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habibi26
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document-spoof

Image Classification
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Safetensors
clip
Generated from Trainer
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README.md ADDED
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+ ---
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+ base_model: openai/clip-vit-base-patch32
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: document-spoof
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9767441860465116
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+ ---
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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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+
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+ # document-spoof
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+
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+ This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1105
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+ - Accuracy: 0.9767
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9524 | 5 | 0.5211 | 0.8837 |
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+ | No log | 1.9048 | 10 | 0.2271 | 0.8837 |
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+ | 0.545 | 2.8571 | 15 | 0.0975 | 0.9884 |
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+ | 0.545 | 4.0 | 21 | 0.1020 | 0.9767 |
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+ | 0.545 | 4.9524 | 26 | 0.3087 | 0.9535 |
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+ | 0.472 | 5.9048 | 31 | 0.3385 | 0.8023 |
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+ | 0.472 | 6.8571 | 36 | 0.2358 | 0.8605 |
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+ | 0.472 | 8.0 | 42 | 0.3675 | 0.8605 |
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+ | 0.3762 | 8.9524 | 47 | 0.1460 | 0.9535 |
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+ | 0.3762 | 9.9048 | 52 | 0.6158 | 0.8140 |
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+ | 0.3762 | 10.8571 | 57 | 0.3228 | 0.9186 |
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+ | 0.1586 | 12.0 | 63 | 0.0248 | 0.9884 |
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+ | 0.1586 | 12.9524 | 68 | 0.0639 | 0.9651 |
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+ | 0.1586 | 13.9048 | 73 | 0.5674 | 0.8488 |
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+ | 0.1159 | 14.8571 | 78 | 0.0291 | 0.9884 |
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+ | 0.1159 | 16.0 | 84 | 0.0539 | 0.9884 |
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+ | 0.1159 | 16.9524 | 89 | 0.0772 | 0.9767 |
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+ | 0.0366 | 17.9048 | 94 | 0.0031 | 1.0 |
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+ | 0.0366 | 18.8571 | 99 | 0.1506 | 0.9535 |
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+ | 0.0179 | 20.0 | 105 | 0.0007 | 1.0 |
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+ | 0.0179 | 20.9524 | 110 | 0.1427 | 0.9535 |
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+ | 0.0179 | 21.9048 | 115 | 0.2299 | 0.9419 |
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+ | 0.0036 | 22.8571 | 120 | 0.1373 | 0.9767 |
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+ | 0.0036 | 23.8095 | 125 | 0.1105 | 0.9767 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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