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SegFormer_mit-b5_Final-Set4-Grayscale_Test_4_lr0.0001
Hasano20/SegFormer_mit-b5_Final-Set4-Grayscale_Test_4_lr0.0001
SegFormer_mit-b5_Final-Set4-Grayscale_Test_4_lr0.0001 is a machine learning model from Hasano20. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Oct 12, 2024
- Updated
- Oct 12, 2024
- SHA
- d0e1caaf
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_mit-b5_Final-Set4-Grayscale_Test_4_lr0.0001
This model is a fine-tuned version of nvidia/mit-b5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1193
- Mean Iou: 0.8167
- Mean Accuracy: 0.8517
- Overall Accuracy: 0.9601
- Accuracy Background: 0.9780
- Accuracy Melt: 0.5944
- Accuracy Substrate: 0.9827
- Iou Background: 0.9616
- Iou Melt: 0.5614
- Iou Substrate: 0.9270
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1133 | 0.8850 | 50 | 0.1193 | 0.8167 | 0.8517 | 0.9601 | 0.9780 | 0.5944 | 0.9827 | 0.9616 | 0.5614 | 0.9270 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
- Type
- segformer
- License
- other
- Created
- Oct 12, 2024
- Updated
- Oct 12, 2024