segformer-b0-finetuned-net-15Oct

PushkarA07/segformer-b0-finetuned-net-15Oct

segformer-b0-finetuned-net-15Oct is a image segmentation model from PushkarA07. 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: Oct 16, 2025
Updated: Oct 16, 2025
SHA: 9a1b9303

Base models

PushkarA07/segformer-b0-finetuned-net-4Sep

Model card

From the Hugging Face model README

segformer-b0-finetuned-net-15Oct

This model is a fine-tuned version of PushkarA07/segformer-b0-finetuned-net-4Sep on the PushkarA07/batch2-tiles_W5 dataset. It achieves the following results on the evaluation set:

Loss: 0.0059
Mean Iou: 0.8668
Mean Accuracy: 0.9041
Overall Accuracy: 0.9978
Accuracy Abnormality: 0.8090
Iou Abnormality: 0.7358

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: 1e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Abnormality	Iou Abnormality
0.0055	0.5556	10	0.0059	0.8661	0.9020	0.9978	0.8047	0.7345
0.0073	1.1111	20	0.0059	0.8664	0.9030	0.9978	0.8067	0.7350
0.0023	1.6667	30	0.0059	0.8668	0.9044	0.9978	0.8097	0.7359
0.0045	2.2222	40	0.0059	0.8668	0.9044	0.9978	0.8096	0.7359
0.0026	2.7778	50	0.0059	0.8671	0.9054	0.9978	0.8115	0.7365
0.0059	3.3333	60	0.0059	0.8668	0.9044	0.9978	0.8095	0.7359
0.0037	3.8889	70	0.0059	0.8667	0.9035	0.9978	0.8078	0.7356
0.0052	4.4444	80	0.0059	0.8667	0.9038	0.9978	0.8084	0.7357
0.007	5.0	90	0.0059	0.8674	0.9065	0.9978	0.8139	0.7370
0.0064	5.5556	100	0.0059	0.8669	0.9046	0.9978	0.8100	0.7361
0.008	6.1111	110	0.0059	0.8665	0.9031	0.9978	0.8070	0.7352
0.008	6.6667	120	0.0059	0.8668	0.9043	0.9978	0.8094	0.7359
0.0046	7.2222	130	0.0059	0.8670	0.9051	0.9978	0.8110	0.7363
0.0025	7.7778	140	0.0059	0.8666	0.9032	0.9978	0.8072	0.7354
0.0077	8.3333	150	0.0059	0.8661	0.9021	0.9978	0.8049	0.7344
0.0041	8.8889	160	0.0059	0.8666	0.9036	0.9978	0.8080	0.7355
0.0034	9.4444	170	0.0059	0.8666	0.9035	0.9978	0.8078	0.7354
0.0042	10.0	180	0.0059	0.8668	0.9041	0.9978	0.8090	0.7358

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.2.0
Tokenizers 0.22.1

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Oct 16, 2025
Updated: Oct 16, 2025