0084	0.0002	0.0000	0.0	0.0	0.0	0.0007	0.0	0.0	0.1168	0.0001	0.0102	0.0032	0.0	0.0000	0.0
2.7321	1.6	80	2.9281	0.0129	0.0300	0.2121	nan	0.1000	0.3599	0.0	0.0	0.0076	0.0	0.0	0.0022	0.0	0.0	0.0	0.0172	0.0000	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.5224	0.0	0.0077	0.0040	0.0	0.0	0.0	nan	0.0577	0.2179	0.0	0.0	0.0056	0.0	0.0	0.0019	0.0	0.0	0.0	0.0126	0.0000	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.1335	0.0	0.0065	0.0028	0.0	0.0	0.0
2.7583	1.8	90	2.9182	0.0107	0.0303	0.1746	nan	0.1465	0.1641	0.0	0.0	0.0036	0.0	0.0	0.0006	0.0	0.0	0.0	0.0123	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.6905	0.0	0.0102	0.0008	0.0	0.0	0.0	nan	0.0714	0.1297	0.0	0.0	0.0030	0.0	0.0	0.0006	0.0	0.0	0.0	0.0095	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.1398	0.0	0.0084	0.0007	0.0	0.0	0.0
3.1177	2.0	100	2.9230	0.0138	0.0297	0.2272	nan	0.1294	0.4556	0.0	0.0000	0.0030	0.0	0.0	0.0009	0.0	0.0	0.0	0.0299	0.0000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.3671	0.0	0.0219	0.0004	0.0	0.0	0.0	nan	0.0662	0.2463	0.0	0.0000	0.0026	0.0	0.0	0.0009	0.0	0.0	0.0	0.0196	0.0000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1193	0.0	0.0149	0.0004	0.0	0.0	0.0
3.041	2.2	110	2.8124	0.0138	0.0291	0.2549	nan	0.1402	0.6049	0.0	0.0000	0.0002	0.0	0.0	0.0005	0.0	0.0	0.0	0.0363	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1992	0.0	0.0075	0.0	0.0	0.0	0.0	nan	0.0683	0.2797	0.0	0.0000	0.0002	0.0	0.0	0.0005	0.0	0.0	0.0	0.0234	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0921	0.0	0.0062	0.0	0.0	0.0	0.0
2.1549	2.4	120	2.7993	0.0132	0.0292	0.2105	nan	0.1463	0.3812	0.0	0.0	0.0001	0.0	0.0	0.0002	0.0	0.0	0.0	0.0572	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.4022	0.0	0.0061	0.0	0.0	0.0	0.0	nan	0.0692	0.2227	0.0	0.0	0.0001	0.0	0.0	0.0002	0.0	0.0	0.0	0.0301	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1223	0.0	0.0053	0.0	0.0	0.0	0.0
2.7506	2.6	130	2.7869	0.0136	0.0290	0.2153	nan	0.1198	0.4194	0.0	0.0	0.0001	0.0	0.0	0.0000	0.0	0.0	0.0	0.0626	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.3578	0.0	0.0272	0.0	0.0	0.0	0.0	nan	0.0628	0.2315	0.0	0.0	0.0001	0.0	0.0	0.0000	0.0	0.0	0.0	0.0319	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1161	0.0	0.0191	0.0	0.0	0.0	0.0
2.8666	2.8	140	2.7030	0.0133	0.0288	0.2546	nan	0.0626	0.5989	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0378	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2736	0.0	0.0047	0.0	0.0	0.0	0.0	nan	0.0417	0.2753	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0239	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1059	0.0	0.0041	0.0	0.0	0.0	0.0
2.3693	3.0	150	2.6758	0.0133	0.0289	0.2790	nan	0.0661	0.7211	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0304	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1548	0.0	0.0089	0.0	0.0	0.0	0.0	nan	0.0432	0.3002	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0211	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0808	0.0	0.0071	0.0	0.0	0.0	0.0
2.4211	3.2	160	2.6509	0.0122	0.0292	0.3118	nan	0.0340	0.8762	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0157	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0493	0.0	0.0169	0.0	0.0	0.0	0.0	nan	0.0270	0.3255	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0129	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0375	0.0	0.0117	0.0	0.0	0.0	0.0
2.2934	3.4	170	2.5811	0.0109	0.0290	0.3268	nan	0.0162	0.9439	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.0104	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0148	0.0	0.0021	0.0	0.0	0.0	0.0	nan	0.0145	0.3322	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.0093	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0131	0.0	0.0019	0.0	0.0	0.0	0.0
2.2474	3.6	180	2.6740	0.0122	0.0287	0.3000	nan	0.0201	0.8363	0.0	0.0	0.0	0.0	0.0	0.0013	0.0	0.0	0.0	0.0619	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0461	0.0	0.0089	0.0	0.0	0.0	0.0	nan	0.0170	0.3185	0.0	0.0	0.0	0.0	0.0	0.0013	0.0	0.0	0.0	0.0342	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0354	0.0	0.0072	0.0	0.0	0.0	0.0
2.4543	3.8	190	2.5741	0.0115	0.0287	0.3111	nan	0.0113	0.8837	0.0	0.0	0.0	0.0	0.0	0.0006	0.0	0.0	0.0	0.0529	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0263	0.0	0.0014	0.0	0.0	0.0	0.0	nan	0.0103	0.3246	0.0	0.0	0.0	0.0	0.0	0.0006	0.0	0.0	0.0	0.0317	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0219	0.0	0.0014	0.0	0.0	0.0	0.0
2.6415	4.0	200	2.4955	0.0114	0.0287	0.3121	nan	0.0075	0.8862	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0495	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0328	0.0	0.0005	0.0	0.0	0.0	0.0	nan	0.0070	0.3248	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0302	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0266	0.0	0.0005	0.0	0.0	0.0	0.0
2.3359	4.2	210	2.6535	0.0130	0.0280	0.2474	nan	0.0389	0.6235	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.1633	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1048	0.0	0.0211	0.0	0.0	0.0	0.0	nan	0.0285	0.2807	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0537	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0632	0.0	0.0142	0.0	0.0	0.0	0.0
1.8133	4.4	220	2.6000	0.0133	0.0285	0.2609	nan	0.0401	0.6643	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.1069	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1350	0.0	0.0210	0.0	0.0	0.0	0.0	nan	0.0291	0.2901	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.0447	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0749	0.0	0.0147	0.0	0.0	0.0	0.0
2.3126	4.6	230	2.6429	0.0126	0.0288	0.1857	nan	0.0332	0.3374	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.2814	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2779	0.0	0.0480	0.0	0.0	0.0	0.0	nan	0.0255	0.2045	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.0639	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1067	0.0	0.0288	0.0	0.0	0.0	0.0
2.2695	4.8	240	2.5140	0.0128	0.0282	0.2399	nan	0.0217	0.5869	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.2003	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1312	0.0	0.0183	0.0	0.0	0.0	0.0	nan	0.0177	0.2729	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0574	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0738	0.0	0.0145	0.0	0.0	0.0	0.0
2.0622	5.0	250	2.4634	0.0126	0.0283	0.2656	nan	0.0107	0.6862	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1332	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1278	0.0	0.0058	0.0	0.0	0.0	0.0	nan	0.0097	0.2918	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0491	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0736	0.0	0.0052	0.0	0.0	0.0	0.0
2.1988	5.2	260	2.5162	0.0125	0.0282	0.2209	nan	0.0083	0.5152	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.2606	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1382	0.0	0.0379	0.0	0.0	0.0	0.0	nan	0.0077	0.2553	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0621	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0760	0.0	0.0236	0.0	0.0	0.0	0.0
2.4214	5.4	270	2.5880	0.0122	0.0284	0.1888	nan	0.0134	0.3772	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.3344	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1887	0.0	0.0516	0.0	0.0	0.0	0.0	nan	0.0117	0.2176	0.0	0.0	0.0	0.0	0.0	0.0002	0.0	0.0	0.0	0.0671	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0892	0.0	0.0279	0.0	0.0	0.0	0.0
2.2255	5.6	280	2.4963	0.0127	0.0287	0.2732	nan	0.0126	0.7299	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1341	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0689	0.0	0.0301	0.0	0.0	0.0	0.0	nan	0.0113	0.3024	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0513	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0476	0.0	0.0182	0.0	0.0	0.0	0.0
2.3459	5.8	290	2.5055	0.0131	0.0288	0.2638	nan	0.0133	0.6801	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.1239	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1258	0.0	0.0347	0.0	0.0	0.0	0.0	nan	0.0118	0.2933	0.0	0.0	0.0	0.0	0.0	0.0001	0.0	0.0	0.0	0.0489	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0718	0.0	0.0198	0.0	0.0	0.0	0.0
2.1034	6.0	300	2.4549	0.0125	0.0288	0.2873	nan	0.0048	0.7776	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0929	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0897	0.0	0.0143	0.0	0.0	0.0	0.0	nan	0.0046	0.3101	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0430	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0581	0.0	0.0107	0.0	0.0	0.0	0.0
2.2193	6.2	310	2.4227	0.0126	0.0290	0.2879	nan	0.0013	0.7619	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0746	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1482	0.0	0.0002	0.0	0.0	0.0	0.0	nan	0.0013	0.3070	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0379	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0810	0.0	0.0002	0.0	0.0	0.0	0.0
2.3808	6.4	320	2.4239	0.0124	0.0290	0.2926	nan	0.0006	0.7900	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0797	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1109	0.0	0.0031	0.0	0.0	0.0	0.0	nan	0.0006	0.3122	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0397	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0675	0.0	0.0028	0.0	0.0	0.0	0.0
2.1201	6.6	330	2.4546	0.0130	0.0292	0.2795	nan	0.0010	0.7295	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0903	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1522	0.0	0.0186	0.0	0.0	0.0	0.0	nan	0.0010	0.3036	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0422	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0817	0.0	0.0131	0.0	0.0	0.0	0.0
2.1429	6.8	340	2.4390	0.0121	0.0292	0.3077	nan	0.0004	0.8612	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0502	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0618	0.0	0.0185	0.0	0.0	0.0	0.0	nan	0.0004	0.3245	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0314	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0446	0.0	0.0122	0.0	0.0	0.0	0.0
2.3745	7.0	350	2.4814	0.0132	0.0292	0.2555	nan	0.0020	0.6392	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0911	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1816	0.0	0.0800	0.0	0.0	0.0	0.0	nan	0.0020	0.2865	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0422	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0881	0.0	0.0287	0.0	0.0	0.0	0.0
2.1907	7.2	360	2.4901	0.0130	0.0290	0.2387	nan	0.0014	0.5526	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1063	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2669	0.0	0.0588	0.0	0.0	0.0	0.0	nan	0.0014	0.2661	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0432	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1055	0.0	0.0274	0.0	0.0	0.0	0.0
2.1116	7.4	370	2.4841	0.0130	0.0290	0.2350	nan	0.0015	0.5323	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0908	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2968	0.0	0.0659	0.0	0.0	0.0	0.0	nan	0.0014	0.2612	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0397	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1097	0.0	0.0284	0.0	0.0	0.0	0.0
2.4808	7.6	380	2.4890	0.0129	0.0293	0.2376	nan	0.0025	0.5715	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0758	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2136	0.0	0.1314	0.0	0.0	0.0	0.0	nan	0.0024	0.2729	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0372	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0958	0.0	0.0319	0.0	0.0	0.0	0.0
1.8601	7.8	390	2.5003	0.0128	0.0290	0.2250	nan	0.0022	0.4998	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0898	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2944	0.0	0.1015	0.0	0.0	0.0	0.0	nan	0.0022	0.2538	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0393	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1094	0.0	0.0313	0.0	0.0	0.0	0.0
2.032	8.0	400	2.5240	0.0125	0.0289	0.2093	nan	0.0027	0.4406	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1033	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.3108	0.0	0.1262	0.0	0.0	0.0	0.0	nan	0.0026	0.2379	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0422	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1106	0.0	0.0326	0.0	0.0	0.0	0.0
1.9364	8.2	410	2.4666	0.0127	0.0292	0.2720	nan	0.0024	0.7293	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0661	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0924	0.0	0.1028	0.0	0.0	0.0	0.0	nan	0.0023	0.3046	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0371	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0590	0.0	0.0282	0.0	0.0	0.0	0.0
2.0335	8.4	420	2.4894	0.0129	0.0292	0.2402	nan	0.0046	0.5965	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0783	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1650	0.0	0.1478	0.0	0.0	0.0	0.0	nan	0.0044	0.2787	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0400	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0831	0.0	0.0315	0.0	0.0	0.0	0.0
2.0622	8.6	430	2.5457	0.0121	0.0287	0.1888	nan	0.0038	0.3645	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1536	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.3132	0.0	0.1396	0.0	0.0	0.0	0.0	nan	0.0037	0.2129	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0500	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1108	0.0	0.0338	0.0	0.0	0.0	0.0
1.9635	8.8	440	2.5416	0.0120	0.0287	0.1908	nan	0.0028	0.4200	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1216	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1900	0.0	0.2427	0.0	0.0	0.0	0.0	nan	0.0027	0.2335	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0465	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0899	0.0	0.0340	0.0	0.0	0.0	0.0
1.9328	9.0	450	2.4707	0.0128	0.0293	0.2609	nan	0.0024	0.6792	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0528	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1358	0.0	0.1274	0.0	0.0	0.0	0.0	nan	0.0024	0.2958	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0327	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0750	0.0	0.0299	0.0	0.0	0.0	0.0
2.0373	9.2	460	2.5003	0.0128	0.0292	0.2294	nan	0.0028	0.5341	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0638	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2482	0.0	0.1447	0.0	0.0	0.0	0.0	nan	0.0028	0.2641	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0349	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1011	0.0	0.0315	0.0	0.0	0.0	0.0
2.2552	9.4	470	2.4884	0.0130	0.0292	0.2400	nan	0.0020	0.5674	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0689	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2513	0.0	0.1038	0.0	0.0	0.0	0.0	nan	0.0020	0.2712	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0365	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1016	0.0	0.0296	0.0	0.0	0.0	0.0
1.956	9.6	480	2.5214	0.0126	0.0289	0.2153	nan	0.0034	0.4825	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.1038	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2477	0.0	0.1458	0.0	0.0	0.0	0.0	nan	0.0033	0.2501	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0445	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1003	0.0	0.0320	0.0	0.0	0.0	0.0
2.1743	9.8	490	2.4624	0.0127	0.0289	0.2689	nan	0.0018	0.7146	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0769	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1041	0.0	0.0848	0.0	0.0	0.0	0.0	nan	0.0018	0.3001	0.0	0.0	0.0	0.0	0.0	0.0000	0.0	0.0	0.0	0.0402	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0633	0.0	0.0261	0.0	0.0	0.0	0.0
2.0282	10.0	500	2.4429	0.0127	0.0289	0.2813	nan	0.0012	0.7342	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0538	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1770	0.0	0.0149	0.0	0.0	0.0	0.0	nan	0.0012	0.3016	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0318	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0859	0.0	0.0108	0.0	0.0	0.0	0.0

Framework versions

Transformers 4.40.1
Pytorch 2.3.0
Datasets 2.19.0
Tokenizers 0.19.1

karthik540/segformer-b0-finetuned-segments-sidewalk-2

segformer-b0-finetuned-segments-sidewalk-2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

karthik540/
segformer-b0-finetuned-segments-sidewalk-2