---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- funsd-layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: funsd-layoutlmv3
      type: funsd-layoutlmv3
      config: funsd
      split: test
      args: funsd
    metrics:
    - name: Precision
      type: precision
      value: 0.9002457002457003
    - name: Recall
      type: recall
      value: 0.9100844510680576
    - name: F1
      type: f1
      value: 0.9051383399209486
    - name: Accuracy
      type: accuracy
      value: 0.8547486033519553
---

<!-- 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. -->

# test

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6194
- Precision: 0.9002
- Recall: 0.9101
- F1: 0.9051
- Accuracy: 0.8547

## 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  | 0.6953          | 0.7761    | 0.8058 | 0.7906 | 0.7680   |
| No log        | 2.67  | 200  | 0.5117          | 0.8250    | 0.8808 | 0.8520 | 0.8290   |
| No log        | 4.0   | 300  | 0.5177          | 0.8397    | 0.8897 | 0.8640 | 0.8337   |
| No log        | 5.33  | 400  | 0.5165          | 0.8642    | 0.9106 | 0.8868 | 0.8509   |
| 0.5653        | 6.67  | 500  | 0.5378          | 0.8735    | 0.9091 | 0.8909 | 0.8458   |
| 0.5653        | 8.0   | 600  | 0.5698          | 0.8733    | 0.9111 | 0.8918 | 0.8482   |
| 0.5653        | 9.33  | 700  | 0.5773          | 0.8934    | 0.9076 | 0.9004 | 0.8557   |
| 0.5653        | 10.67 | 800  | 0.6073          | 0.8905    | 0.9006 | 0.8955 | 0.8520   |
| 0.5653        | 12.0  | 900  | 0.6090          | 0.8940    | 0.9091 | 0.9015 | 0.8513   |
| 0.1357        | 13.33 | 1000 | 0.6194          | 0.9002    | 0.9101 | 0.9051 | 0.8547   |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3