---
license: cc-by-nc-sa-4.0
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8330
- Precision: 0.9046
- Recall: 0.9105
- F1: 0.9076
- Accuracy: 0.8536

## 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: 4
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.32  | 50   | 0.6163          | 0.8088    | 0.8965 | 0.8504 | 0.8088   |
| No log        | 2.63  | 100  | 0.5416          | 0.8037    | 0.868  | 0.8346 | 0.8134   |
| No log        | 3.95  | 150  | 0.5572          | 0.8446    | 0.8885 | 0.8660 | 0.8385   |
| No log        | 5.26  | 200  | 0.7317          | 0.8458    | 0.8555 | 0.8506 | 0.8124   |
| No log        | 6.58  | 250  | 0.7220          | 0.8877    | 0.8935 | 0.8906 | 0.8385   |
| No log        | 7.89  | 300  | 0.8070          | 0.8778    | 0.9055 | 0.8915 | 0.8436   |
| No log        | 9.21  | 350  | 0.7895          | 0.8969    | 0.913  | 0.9049 | 0.8477   |
| No log        | 10.53 | 400  | 0.8168          | 0.8935    | 0.889  | 0.8912 | 0.8412   |
| No log        | 11.84 | 450  | 0.8233          | 0.8955    | 0.917  | 0.9061 | 0.8521   |
| 0.2564        | 13.16 | 500  | 0.8330          | 0.9046    | 0.9105 | 0.9076 | 0.8536   |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 2.13.2
- Tokenizers 0.10.1