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---
license: apache-2.0
base_model: facebook/deit-tiny-distilled-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
pipeline_tag: image-classification
datasets: Mozilla/docornot
---
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.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
# CO2 emissions
This model was trained on an M1 and took 0.322 g of CO2 (measured with [CodeCarbon](https://codecarbon.io/))
# Model description
This model is distilled Vision Transformer (ViT) model.
Images are presented to the model as a sequence of fixed-size patches (resolution 16x16), which are linearly embedded.
# Intended uses & limitations
You can use this model to detect if an image is a picture or a document.
# Training procedure
Source code used to generate this model : https://github.com/mozilla/docornot
## Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
## Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0 | 1.0 | 1600 | 0.0000 | 1.0 |
## Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2 |