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SegFormer_Clean_Set1_240430_V2-Augmented_mit-b5_RGB
Hasano20/SegFormer_Clean_Set1_240430_V2-Augmented_mit-b5_RGB
SegFormer_Clean_Set1_240430_V2-Augmented_mit-b5_RGB 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 24, 2024
- Updated
- Jun 24, 2024
- SHA
- efce221a
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
SegFormer_Clean_Set1_240430_V2-Augmented_mit-b5_RGB
This model is a fine-tuned version of nvidia/mit-b5 on the Hasano20/Clean_Set1_240430_V2-Augmented dataset. It achieves the following results on the evaluation set:
- Loss: 0.4812
- Mean Iou: 0.6072
- Mean Accuracy: 0.6905
- Overall Accuracy: 0.8761
- Accuracy Background: 0.8967
- Accuracy Melt: 0.2439
- Accuracy Substrate: 0.9311
- Iou Background: 0.8325
- Iou Melt: 0.1423
- Iou Substrate: 0.8467
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2826 | 6.6667 | 20 | 0.4812 | 0.6072 | 0.6905 | 0.8761 | 0.8967 | 0.2439 | 0.9311 | 0.8325 | 0.1423 | 0.8467 |
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 24, 2024
- Updated
- Jun 24, 2024