---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model-2024-06-05
  results: []
---

<!-- 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. -->

# model-2024-06-05

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4986
- Precision: 0.7474
- Recall: 0.7807
- F1: 0.7637
- Accuracy: 0.8733

## 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: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.02  | 100  | 1.1715          | 0.4678    | 0.1928 | 0.2730 | 0.6988   |
| No log        | 2.04  | 200  | 0.7350          | 0.7285    | 0.6337 | 0.6778 | 0.8296   |
| No log        | 3.06  | 300  | 0.6022          | 0.7073    | 0.6843 | 0.6957 | 0.8428   |
| No log        | 4.08  | 400  | 0.5440          | 0.7218    | 0.7096 | 0.7157 | 0.8498   |
| 0.9898        | 5.1   | 500  | 0.5059          | 0.7300    | 0.7458 | 0.7378 | 0.8610   |
| 0.9898        | 6.12  | 600  | 0.4998          | 0.7438    | 0.7554 | 0.7496 | 0.8696   |
| 0.9898        | 7.14  | 700  | 0.5104          | 0.7549    | 0.7458 | 0.7503 | 0.8663   |
| 0.9898        | 8.16  | 800  | 0.4817          | 0.7608    | 0.7627 | 0.7617 | 0.8758   |
| 0.9898        | 9.18  | 900  | 0.4845          | 0.76      | 0.7783 | 0.7690 | 0.8758   |
| 0.3448        | 10.2  | 1000 | 0.4986          | 0.7474    | 0.7807 | 0.7637 | 0.8733   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3