segformer-b0-winter

johanhag/segformer-b0-winter

segformer-b0-winter is a image segmentation model from johanhag. 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: Dec 14, 2023
Updated: Dec 14, 2023
SHA: 9e1949ff

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

segformer-b0-winter

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

Loss: 0.1441
Mean Iou: 0.8861
Mean Accuracy: 0.9456
Overall Accuracy: 0.9660
Accuracy Unlabeled: nan
Accuracy Object: nan
Accuracy Road: 0.9769
Accuracy Side walk: 0.8930
Accuracy Car: 0.9347
Accuracy Pedestrian: nan
Accuracy Other: 0.9779
Iou Unlabeled: nan
Iou Object: nan
Iou Road: 0.9197
Iou Side walk: 0.8250
Iou Car: 0.8319
Iou Pedestrian: nan
Iou Other: 0.9678

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Object	Accuracy Road	Accuracy Side walk	Accuracy Car	Accuracy Pedestrian	Accuracy Other	Iou Unlabeled	Iou Object	Iou Road	Iou Side walk	Iou Car	Iou Pedestrian	Iou Other
0.2207	4.0	20	0.2300	0.8576	0.9439	0.9583	nan	nan	0.9738	0.8767	0.9564	nan	0.9686	nan	nan	0.9018	0.8000	0.7670	nan	0.9617
0.1792	8.0	40	0.2126	0.8696	0.9457	0.9614	nan	nan	0.9768	0.8911	0.9444	nan	0.9706	nan	nan	0.9106	0.8122	0.7924	nan	0.9633
0.1527	12.0	60	0.1869	0.8769	0.9470	0.9634	nan	nan	0.9776	0.9023	0.9364	nan	0.9718	nan	nan	0.9180	0.8165	0.8085	nan	0.9647
0.1329	16.0	80	0.1787	0.8783	0.9429	0.9634	nan	nan	0.9772	0.8880	0.9314	nan	0.9749	nan	nan	0.9126	0.8117	0.8229	nan	0.9661
0.1746	20.0	100	0.1651	0.8864	0.9511	0.9668	nan	nan	0.9771	0.9126	0.9395	nan	0.9751	nan	nan	0.9258	0.8369	0.8157	nan	0.9671
0.1218	24.0	120	0.1652	0.8798	0.9444	0.9643	nan	nan	0.9791	0.8858	0.9370	nan	0.9757	nan	nan	0.9140	0.8156	0.8224	nan	0.9673
0.0816	28.0	140	0.1473	0.8921	0.9521	0.9684	nan	nan	0.9723	0.9199	0.9383	nan	0.9780	nan	nan	0.9299	0.8478	0.8231	nan	0.9676
0.0893	32.0	160	0.1490	0.8892	0.9502	0.9672	nan	nan	0.9749	0.9140	0.9354	nan	0.9766	nan	nan	0.9260	0.8384	0.825	nan	0.9673
0.0849	36.0	180	0.1517	0.8861	0.9476	0.9660	nan	nan	0.9791	0.8987	0.9367	nan	0.9760	nan	nan	0.9205	0.8258	0.8308	nan	0.9674
0.1625	40.0	200	0.1519	0.8843	0.9468	0.9654	nan	nan	0.9777	0.8938	0.9394	nan	0.9763	nan	nan	0.9176	0.8235	0.8289	nan	0.9673
0.1396	44.0	220	0.1500	0.8850	0.9476	0.9655	nan	nan	0.9791	0.8949	0.9408	nan	0.9757	nan	nan	0.9187	0.8223	0.8317	nan	0.9674
0.0931	48.0	240	0.1441	0.8861	0.9456	0.9660	nan	nan	0.9769	0.8930	0.9347	nan	0.9779	nan	nan	0.9197	0.8250	0.8319	nan	0.9678

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Dec 14, 2023
Updated: Dec 14, 2023