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vit-base-crack-classification-129
akashmaggon/vit-base-crack-classification-129
vit-base-crack-classification-129 is a image classification model from akashmaggon. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Dec 1, 2023
- Updated
- Dec 1, 2023
- SHA
- 687c9170
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. -->
vit-base-crack-classification-129
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4641
- Accuracy: 0.8889
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-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3061 | 1.0 | 212 | 1.1094 | 0.6759 |
| 0.844 | 2.0 | 424 | 0.7624 | 0.7940 |
| 0.5972 | 3.0 | 636 | 0.5760 | 0.8472 |
| 0.4424 | 4.0 | 848 | 0.4922 | 0.875 |
| 0.3815 | 5.0 | 1060 | 0.4641 | 0.8889 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 1, 2023
- Updated
- Dec 1, 2023