---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLMv3_97_2
  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_97_2

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5892
- Precision: 0.8315
- Recall: 0.7721
- F1: 0.8007
- Accuracy: 0.9122

## 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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.56  | 100  | 0.4807          | 0.6058    | 0.4966 | 0.5458 | 0.8297   |
| No log        | 5.13  | 200  | 0.3940          | 0.7553    | 0.6088 | 0.6742 | 0.8771   |
| No log        | 7.69  | 300  | 0.3804          | 0.7438    | 0.7109 | 0.7270 | 0.9008   |
| No log        | 10.26 | 400  | 0.3900          | 0.8185    | 0.8129 | 0.8157 | 0.9096   |
| 0.2035        | 12.82 | 500  | 0.4102          | 0.8255    | 0.7721 | 0.7979 | 0.9087   |
| 0.2035        | 15.38 | 600  | 0.4077          | 0.8095    | 0.8095 | 0.8095 | 0.9148   |
| 0.2035        | 17.95 | 700  | 0.4915          | 0.7867    | 0.7653 | 0.7759 | 0.8982   |
| 0.2035        | 20.51 | 800  | 0.4861          | 0.8269    | 0.7959 | 0.8111 | 0.9131   |
| 0.2035        | 23.08 | 900  | 0.5051          | 0.7818    | 0.7313 | 0.7557 | 0.9052   |
| 0.0117        | 25.64 | 1000 | 0.5404          | 0.8303    | 0.7653 | 0.7965 | 0.9069   |
| 0.0117        | 28.21 | 1100 | 0.6110          | 0.8492    | 0.7279 | 0.7839 | 0.9061   |
| 0.0117        | 30.77 | 1200 | 0.5379          | 0.8014    | 0.7823 | 0.7917 | 0.9096   |
| 0.0117        | 33.33 | 1300 | 0.5343          | 0.8057    | 0.7755 | 0.7903 | 0.9131   |
| 0.0117        | 35.9  | 1400 | 0.5590          | 0.8333    | 0.7653 | 0.7979 | 0.9140   |
| 0.0013        | 38.46 | 1500 | 0.6296          | 0.8488    | 0.7449 | 0.7935 | 0.9122   |
| 0.0013        | 41.03 | 1600 | 0.6089          | 0.8421    | 0.7619 | 0.8    | 0.9122   |
| 0.0013        | 43.59 | 1700 | 0.5869          | 0.8291    | 0.7755 | 0.8014 | 0.9140   |
| 0.0013        | 46.15 | 1800 | 0.5847          | 0.8291    | 0.7755 | 0.8014 | 0.9140   |
| 0.0013        | 48.72 | 1900 | 0.5881          | 0.8285    | 0.7721 | 0.7993 | 0.9131   |
| 0.0004        | 51.28 | 2000 | 0.5892          | 0.8315    | 0.7721 | 0.8007 | 0.9122   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3