---
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-funsd2
  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-funsd2

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: 0.6633
- Precision: 0.9027
- Recall: 0.9090
- F1: 0.9058
- Accuracy: 0.8500

## 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: 5e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 120

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.9091  | 10   | 0.9825          | 0.5685    | 0.6133 | 0.5901 | 0.6804   |
| No log        | 1.8182  | 20   | 0.6492          | 0.7647    | 0.8215 | 0.7921 | 0.7781   |
| No log        | 2.7273  | 30   | 0.5079          | 0.8037    | 0.8635 | 0.8326 | 0.8370   |
| No log        | 3.6364  | 40   | 0.5371          | 0.8600    | 0.8924 | 0.8759 | 0.8428   |
| No log        | 4.5455  | 50   | 0.5696          | 0.8753    | 0.8968 | 0.8859 | 0.8348   |
| No log        | 5.4545  | 60   | 0.6309          | 0.8733    | 0.8863 | 0.8797 | 0.8272   |
| No log        | 6.3636  | 70   | 0.6272          | 0.8878    | 0.9003 | 0.8940 | 0.8494   |
| No log        | 7.2727  | 80   | 0.6168          | 0.9025    | 0.9151 | 0.9088 | 0.8688   |
| No log        | 8.1818  | 90   | 0.6458          | 0.9094    | 0.9134 | 0.9114 | 0.8588   |
| No log        | 9.0909  | 100  | 0.6830          | 0.8985    | 0.9064 | 0.9024 | 0.8490   |
| No log        | 10.0    | 110  | 0.6325          | 0.9086    | 0.9221 | 0.9153 | 0.8502   |
| No log        | 10.9091 | 120  | 0.6633          | 0.9027    | 0.9090 | 0.9058 | 0.8500   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1