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--- |
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license: apache-2.0 |
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base_model: facebook/deit-tiny-distilled-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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model-index: |
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- name: results |
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results: [] |
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pipeline_tag: image-classification |
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datasets: Mozilla/docornot |
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--- |
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This model is a fine-tuned version of [facebook/deit-tiny-distilled-patch16-224](https://huggingface.co./facebook/deit-tiny-distilled-patch16-224) on the [docornot](https://huggingface.co./datasets/tarekziade/docornot) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Accuracy: 1.0 |
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# CO2 emissions |
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This model was trained on an M1 and took 0.322 g of CO2 (measured with [CodeCarbon](https://codecarbon.io/)) |
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# Model description |
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This model is distilled Vision Transformer (ViT) model. |
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Images are presented to the model as a sequence of fixed-size patches (resolution 16x16), which are linearly embedded. |
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# Intended uses & limitations |
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You can use this model to detect if an image is a picture or a document. |
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# Training procedure |
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Source code used to generate this model : https://github.com/mozilla/docornot |
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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: 8 |
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- eval_batch_size: 8 |
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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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- num_epochs: 1 |
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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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| 0.0 | 1.0 | 1600 | 0.0000 | 1.0 | |
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## Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
