---
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-FUNSD
  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-FUNSD

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: 0.6088
- Precision: 0.9024
- Recall: 0.9190
- F1: 0.9107
- Accuracy: 0.8544

## 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        | 1.33  | 100  | 0.6659          | 0.7835    | 0.8217 | 0.8021 | 0.7825   |
| No log        | 2.67  | 200  | 0.5631          | 0.8229    | 0.8912 | 0.8557 | 0.7903   |
| No log        | 4.0   | 300  | 0.4653          | 0.8470    | 0.8992 | 0.8723 | 0.8389   |
| No log        | 5.33  | 400  | 0.5080          | 0.8526    | 0.9081 | 0.8795 | 0.8324   |
| 0.5612        | 6.67  | 500  | 0.5200          | 0.8733    | 0.9036 | 0.8882 | 0.8429   |
| 0.5612        | 8.0   | 600  | 0.5480          | 0.8878    | 0.9160 | 0.9017 | 0.8531   |
| 0.5612        | 9.33  | 700  | 0.5655          | 0.8894    | 0.9146 | 0.9018 | 0.8521   |
| 0.5612        | 10.67 | 800  | 0.5971          | 0.8943    | 0.9160 | 0.9050 | 0.8514   |
| 0.5612        | 12.0  | 900  | 0.5873          | 0.9022    | 0.9215 | 0.9118 | 0.8583   |
| 0.1425        | 13.33 | 1000 | 0.6088          | 0.9024    | 0.9190 | 0.9107 | 0.8544   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1