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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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<!-- 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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# document-spoof |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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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