---
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_100
  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_100

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an FUNSD dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5728
- Precision: 0.8172
- Recall: 0.8664
- F1: 0.8411
- Accuracy: 0.8318

## 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: 250

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.83  | 25   | 1.3530          | 0.2996    | 0.3040 | 0.3018 | 0.5402   |
| No log        | 1.67  | 50   | 0.9373          | 0.6537    | 0.7193 | 0.6850 | 0.7412   |
| No log        | 2.5   | 75   | 0.7492          | 0.7574    | 0.8018 | 0.7790 | 0.7748   |
| No log        | 3.33  | 100  | 0.6587          | 0.7721    | 0.8097 | 0.7905 | 0.7900   |
| No log        | 4.17  | 125  | 0.6224          | 0.7808    | 0.8336 | 0.8063 | 0.8005   |
| No log        | 5.0   | 150  | 0.5720          | 0.7870    | 0.8445 | 0.8148 | 0.8171   |
| No log        | 5.83  | 175  | 0.5343          | 0.8164    | 0.8549 | 0.8352 | 0.8250   |
| No log        | 6.67  | 200  | 0.5856          | 0.8139    | 0.8604 | 0.8365 | 0.8268   |
| No log        | 7.5   | 225  | 0.5787          | 0.8166    | 0.8624 | 0.8388 | 0.8266   |
| No log        | 8.33  | 250  | 0.5728          | 0.8172    | 0.8664 | 0.8411 | 0.8318   |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2