---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-UsingAlgoDataset_427Images
  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. -->

# layoutlmv3-finetuned-UsingAlgoDataset_427Images

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0022
- Precision: 0.9892
- Recall: 0.9880
- F1: 0.9886
- Accuracy: 0.9997

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.62  | 50   | 0.0349          | 0.7521    | 0.6300 | 0.6857 | 0.9926   |
| No log        | 1.25  | 100  | 0.0080          | 0.9538    | 0.9405 | 0.9471 | 0.9985   |
| No log        | 1.88  | 150  | 0.0044          | 0.9750    | 0.9723 | 0.9736 | 0.9992   |
| No log        | 2.5   | 200  | 0.0032          | 0.9834    | 0.9827 | 0.9831 | 0.9995   |
| No log        | 3.12  | 250  | 0.0037          | 0.9710    | 0.9784 | 0.9747 | 0.9992   |
| No log        | 3.75  | 300  | 0.0026          | 0.9861    | 0.9852 | 0.9857 | 0.9996   |
| No log        | 4.38  | 350  | 0.0023          | 0.9880    | 0.9871 | 0.9875 | 0.9996   |
| No log        | 5.0   | 400  | 0.0022          | 0.9883    | 0.9871 | 0.9877 | 0.9997   |
| No log        | 5.62  | 450  | 0.0022          | 0.9892    | 0.9880 | 0.9886 | 0.9997   |
| 0.029         | 6.25  | 500  | 0.0022          | 0.9892    | 0.9880 | 0.9886 | 0.9997   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3