segformer-b0-miic-tl

yijisuk/segformer-b0-miic-tl

segformer-b0-miic-tl is a image segmentation model from yijisuk. 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 8, 2024
Updated: Jun 26, 2024
SHA: 6e195014

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

segformer-b0-miic-tl

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

Loss: 0.3415
Mean Iou: 0.4569
Mean Accuracy: 0.9138
Overall Accuracy: 0.9138
Accuracy Unlabeled: nan
Accuracy Circuit: 0.9138
Iou Unlabeled: 0.0
Iou Circuit: 0.9138
Dice Coefficient: 0.8323

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 Circuit	Iou Circuit	Dice Coefficient
0.3496	3.12	250	0.3203	0.4832	0.9665	0.9665	nan	0.9665	0.9665	0.8163
0.2808	6.25	500	0.3289	0.4814	0.9629	0.9629	nan	0.9629	0.9629	0.8271
0.2582	9.38	750	0.3404	0.4670	0.9339	0.9339	nan	0.9339	0.9339	0.8327
0.2791	12.5	1000	0.3033	0.4591	0.9181	0.9181	nan	0.9181	0.9181	0.8300
0.2668	15.62	1250	0.3117	0.4559	0.9118	0.9118	nan	0.9118	0.9118	0.8285
0.2531	18.75	1500	0.2652	0.4686	0.9373	0.9373	nan	0.9373	0.9373	0.8432
0.2326	21.88	1750	0.3256	0.4604	0.9208	0.9208	nan	0.9208	0.9208	0.8315
0.2361	25.0	2000	0.3129	0.4656	0.9313	0.9313	nan	0.9313	0.9313	0.8400
0.2167	28.12	2250	0.3135	0.4558	0.9116	0.9116	nan	0.9116	0.9116	0.8290
0.2133	31.25	2500	0.3132	0.4560	0.9120	0.9120	nan	0.9120	0.9120	0.8219
0.1769	34.38	2750	0.3200	0.4441	0.8882	0.8882	nan	0.8882	0.8882	0.8176
0.1899	37.5	3000	0.3342	0.4612	0.9224	0.9224	nan	0.9224	0.9224	0.8363
0.1765	40.62	3250	0.3445	0.4625	0.9249	0.9249	nan	0.9249	0.9249	0.8369
0.1739	43.75	3500	0.3235	0.4608	0.9216	0.9216	nan	0.9216	0.9216	0.8373
0.1639	46.88	3750	0.3527	0.4591	0.9181	0.9181	nan	0.9181	0.9181	0.8342
0.1734	50.0	4000	0.3415	0.4569	0.9138	0.9138	nan	0.9138	0.9138	0.8323

Framework versions

Transformers 4.36.2
Pytorch 1.11.0+cu115
Datasets 2.15.0
Tokenizers 0.15.0

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Jun 8, 2024
Updated: Jun 26, 2024