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vit-real-fake-classification-v4
0xfffm4bs/vit-real-fake-classification-v4
vit-real-fake-classification-v4 is a machine learning model from 0xfffm4bs. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
<<<<<<< HEAD --- license: apache-2.0 --- ======= --- license: apache-2.0 basemodel: google/vit-base-patch16-224 tags: - generatedfromtrainer metrics: - accuracy - f1 - recall - precision model-index: - name: vit-real-…
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At a glance
- Model type
- vit
- Access
- Public
- Created
- Aug 19, 2025
- Updated
- Aug 19, 2025
- SHA
- ed815dbc
Model card
From the Hugging Face model README
<<<<<<< HEAD
license: apache-2.0
=======
license: apache-2.0 base_model: google/vit-base-patch16-224 tags:
- generated_from_trainer metrics:
- accuracy
- f1
- recall
- precision model-index:
- name: vit-real-fake-classification-v4 results: []
<!-- 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-real-fake-classification-v4
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0585
- Accuracy: 0.9796
- F1: 0.9815
- Recall: 0.9815
- Precision: 0.9815
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.1295 | 1.0 | 233 | 0.2414 | 0.9151 | 0.9280 | 0.9912 | 0.8723 |
| 0.4466 | 2.0 | 466 | 0.1042 | 0.9646 | 0.9680 | 0.9718 | 0.9643 |
| 0.3302 | 3.0 | 699 | 0.0667 | 0.9764 | 0.9786 | 0.9776 | 0.9795 |
| 0.0003 | 4.0 | 932 | 0.0995 | 0.9731 | 0.9758 | 0.9796 | 0.9720 |
| 0.0002 | 5.0 | 1165 | 0.0585 | 0.9796 | 0.9815 | 0.9815 | 0.9815 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
3516007fbc33bd89b07b531bf52afda1db96b6f3
- Type
- vit
- Created
- Aug 19, 2025
- Updated
- Aug 19, 2025