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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-v3 |
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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-v3 |
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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: 0.0541 |
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- Accuracy: 0.9817 |
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- F1: 0.9834 |
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- Recall: 0.9834 |
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- Precision: 0.9834 |
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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: 5e-05 |
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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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| 0.2481 | 1.0 | 233 | 0.0846 | 0.9667 | 0.9699 | 0.9737 | 0.9662 | |
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| 0.1881 | 2.0 | 466 | 0.0773 | 0.9726 | 0.9756 | 0.9912 | 0.9604 | |
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| 0.1036 | 3.0 | 699 | 0.0691 | 0.9774 | 0.9796 | 0.9815 | 0.9777 | |
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| 0.0007 | 4.0 | 932 | 0.0698 | 0.9817 | 0.9835 | 0.9854 | 0.9816 | |
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| 0.0029 | 5.0 | 1165 | 0.0541 | 0.9817 | 0.9834 | 0.9834 | 0.9834 | |
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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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