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ViT-threat-classification-v2
SABR22/ViT-threat-classification-v2
ViT-threat-classification-v2 is a image classification model from SABR22. 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
- Nov 18, 2024
- Updated
- Nov 19, 2024
- SHA
- 77182d21
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-threat-classification-v2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. This is model created as a prrof of concept for a Carleton University computer vision event. It is by no means meant to be used in deliverable systems in its current state, and should be used exclusively for research and development. It achieves the following results on the evaluation set:
- Loss: 0.0381
- F1: 0.9657
- Precision: 0.9563
- Recall: 0.9752
Model description
More information needed
Intended uses & limitations
More information needed
Collaborators
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.0744 | 0.9985 | 326 | 0.0576 | 0.9466 | 0.9738 | 0.9208 |
| 0.0449 | 2.0 | 653 | 0.0397 | 0.9641 | 0.9747 | 0.9538 |
| 0.0207 | 2.9985 | 979 | 0.0409 | 0.9647 | 0.9607 | 0.9686 |
| 0.0342 | 4.0 | 1306 | 0.0382 | 0.9650 | 0.9518 | 0.9785 |
| 0.0286 | 4.9923 | 1630 | 0.0381 | 0.9657 | 0.9563 | 0.9752 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 18, 2024
- Updated
- Nov 19, 2024