mit-b0-finetuned-sidewalks

greathero/mit-b0-finetuned-sidewalks

mit-b0-finetuned-sidewalks is a machine learning model from greathero. Use it for the machine learning 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.

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

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Repo size

758 MB

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Repo makeup

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At a glance

Library: transformers
License: other
Model type: segformer
Access: Public
Created: Nov 4, 2023
Updated: Dec 3, 2023
SHA: 12f79659

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

greathero/mit-b0-finetuned-sidewalks

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

Train Loss: 0.1964
Validation Loss: 0.5617
Validation Mean Iou: 0.3482
Validation Mean Accuracy: 0.4212
Validation Overall Accuracy: 0.8714
Validation Accuracy Unlabeled: 0.0
Validation Accuracy Flat-road: 0.9191
Validation Accuracy Flat-sidewalk: 0.9583
Validation Accuracy Flat-crosswalk: 0.5878
Validation Accuracy Flat-cyclinglane: 0.7730
Validation Accuracy Flat-parkingdriveway: 0.6079
Validation Accuracy Flat-railtrack: nan
Validation Accuracy Flat-curb: 0.5577
Validation Accuracy Human-person: 0.6959
Validation Accuracy Human-rider: 0.2221
Validation Accuracy Vehicle-car: 0.9300
Validation Accuracy Vehicle-truck: 0.1310
Validation Accuracy Vehicle-bus: 0.0
Validation Accuracy Vehicle-tramtrain: nan
Validation Accuracy Vehicle-motorcycle: 0.0
Validation Accuracy Vehicle-bicycle: 0.6927
Validation Accuracy Vehicle-caravan: 0.0
Validation Accuracy Vehicle-cartrailer: 0.0
Validation Accuracy Construction-building: 0.9088
Validation Accuracy Construction-door: 0.0611
Validation Accuracy Construction-wall: 0.4825
Validation Accuracy Construction-fenceguardrail: 0.4370
Validation Accuracy Construction-bridge: 0.0
Validation Accuracy Construction-tunnel: nan
Validation Accuracy Construction-stairs: 0.0
Validation Accuracy Object-pole: 0.4339
Validation Accuracy Object-trafficsign: 0.4711
Validation Accuracy Object-trafficlight: 0.0
Validation Accuracy Nature-vegetation: 0.9172
Validation Accuracy Nature-terrain: 0.9151
Validation Accuracy Sky: 0.9692
Validation Accuracy Void-ground: 0.5121
Validation Accuracy Void-dynamic: 0.0265
Validation Accuracy Void-static: 0.2676
Validation Accuracy Void-unclear: 0.0
Validation Iou Unlabeled: 0.0
Validation Iou Flat-road: 0.7902
Validation Iou Flat-sidewalk: 0.9044
Validation Iou Flat-crosswalk: 0.4201
Validation Iou Flat-cyclinglane: 0.6963
Validation Iou Flat-parkingdriveway: 0.4879
Validation Iou Flat-railtrack: nan
Validation Iou Flat-curb: 0.4607
Validation Iou Human-person: 0.4926
Validation Iou Human-rider: 0.1864
Validation Iou Vehicle-car: 0.8243
Validation Iou Vehicle-truck: 0.1278
Validation Iou Vehicle-bus: 0.0
Validation Iou Vehicle-tramtrain: nan
Validation Iou Vehicle-motorcycle: 0.0
Validation Iou Vehicle-bicycle: 0.4759
Validation Iou Vehicle-caravan: 0.0
Validation Iou Vehicle-cartrailer: 0.0
Validation Iou Construction-building: 0.6973
Validation Iou Construction-door: 0.0588
Validation Iou Construction-wall: 0.3754
Validation Iou Construction-fenceguardrail: 0.3760
Validation Iou Construction-bridge: 0.0
Validation Iou Construction-tunnel: nan
Validation Iou Construction-stairs: 0.0
Validation Iou Object-pole: 0.3330
Validation Iou Object-trafficsign: 0.3555
Validation Iou Object-trafficlight: 0.0
Validation Iou Nature-vegetation: 0.8600
Validation Iou Nature-terrain: 0.7533
Validation Iou Sky: 0.9288
Validation Iou Void-ground: 0.3089
Validation Iou Void-dynamic: 0.0223
Validation Iou Void-static: 0.2055
Validation Iou Void-unclear: 0.0
Epoch: 49

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:

optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Validation Loss	Validation Mean Iou	Validation Mean Accuracy	Validation Overall Accuracy	Validation Accuracy Flat-road	Validation Accuracy Flat-sidewalk	Validation Accuracy Flat-crosswalk	Validation Accuracy Flat-cyclinglane	Validation Accuracy Flat-parkingdriveway	Validation Accuracy Flat-railtrack	Validation Accuracy Flat-curb	Validation Accuracy Human-person	Validation Accuracy Human-rider	Validation Accuracy Vehicle-car	Validation Accuracy Vehicle-truck	Validation Accuracy Vehicle-tramtrain	Validation Accuracy Vehicle-bicycle	Validation Accuracy Construction-building	Validation Accuracy Construction-door	Validation Accuracy Construction-wall	Validation Accuracy Construction-fenceguardrail	Validation Accuracy Construction-tunnel	Validation Accuracy Object-pole	Validation Accuracy Object-trafficsign	Validation Accuracy Nature-vegetation	Validation Accuracy Nature-terrain	Validation Accuracy Sky	Validation Accuracy Void-ground	Validation Accuracy Void-dynamic	Validation Accuracy Void-static	Validation Iou Flat-road	Validation Iou Flat-sidewalk	Validation Iou Flat-crosswalk	Validation Iou Flat-cyclinglane	Validation Iou Flat-parkingdriveway	Validation Iou Flat-railtrack	Validation Iou Flat-curb	Validation Iou Human-person	Validation Iou Human-rider	Validation Iou Vehicle-car	Validation Iou Vehicle-truck	Validation Iou Vehicle-tramtrain	Validation Iou Vehicle-bicycle	Validation Iou Construction-building	Validation Iou Construction-door	Validation Iou Construction-wall	Validation Iou Construction-fenceguardrail	Validation Iou Construction-tunnel	Validation Iou Object-pole	Validation Iou Object-trafficsign	Validation Iou Nature-vegetation	Validation Iou Nature-terrain	Validation Iou Sky	Validation Iou Void-ground	Validation Iou Void-dynamic	Validation Iou Void-static	Epoch
1.9172	1.1456	0.1406	0.1941	0.7310	0.7980	0.9298	0.0051	0.2528	0.0049	nan	0.0001	0.0458	0.0	0.8315	0.0	nan	0.0	0.7839	0.0	0.0210	0.0370	nan	0.0058	0.0	0.9028	0.6924	0.9004	0.0	0.0	0.0002	0.4633	0.7662	0.0051	0.2317	0.0048	0.0	0.0001	0.0323	0.0	0.6396	0.0	0.0	0.0	0.5243	0.0	0.0206	0.0348	nan	0.0054	0.0	0.7094	0.5497	0.7916	0.0	0.0	0.0002	0
1.0247	0.8848	0.1918	0.2336	0.7698	0.6997	0.9651	0.4394	0.4069	0.1304	nan	0.0606	0.0601	0.0	0.8688	0.0	nan	0.0097	0.8430	0.0	0.2444	0.1184	nan	0.0102	0.0	0.9227	0.7934	0.9018	0.0	0.0	0.0014	0.5611	0.7751	0.4093	0.3588	0.1102	nan	0.0550	0.0513	0.0	0.6674	0.0	nan	0.0097	0.5662	0.0	0.2011	0.1101	nan	0.0101	0.0	0.7593	0.6549	0.8360	0.0	0.0	0.0014	1
0.8452	0.7838	0.2203	0.2738	0.7971	0.8465	0.9296	0.5352	0.5975	0.2817	nan	0.1721	0.3577	0.0	0.8242	0.0	nan	0.0999	0.8508	0.0	0.3727	0.1481	nan	0.0712	0.0	0.9379	0.8088	0.9242	0.0	0.0	0.0027	0.5691	0.8475	0.3104	0.5182	0.2163	nan	0.1416	0.2415	0.0	0.7082	0.0	nan	0.0997	0.5843	0.0	0.2783	0.1415	nan	0.0679	0.0	0.7789	0.6955	0.8480	0.0	0.0	0.0026	2
0.7393	0.7194	0.2443	0.2959	0.8084	0.7601	0.9601	0.3925	0.5485	0.4444	nan	0.2765	0.4666	0.0	0.8905	0.0	nan	0.3695	0.8608	0.0	0.4003	0.2319	nan	0.1120	0.0	0.9064	0.8793	0.9268	0.0	0.0	0.0434	0.6189	0.8385	0.3858	0.4982	0.2872	nan	0.2269	0.2991	0.0	0.7134	0.0	nan	0.3144	0.6105	0.0	0.3110	0.2177	nan	0.1034	0.0	0.7932	0.6956	0.8646	0.0	0.0	0.0385	3
0.6723	0.6423	0.2585	0.3200	0.8243	0.8379	0.9392	0.5390	0.6706	0.5206	nan	0.3683	0.6301	0.0	0.8838	0.0	nan	0.3830	0.8862	0.0	0.3901	0.2524	nan	0.1545	0.0	0.9096	0.8846	0.9254	0.0	0.0001	0.0643	0.6716	0.8658	0.3985	0.5764	0.3400	nan	0.2731	0.3130	0.0	0.7325	0.0	nan	0.3255	0.6179	0.0	0.3338	0.2397	nan	0.1381	0.0	0.8056	0.7102	0.8723	0.0	0.0001	0.0578	4
0.6205	0.6604	0.2592	0.3188	0.8256	0.8237	0.9528	0.5500	0.5608	0.6090	nan	0.3591	0.4741	0.0	0.8835	0.0	nan	0.4288	0.9049	0.0	0.4296	0.2780	nan	0.2117	0.0	0.9279	0.8381	0.9277	0.0	0.0003	0.0425	0.6967	0.8550	0.2920	0.5056	0.3663	nan	0.2893	0.3073	0.0	0.7447	0.0	nan	0.3632	0.6182	0.0	0.3474	0.2593	nan	0.1780	0.0	0.8229	0.7302	0.8786	0.0	0.0003	0.0396	5
0.5839	0.6139	0.2738	0.3325	0.8330	0.8190	0.9635	0.5040	0.6479	0.5465	nan	0.3405	0.5509	0.0	0.8938	0.0	nan	0.5717	0.8895	0.0	0.4915	0.3136	nan	0.2540	0.0	0.9038	0.8733	0.9399	0.0	0.0039	0.1320	0.7100	0.8592	0.4158	0.5694	0.3564	nan	0.2854	0.3518	0.0	0.7495	0.0	nan	0.4226	0.6419	0.0	0.3810	0.2908	nan	0.1984	0.0	0.8237	0.7147	0.8798	0.0	0.0038	0.1073	6
0.5377	0.5787	0.2763	0.3397	0.8374	0.8782	0.9396	0.5571	0.6511	0.5741	nan	0.4205	0.5055	0.0	0.8842	0.0	nan	0.5905	0.8932	0.0	0.4833	0.3608	nan	0.2777	0.0018	0.9253	0.8693	0.9532	0.0	0.0025	0.1022	0.6996	0.8736	0.3436	0.5970	0.3762	nan	0.3136	0.3388	0.0	0.7668	0.0	nan	0.4413	0.6375	0.0	0.3730	0.3209	nan	0.2190	0.0018	0.8323	0.7339	0.8797	0.0	0.0024	0.0908	7
0.5102	0.5413	0.2852	0.3417	0.8472	0.8733	0.9482	0.4978	0.7936	0.4843	nan	0.3768	0.5607	0.0	0.8764	0.0	nan	0.5866	0.8863	0.0	0.4769	0.3574	nan	0.2680	0.0013	0.9395	0.8760	0.9478	0.0	0.0045	0.1792	0.7354	0.8816	0.4221	0.6823	0.3631	nan	0.3052	0.3647	0.0	0.7699	0.0	nan	0.4497	0.6563	0.0	0.3737	0.3235	nan	0.2125	0.0013	0.8273	0.7161	0.8933	0.0	0.0044	0.1451	8
0.4841	0.5317	0.2880	0.3513	0.8505	0.8846	0.9516	0.5489	0.8002	0.5770	nan	0.3905	0.5536	0.0	0.8946	0.0	nan	0.6090	0.8865	0.0	0.4967	0.3616	nan	0.3103	0.0129	0.9036	0.9037	0.9505	0.0	0.0032	0.2026	0.7536	0.8840	0.3437	0.7198	0.4150	nan	0.3262	0.3606	0.0	0.7672	0.0	nan	0.4336	0.6606	0.0	0.3724	0.3274	nan	0.2363	0.0129	0.8265	0.7080	0.8948	0.0	0.0030	0.1696	9
0.4663	0.5253	0.2903	0.3504	0.8531	0.8632	0.9503	0.4520	0.8542	0.5251	nan	0.3878	0.5854	0.0	0.9041	0.0	nan	0.6516	0.8830	0.0	0.5018	0.3624	nan	0.3190	0.0143	0.9290	0.8950	0.9495	0.0	0.0025	0.1835	0.7467	0.8831	0.3961	0.7313	0.3927	nan	0.3174	0.3708	0.0	0.7719	0.0	nan	0.4393	0.6648	0.0	0.3684	0.3338	nan	0.2396	0.0143	0.8406	0.7302	0.9009	0.0	0.0024	0.1464	10
0.4466	0.5667	0.2867	0.3460	0.8459	0.8852	0.9554	0.5124	0.6566	0.6231	nan	0.3960	0.5075	0.0	0.8932	0.0	nan	0.6307	0.9193	0.0	0.5021	0.3920	nan	0.3301	0.0299	0.9236	0.8399	0.9567	0.0	0.0096	0.1091	0.7247	0.8746	0.4095	0.6009	0.4343	nan	0.3309	0.3346	0.0	0.7803	0.0	nan	0.4490	0.6423	0.0	0.3891	0.3310	nan	0.2522	0.0299	0.8416	0.7461	0.8986	0.0	0.0085	0.0979	11
0.4201	0.5216	0.2959	0.3557	0.8570	0.8772	0.9565	0.4502	0.7909	0.5969	nan	0.4384	0.5878	0.0028	0.9030	0.0	nan	0.6439	0.8963	0.0	0.5378	0.3621	nan	0.3043	0.0282	0.9206	0.8979	0.9562	0.0	0.0015	0.2284	0.7601	0.8843	0.3895	0.7020	0.4255	nan	0.3655	0.3689	0.0028	0.7794	0.0	nan	0.4512	0.6719	0.0	0.3923	0.3293	nan	0.2432	0.0281	0.8495	0.7423	0.9015	0.0	0.0014	0.1815	12
0.4155	0.5468	0.2913	0.3606	0.8525	0.8460	0.9363	0.5329	0.8216	0.6785	nan	0.4931	0.5219	0.0076	0.9172	0.0	nan	0.6537	0.9282	0.0	0.5048	0.3783	nan	0.3354	0.0529	0.9057	0.9100	0.9441	0.0	0.0143	0.1573	0.7598	0.8861	0.2428	0.7322	0.4286	nan	0.3793	0.3453	0.0076	0.7781	0.0	nan	0.4537	0.6496	0.0	0.3874	0.3258	nan	0.2583	0.0526	0.8479	0.7370	0.9009	0.0	0.0129	0.1355	13
0.3892	0.5175	0.3004	0.3618	0.8613	0.9000	0.9479	0.4376	0.8710	0.6180	nan	0.4245	0.6868	0.0094	0.8863	0.0	nan	0.6129	0.9115	0.0	0.4900	0.3562	nan	0.3215	0.1297	0.9228	0.9045	0.9555	0.0	0.0057	0.1855	0.7676	0.8928	0.3316	0.7655	0.4191	nan	0.3657	0.3880	0.0094	0.7938	0.0	nan	0.4393	0.6601	0.0	0.4075	0.3296	nan	0.2502	0.1287	0.8530	0.7461	0.9041	0.0	0.0054	0.1551	14
0.3774	0.5600	0.2950	0.3518	0.8528	0.8595	0.9628	0.2409	0.7379	0.6461	nan	0.4255	0.5880	0.0124	0.8996	0.0	nan	0.6380	0.9198	0.0	0.5246	0.3877	nan	0.3241	0.1567	0.9042	0.8958	0.9545	0.0	0.0130	0.1680	0.7599	0.8747	0.2287	0.6677	0.4078	nan	0.3595	0.3946	0.0124	0.7930	0.0	nan	0.4603	0.6603	0.0	0.4156	0.3319	nan	0.2643	0.1535	0.8453	0.7478	0.9060	0.0	0.0121	0.1449	15
0.3713	0.5397	0.3053	0.3675	0.8565	0.8845	0.9473	0.5039	0.7752	0.6646	nan	0.4841	0.6128	0.0313	0.9142	0.0029	nan	0.6522	0.9018	0.0054	0.5113	0.3701	nan	0.3208	0.1426	0.9068	0.9156	0.9537	0.0011	0.0201	0.2376	0.7785	0.8791	0.4051	0.7029	0.4544	nan	0.3946	0.3946	0.0311	0.7865	0.0029	nan	0.4606	0.6823	0.0053	0.3835	0.3334	nan	0.2581	0.1383	0.8433	0.7196	0.9061	0.0007	0.0182	0.1920	16
0.3502	0.5369	0.3065	0.3627	0.8594	0.9004	0.9587	0.4626	0.7253	0.5631	nan	0.5189	0.5677	0.0020	0.9280	0.0247	nan	0.6415	0.8986	0.0008	0.5035	0.3569	nan	0.3524	0.2297	0.9422	0.8659	0.9595	0.0	0.0117	0.1931	0.7554	0.8846	0.4080	0.6569	0.4399	nan	0.4082	0.3910	0.0020	0.7829	0.0247	nan	0.4650	0.6756	0.0008	0.4035	0.3249	nan	0.2717	0.2187	0.8550	0.7560	0.9070	0.0	0.0113	0.1663	17
0.3405	0.5502	0.3062	0.3636	0.8594	0.9166	0.9532	0.4142	0.7531	0.6138	nan	0.4230	0.5584	0.0258	0.8984	0.0044	nan	0.6498	0.9063	0.0057	0.5072	0.3758	nan	0.3565	0.2564	0.9187	0.9228	0.9622	0.0021	0.0172	0.1947	0.7390	0.8967	0.3897	0.6933	0.4355	nan	0.3709	0.3863	0.0256	0.7977	0.0044	nan	0.4553	0.6760	0.0056	0.3945	0.3398	nan	0.2704	0.2408	0.8494	0.7349	0.9070	0.0020	0.0160	0.1688	18
0.3311	0.5097	0.3140	0.3734	0.8628	0.8703	0.9682	0.4415	0.8131	0.5973	nan	0.4837	0.6228	0.0409	0.9119	0.0300	nan	0.6709	0.8819	0.0123	0.5047	0.4101	nan	0.3714	0.2680	0.9125	0.9120	0.9623	0.0	0.0194	0.2439	0.7928	0.8843	0.3726	0.7384	0.4594	nan	0.3924	0.4183	0.0407	0.8016	0.0300	nan	0.4553	0.6842	0.0119	0.3877	0.3679	nan	0.2747	0.2447	0.8427	0.7257	0.9099	0.0	0.0182	0.1957	19
0.3200	0.5690	0.3125	0.3727	0.8588	0.8760	0.9569	0.4469	0.6968	0.7124	nan	0.4744	0.6537	0.0381	0.9262	0.0226	nan	0.6176	0.8978	0.0201	0.5154	0.3644	nan	0.3458	0.3278	0.9375	0.8824	0.9608	0.0	0.0238	0.2276	0.7867	0.8779	0.3945	0.6375	0.4626	nan	0.3969	0.4168	0.0376	0.7872	0.0226	nan	0.4612	0.6770	0.0192	0.4005	0.3394	nan	0.2703	0.2821	0.8552	0.7527	0.9104	0.0	0.0219	0.1902	20
0.3120	0.5155	0.3151	0.3760	0.8626	0.8875	0.9659	0.4640	0.7236	0.6301	nan	0.4876	0.5926	0.0416	0.9255	0.0116	nan	0.6732	0.9028	0.0270	0.5107	0.4032	nan	0.3817	0.3335	0.9350	0.8668	0.9556	0.0012	0.0434	0.2684	0.7974	0.8797	0.3892	0.6598	0.4580	nan	0.4000	0.3794	0.0414	0.7968	0.0116	nan	0.4536	0.6872	0.0259	0.4002	0.3626	nan	0.2821	0.2841	0.8603	0.7609	0.9128	0.0011	0.0331	0.2076	21
0.3017	0.5201	0.3199	0.3827	0.8670	0.9120	0.9521	0.5413	0.8270	0.6610	nan	0.4946	0.5627	0.0423	0.9207	0.0336	nan	0.6437	0.9003	0.0247	0.5331	0.4028	nan	0.3737	0.3892	0.9171	0.9109	0.9616	0.0146	0.0184	0.2092	0.7717	0.9034	0.3938	0.7287	0.4774	nan	0.4103	0.4008	0.0419	0.8044	0.0336	nan	0.4686	0.6813	0.0230	0.3958	0.3564	nan	0.2823	0.3297	0.8547	0.7570	0.9126	0.0121	0.0173	0.1786	22
0.3016	0.5527	0.3173	0.3811	0.8609	0.8912	0.9593	0.4638	0.6868	0.7110	nan	0.4653	0.6380	0.0447	0.9197	0.0362	nan	0.6737	0.8998	0.0303	0.5386	0.4095	nan	0.3663	0.3935	0.9284	0.8910	0.9618	0.0000	0.0297	0.2570	0.7536	0.8893	0.3672	0.6440	0.4740	nan	0.3968	0.4275	0.0444	0.7999	0.0361	nan	0.4593	0.6930	0.0291	0.3877	0.3651	nan	0.2839	0.3360	0.8568	0.7558	0.9154	0.0000	0.0277	0.2098	23
0.2903	0.5091	0.3204	0.3803	0.8666	0.9124	0.9512	0.5347	0.8343	0.6212	nan	0.5144	0.5947	0.0513	0.9161	0.0387	nan	0.6167	0.9043	0.0255	0.4947	0.3443	nan	0.3727	0.3979	0.9229	0.9170	0.9584	0.0134	0.0171	0.2150	0.8085	0.8943	0.4187	0.7402	0.4403	nan	0.4257	0.4229	0.0506	0.8021	0.0384	nan	0.4653	0.6774	0.0241	0.3744	0.3237	nan	0.2837	0.3375	0.8534	0.7470	0.9170	0.0119	0.0165	0.1784	24
0.2869	0.5304	0.3208	0.3853	0.8631	0.9204	0.9461	0.5684	0.7963	0.5569	nan	0.5264	0.6297	0.0769	0.9035	0.0469	nan	0.6724	0.9134	0.0107	0.4920	0.3848	nan	0.3858	0.4485	0.9322	0.8984	0.9576	0.0506	0.0301	0.1830	0.7513	0.9008	0.4016	0.7108	0.4265	nan	0.4086	0.4314	0.0752	0.8133	0.0455	nan	0.4575	0.6703	0.0105	0.4124	0.3496	nan	0.2943	0.3631	0.8537	0.7527	0.9175	0.0397	0.0272	0.1531	25
0.2870	0.6210	0.3239	0.3867	0.8601	0.9226	0.9662	0.5159	0.6950	0.5032	nan	0.4978	0.5125	0.0764	0.9003	0.0567	nan	0.6650	0.9188	0.0165	0.4980	0.4263	nan	0.3906	0.4679	0.9084	0.9043	0.9576	0.3333	0.0473	0.1939	0.7746	0.8841	0.4054	0.6361	0.4274	nan	0.4203	0.3645	0.0747	0.7990	0.0559	nan	0.4630	0.6670	0.0159	0.4031	0.3693	nan	0.2942	0.3689	0.8547	0.7547	0.9169	0.2169	0.0353	0.1634	26
0.2759	0.5174	0.3291	0.3943	0.8685	0.9123	0.9615	0.3826	0.8113	0.5876	nan	0.5130	0.6677	0.0862	0.9153	0.0635	nan	0.6666	0.8736	0.0716	0.5387	0.4437	nan	0.4190	0.4781	0.9194	0.9174	0.9674	0.1048	0.0253	0.2898	0.8047	0.8922	0.3331	0.7338	0.4635	nan	0.4187	0.4413	0.0833	0.8020	0.0626	nan	0.4483	0.6970	0.0629	0.4012	0.3818	nan	0.2971	0.3643	0.8551	0.7489	0.9153	0.0753	0.0232	0.2256	27
0.2791	0.5138	0.3264	0.3888	0.8699	0.9082	0.9556	0.2156	0.8500	0.6538	nan	0.4691	0.6238	0.1046	0.9234	0.0362	nan	0.6441	0.9040	0.0592	0.5193	0.4442	nan	0.3749	0.4394	0.9309	0.8876	0.9605	0.2636	0.0214	0.2527	0.8137	0.8936	0.1818	0.7657	0.4724	nan	0.4108	0.4396	0.1005	0.8096	0.0355	nan	0.4640	0.6934	0.0564	0.3842	0.3718	nan	0.2963	0.3541	0.8566	0.7598	0.9180	0.1539	0.0190	0.1941	28
0.2728	0.5249	0.3275	0.3886	0.8672	0.9286	0.9447	0.4269	0.7825	0.6896	nan	0.4984	0.5883	0.1082	0.9204	0.0530	nan	0.6501	0.8936	0.0489	0.5277	0.4051	nan	0.3965	0.5070	0.9425	0.8916	0.9645	0.0	0.0170	0.2491	0.7636	0.8983	0.3799	0.7214	0.4693	nan	0.4124	0.4454	0.1	0.8081	0.0510	nan	0.4717	0.6914	0.0449	0.3906	0.3600	nan	0.2989	0.3980	0.8612	0.7709	0.9191	0.0	0.0160	0.2067	29
0.2556	0.5577	0.3283	0.3899	0.8668	0.8620	0.9599	0.4681	0.8029	0.6812	nan	0.5151	0.6041	0.1296	0.9314	0.0517	nan	0.6206	0.9120	0.0537	0.5219	0.3835	nan	0.3950	0.4880	0.9270	0.9054	0.9584	0.0697	0.0167	0.2185	0.7991	0.8851	0.3274	0.7335	0.4697	nan	0.4272	0.4588	0.1172	0.8067	0.0492	nan	0.4710	0.6861	0.0498	0.4047	0.3498	nan	0.3004	0.3865	0.8604	0.7579	0.9202	0.0519	0.0158	0.1782	30
0.2480	0.4931	0.3356	0.3974	0.8742	0.9152	0.9569	0.4642	0.8997	0.7098	nan	0.5025	0.6441	0.1322	0.9129	0.0527	nan	0.6643	0.9249	0.0377	0.4957	0.3950	nan	0.4079	0.4869	0.9195	0.8827	0.9639	0.1584	0.0280	0.1628	0.8160	0.9034	0.3920	0.8109	0.5004	nan	0.4275	0.4552	0.1180	0.8086	0.0495	nan	0.4663	0.6714	0.0363	0.4029	0.3486	nan	0.3016	0.3987	0.8584	0.7624	0.9200	0.1279	0.0253	0.1375	31
0.2467	0.5091	0.3348	0.3964	0.8752	0.8971	0.9568	0.5112	0.8863	0.7226	nan	0.5276	0.6090	0.1273	0.9138	0.0480	nan	0.6762	0.9223	0.0349	0.5263	0.3831	nan	0.3999	0.4924	0.9358	0.8774	0.9652	0.0667	0.0259	0.1795	0.8313	0.9006	0.3902	0.8000	0.5045	nan	0.4362	0.4580	0.1173	0.8150	0.0460	nan	0.4735	0.6802	0.0342	0.4123	0.3509	nan	0.3049	0.3913	0.8605	0.7658	0.9220	0.0444	0.0242	0.1502	32
0.2430	0.5393	0.3325	0.3917	0.8704	0.8953	0.9632	0.5036	0.8081	0.5941	nan	0.5130	0.6436	0.1049	0.9329	0.0502	nan	0.6347	0.8882	0.0652	0.5115	0.4234	nan	0.3974	0.4341	0.9334	0.9137	0.9621	0.0518	0.0264	0.2825	0.8197	0.8887	0.4044	0.7367	0.4565	nan	0.4257	0.4769	0.0954	0.8060	0.0493	nan	0.4708	0.6965	0.0594	0.3946	0.3766	nan	0.2996	0.3611	0.8589	0.7588	0.9239	0.0379	0.0233	0.2182	33
0.2362	0.5184	0.3370	0.3951	0.8716	0.9045	0.9681	0.4519	0.8066	0.5724	nan	0.5364	0.6084	0.1367	0.9124	0.0536	nan	0.6666	0.8956	0.0637	0.5331	0.4525	nan	0.3985	0.5169	0.9250	0.9175	0.9598	0.0945	0.0224	0.2478	0.7909	0.8971	0.4231	0.7306	0.4766	nan	0.4453	0.4660	0.1233	0.8117	0.0523	nan	0.4698	0.6947	0.0584	0.4099	0.3913	nan	0.3072	0.4038	0.8585	0.7556	0.9243	0.0807	0.0205	0.1925	34

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

Library: transformers
Type: segformer
License: other
Created: Nov 4, 2023
Updated: Dec 3, 2023