test_os_counties

rwood-97/test_os_counties

test_os_counties is a image segmentation model from rwood-97. 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

1% of all-time downloads

All-time downloads

640

Public

Repo size

29.8 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin14.9 MB · 100%

At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: Nov 7, 2023
Updated: Nov 7, 2023
SHA: 36c50e4a

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

test_os_counties

This model is a fine-tuned version of nvidia/mit-b0 on the rwood-97/os_counties dataset. It achieves the following results on the evaluation set:

Loss: 1.8997
Mean Iou: 0.1075
Mean Accuracy: 0.4992
Overall Accuracy: 0.2118
Accuracy Non-map: 0.9899
Accuracy Map: 0.0084
Iou Non-map: 0.2065
Iou Map: 0.0084

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: 4
eval_batch_size: 4
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 Non-map	Accuracy Map	Iou Non-map	Iou Map
0.4081	0.41	20	0.8267	0.2101	0.4981	0.3478	0.7548	0.2414	0.1934	0.2268
0.3939	0.82	40	0.8190	0.2387	0.4978	0.3898	0.6821	0.3134	0.1881	0.2894
0.3319	1.22	60	0.9487	0.1579	0.4976	0.2759	0.8762	0.1191	0.2005	0.1153
0.3234	1.63	80	0.9275	0.1847	0.4974	0.3120	0.8138	0.1809	0.1969	0.1725
0.3932	2.04	100	0.9053	0.1892	0.4974	0.3183	0.8031	0.1916	0.1962	0.1822
0.3412	2.45	120	0.8265	0.2385	0.4973	0.3895	0.6814	0.3132	0.1878	0.2891
0.2976	2.86	140	1.3713	0.1127	0.4987	0.2182	0.9778	0.0197	0.2058	0.0195
0.2803	3.27	160	1.6436	0.1095	0.4993	0.2143	0.9860	0.0126	0.2064	0.0125
0.3686	3.67	180	1.2379	0.1221	0.4982	0.2298	0.9564	0.0399	0.2047	0.0395
0.3434	4.08	200	1.1857	0.1385	0.4978	0.2507	0.9197	0.0758	0.2028	0.0743
0.2951	4.49	220	1.3947	0.1160	0.4986	0.2223	0.9704	0.0268	0.2054	0.0266
0.2333	4.9	240	1.5480	0.1170	0.4988	0.2236	0.9687	0.0288	0.2054	0.0286
0.2491	5.31	260	1.6563	0.1136	0.4990	0.2194	0.9764	0.0215	0.2058	0.0214
0.2706	5.71	280	1.9766	0.1058	0.4995	0.2098	0.9942	0.0048	0.2068	0.0048
0.2171	6.12	300	1.6191	0.1117	0.4989	0.2170	0.9804	0.0175	0.2060	0.0174
0.2352	6.53	320	1.8075	0.1102	0.4992	0.2151	0.9842	0.0141	0.2062	0.0141
0.2953	6.94	340	1.4709	0.1178	0.4986	0.2245	0.9667	0.0305	0.2053	0.0303
0.2799	7.35	360	1.3843	0.1300	0.4982	0.2399	0.9392	0.0571	0.2038	0.0562
0.2285	7.76	380	1.7799	0.1101	0.4991	0.2150	0.9842	0.0140	0.2062	0.0139
0.3461	8.16	400	1.7282	0.1106	0.4989	0.2157	0.9826	0.0153	0.2061	0.0152
0.1867	8.57	420	2.3356	0.1042	0.4997	0.2079	0.9981	0.0014	0.2070	0.0014
0.1731	8.98	440	2.1465	0.1050	0.4996	0.2089	0.9959	0.0032	0.2069	0.0032
0.224	9.39	460	2.3467	0.1047	0.4996	0.2084	0.9969	0.0024	0.2070	0.0024
0.2199	9.8	480	1.8997	0.1075	0.4992	0.2118	0.9899	0.0084	0.2065	0.0084

Framework versions

Transformers 4.35.0.dev0
Pytorch 2.1.0
Datasets 2.14.5
Tokenizers 0.14.1

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Nov 7, 2023
Updated: Nov 7, 2023