---
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: 0.2991
- Precision: 0.7279
- Recall: 0.7091
- F1: 0.7183
- Accuracy: 0.9111

## 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   | 0.5192          | 0.5148    | 0.4871 | 0.5006 | 0.8322   |
| No log        | 1.8182  | 20   | 0.3608          | 0.6485    | 0.6164 | 0.6320 | 0.8912   |
| No log        | 2.7273  | 30   | 0.2978          | 0.6762    | 0.6616 | 0.6688 | 0.9027   |
| No log        | 3.6364  | 40   | 0.2697          | 0.6768    | 0.6724 | 0.6746 | 0.8996   |
| No log        | 4.5455  | 50   | 0.2737          | 0.6726    | 0.6509 | 0.6616 | 0.8989   |
| No log        | 5.4545  | 60   | 0.2784          | 0.6667    | 0.6724 | 0.6695 | 0.8973   |
| No log        | 6.3636  | 70   | 0.2536          | 0.7054    | 0.6810 | 0.6930 | 0.9096   |
| No log        | 7.2727  | 80   | 0.2803          | 0.7100    | 0.7069 | 0.7084 | 0.9103   |
| No log        | 8.1818  | 90   | 0.2924          | 0.7165    | 0.7026 | 0.7095 | 0.9057   |
| No log        | 9.0909  | 100  | 0.2993          | 0.6801    | 0.6918 | 0.6859 | 0.9004   |
| No log        | 10.0    | 110  | 0.3056          | 0.7013    | 0.6983 | 0.6998 | 0.9057   |
| No log        | 10.9091 | 120  | 0.2991          | 0.7279    | 0.7091 | 0.7183 | 0.9111   |


### Framework versions

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