segformer_Clean_Set1_95images

Hasano20/segformer_Clean_Set1_95images

segformer_Clean_Set1_95images is a image segmentation model from Hasano20. 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: Jun 19, 2024
Updated: Jun 19, 2024
SHA: 01f520bd

Base models

nvidia/mit-b4

Model card

From the Hugging Face model README

segformer_Clean_Set1_95images

This model is a fine-tuned version of nvidia/mit-b4 on the Hasano20/Clean_Set1_95images dataset. It achieves the following results on the evaluation set:

Loss: 0.0223
Mean Iou: 0.6447
Mean Accuracy: 0.9824
Overall Accuracy: 0.9886
Accuracy Background: nan
Accuracy Melt: 0.9724
Accuracy Substrate: 0.9923
Iou Background: 0.0
Iou Melt: 0.9458
Iou Substrate: 0.9882

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: 0.0001
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Background	Accuracy Melt	Accuracy Substrate	Iou Melt	Iou Substrate
0.2051	1.1765	20	0.3764	0.3339	0.5766	0.8354	nan	0.1639	0.9894	0.1612	0.8404
0.3486	2.3529	40	0.1932	0.4595	0.7687	0.8745	nan	0.6000	0.9375	0.4928	0.8858
0.0831	3.5294	60	0.2016	0.4101	0.6782	0.8792	nan	0.3576	0.9988	0.3570	0.8732
0.0809	4.7059	80	0.0763	0.5787	0.9243	0.9507	nan	0.8822	0.9664	0.7830	0.9531
0.0325	5.8824	100	0.0694	0.6028	0.9436	0.9618	nan	0.9146	0.9727	0.8479	0.9606
0.0279	7.0588	120	0.0460	0.6142	0.9520	0.9712	nan	0.9213	0.9826	0.8739	0.9686
0.0493	8.2353	140	0.0353	0.6297	0.9648	0.9802	nan	0.9404	0.9893	0.9092	0.9797
0.0286	9.4118	160	0.0366	0.6261	0.9643	0.9765	nan	0.9449	0.9837	0.8997	0.9787
0.0463	10.5882	180	0.0258	0.6425	0.9798	0.9879	nan	0.9669	0.9927	0.9414	0.9862
0.0145	11.7647	200	0.0302	0.6324	0.9652	0.9821	nan	0.9382	0.9922	0.9162	0.9810
0.0221	12.9412	220	0.0262	0.6379	0.9733	0.9850	nan	0.9547	0.9919	0.9289	0.9848
0.0109	14.1176	240	0.0236	0.6417	0.9764	0.9869	nan	0.9595	0.9932	0.9379	0.9871
0.0122	15.2941	260	0.0252	0.6407	0.9812	0.9866	nan	0.9725	0.9898	0.9358	0.9864
0.0101	16.4706	280	0.0239	0.6417	0.9799	0.9869	nan	0.9686	0.9911	0.9382	0.9870
0.0113	17.6471	300	0.0231	0.6425	0.9798	0.9874	nan	0.9675	0.9920	0.9399	0.9875
0.0086	18.8235	320	0.0225	0.6444	0.9826	0.9885	nan	0.9733	0.9919	0.9451	0.9882
0.0086	20.0	340	0.0223	0.6447	0.9824	0.9886	nan	0.9724	0.9923	0.9458	0.9882

Framework versions

Transformers 4.41.2
Pytorch 2.0.1+cu117
Datasets 2.19.2
Tokenizers 0.19.1

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Jun 19, 2024
Updated: Jun 19, 2024