Model save
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README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- recall
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- precision
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model-index:
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- name: vit-real-fake-classification-v4
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# vit-real-fake-classification-v4
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0585
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- Accuracy: 0.9796
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- F1: 0.9815
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- Recall: 0.9815
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- Precision: 0.9815
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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| 0.1295 | 1.0 | 233 | 0.2414 | 0.9151 | 0.9280 | 0.9912 | 0.8723 |
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| 0.4466 | 2.0 | 466 | 0.1042 | 0.9646 | 0.9680 | 0.9718 | 0.9643 |
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| 0.3302 | 3.0 | 699 | 0.0667 | 0.9764 | 0.9786 | 0.9776 | 0.9795 |
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| 0.0003 | 4.0 | 932 | 0.0995 | 0.9731 | 0.9758 | 0.9796 | 0.9720 |
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| 0.0002 | 5.0 | 1165 | 0.0585 | 0.9796 | 0.9815 | 0.9815 | 0.9815 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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