---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- generated
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: document-data-extraction-layoutlmv3
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: generated
      type: generated
      config: sroie
      split: test
      args: sroie
    metrics:
    - name: Precision
      type: precision
      value: 1.0
    - name: Recall
      type: recall
      value: 1.0
    - name: F1
      type: f1
      value: 1.0
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- 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. -->

# document-data-extraction-layoutlmv3

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0015
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 100  | 0.1114          | 0.95      | 0.9635 | 0.9567 | 0.9947   |
| No log        | 2.0   | 200  | 0.0286          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| No log        | 3.0   | 300  | 0.0184          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| No log        | 4.0   | 400  | 0.0163          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1385        | 5.0   | 500  | 0.0141          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1385        | 6.0   | 600  | 0.0123          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1385        | 7.0   | 700  | 0.0122          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1385        | 8.0   | 800  | 0.0108          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1385        | 9.0   | 900  | 0.0104          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.0119        | 10.0  | 1000 | 0.0113          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.0119        | 11.0  | 1100 | 0.0080          | 0.974     | 0.9878 | 0.9809 | 0.9973   |
| 0.0119        | 12.0  | 1200 | 0.0089          | 0.9856    | 0.9736 | 0.9796 | 0.9973   |
| 0.0119        | 13.0  | 1300 | 0.0034          | 0.9959    | 0.9959 | 0.9959 | 0.9994   |
| 0.0119        | 14.0  | 1400 | 0.0037          | 0.9980    | 0.9939 | 0.9959 | 0.9994   |
| 0.006         | 15.0  | 1500 | 0.0024          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
| 0.006         | 16.0  | 1600 | 0.0019          | 0.9980    | 1.0    | 0.9990 | 0.9998   |
| 0.006         | 17.0  | 1700 | 0.0022          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
| 0.006         | 18.0  | 1800 | 0.0017          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.006         | 19.0  | 1900 | 0.0015          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0027        | 20.0  | 2000 | 0.0015          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0