---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
- layoutlmv3
- token_classifier
- layout_analysis
datasets:
- pierreguillou/DocLayNet-small
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-DocLayNet
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: doc_lay_net-small
      type: doc_lay_net-small
      config: DocLayNet_2022.08_processed_on_2023.01
      split: test
      args: DocLayNet_2022.08_processed_on_2023.01
    metrics:
    - name: Precision
      type: precision
      value: 0.6178861788617886
    - name: Recall
      type: recall
      value: 0.7238095238095238
    - name: F1
      type: f1
      value: 0.6666666666666667
    - name: Accuracy
      type: accuracy
      value: 0.8719611021069692
language:
- en
pipeline_tag: token-classification
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# layoutlmv3-finetuned-DocLayNet

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the doc_lay_net-small dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5644
- Precision: 0.6179
- Recall: 0.7238
- F1: 0.6667
- Accuracy: 0.8720

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3383        | 0.58  | 200  | 0.8358          | 0.3007    | 0.4381 | 0.3566 | 0.7724   |
| 0.8308        | 1.16  | 400  | 0.6735          | 0.4634    | 0.5429 | 0.5    | 0.8084   |
| 0.518         | 1.74  | 600  | 0.5706          | 0.5373    | 0.6857 | 0.6025 | 0.8399   |
| 0.3856        | 2.33  | 800  | 0.6303          | 0.6032    | 0.7238 | 0.6580 | 0.8648   |
| 0.2558        | 2.91  | 1000 | 0.5644          | 0.6179    | 0.7238 | 0.6667 | 0.8720   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2



### How to Train & Inference:

Check this out this repo: https://github.com/mit1280/Document-AI