---
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: 0.8892100192678227
    - name: Recall
      type: recall
      value: 0.9170392449080974
    - name: F1
      type: f1
      value: 0.9029102470041576
    - name: Accuracy
      type: accuracy
      value: 0.8690122429573279
---

<!-- 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: 0.5352
- Precision: 0.8892
- Recall: 0.9170
- F1: 0.9029
- Accuracy: 0.8690

## 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  | 0.7740          | 0.7470    | 0.8127 | 0.7785 | 0.7037   |
| No log        | 2.67  | 200  | 0.5483          | 0.8111    | 0.8937 | 0.8504 | 0.7910   |
| No log        | 4.0   | 300  | 0.4411          | 0.8400    | 0.8813 | 0.8601 | 0.8492   |
| No log        | 5.33  | 400  | 0.4512          | 0.8432    | 0.8952 | 0.8684 | 0.8499   |
| 0.5705        | 6.67  | 500  | 0.4541          | 0.8865    | 0.9195 | 0.9027 | 0.8652   |
| 0.5705        | 8.0   | 600  | 0.4939          | 0.8782    | 0.9165 | 0.8969 | 0.8625   |
| 0.5705        | 9.33  | 700  | 0.5152          | 0.8792    | 0.9151 | 0.8968 | 0.8572   |
| 0.5705        | 10.67 | 800  | 0.5299          | 0.8856    | 0.9116 | 0.8984 | 0.8663   |
| 0.5705        | 12.0  | 900  | 0.5162          | 0.8894    | 0.9185 | 0.9037 | 0.8697   |
| 0.1324        | 13.33 | 1000 | 0.5352          | 0.8892    | 0.9170 | 0.9029 | 0.8690   |


### Framework versions

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