---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutLMv3-finetuned-confluence
  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-confluence

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1354
- Precision: 0.8992
- Recall: 0.9126
- F1: 0.9058
- Accuracy: 0.8578

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 8.33  | 250  | 0.9563          | 0.8807    | 0.9056 | 0.8930 | 0.8505   |
| 0.0199        | 16.67 | 500  | 1.0827          | 0.8792    | 0.9041 | 0.8915 | 0.8393   |
| 0.0199        | 25.0  | 750  | 1.0539          | 0.8834    | 0.9036 | 0.8934 | 0.8493   |
| 0.0048        | 33.33 | 1000 | 1.1217          | 0.8944    | 0.9131 | 0.9036 | 0.8583   |
| 0.0048        | 41.67 | 1250 | 1.1195          | 0.9004    | 0.9071 | 0.9037 | 0.8616   |
| 0.0025        | 50.0  | 1500 | 1.1927          | 0.8923    | 0.9056 | 0.8989 | 0.8467   |
| 0.0025        | 58.33 | 1750 | 1.1155          | 0.9017    | 0.9116 | 0.9066 | 0.8640   |
| 0.0008        | 66.67 | 2000 | 1.1871          | 0.8971    | 0.9056 | 0.9014 | 0.8395   |
| 0.0008        | 75.0  | 2250 | 1.1709          | 0.9007    | 0.9106 | 0.9056 | 0.8420   |
| 0.0006        | 83.33 | 2500 | 1.1354          | 0.8992    | 0.9126 | 0.9058 | 0.8578   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2