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Browse files- README.md +91 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- image-classification
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- fakevsreal
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: real_vs_fake_image_model_vit_base
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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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# real_vs_fake_image_model_vit_base
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0189
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- Accuracy: 0.9953
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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: 3e-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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.0094 | 0.1883 | 100 | 0.0243 | 0.9941 |
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| 0.0165 | 0.3766 | 200 | 0.0351 | 0.9901 |
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| 0.0239 | 0.5650 | 300 | 0.0470 | 0.9876 |
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| 0.0179 | 0.7533 | 400 | 0.0678 | 0.9856 |
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| 0.0166 | 0.9416 | 500 | 0.0296 | 0.9920 |
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| 0.0138 | 1.1299 | 600 | 0.0337 | 0.9926 |
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| 0.0574 | 1.3183 | 700 | 0.1020 | 0.9772 |
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| 0.0256 | 1.5066 | 800 | 0.0612 | 0.9847 |
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| 0.0327 | 1.6949 | 900 | 0.0616 | 0.9846 |
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| 0.0086 | 1.8832 | 1000 | 0.0272 | 0.9923 |
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| 0.008 | 2.0716 | 1100 | 0.0329 | 0.9920 |
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| 0.0014 | 2.2599 | 1200 | 0.0250 | 0.9939 |
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| 0.0132 | 2.4482 | 1300 | 0.0248 | 0.9937 |
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| 0.0189 | 2.6365 | 1400 | 0.0266 | 0.9936 |
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| 0.0034 | 2.8249 | 1500 | 0.0225 | 0.9948 |
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| 0.009 | 3.0132 | 1600 | 0.0240 | 0.9942 |
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| 0.0009 | 3.2015 | 1700 | 0.0244 | 0.9942 |
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| 0.0054 | 3.3898 | 1800 | 0.0339 | 0.9928 |
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| 0.0046 | 3.5782 | 1900 | 0.0248 | 0.9945 |
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| 0.0135 | 3.7665 | 2000 | 0.0245 | 0.9945 |
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| 0.0274 | 3.9548 | 2100 | 0.0241 | 0.9947 |
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| 0.0031 | 4.1431 | 2200 | 0.0225 | 0.9947 |
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| 0.0121 | 4.3315 | 2300 | 0.0210 | 0.9952 |
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| 0.0055 | 4.5198 | 2400 | 0.0209 | 0.9953 |
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| 0.0183 | 4.7081 | 2500 | 0.0197 | 0.9955 |
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| 0.0077 | 4.8964 | 2600 | 0.0189 | 0.9953 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 343223968
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version https://git-lfs.github.com/spec/v1
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oid sha256:ba90e2477e6780da18b967940709e5023dc76ffe7d694b3191801efb7a45470e
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size 343223968
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