---
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: 0.8808265257087938
    - name: Recall
      type: recall
      value: 0.910581222056632
    - name: F1
      type: f1
      value: 0.895456765999023
    - name: Accuracy
      type: accuracy
      value: 0.8507072387970998
---

<!-- 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: 0.5799
- Precision: 0.8808
- Recall: 0.9106
- F1: 0.8955
- Accuracy: 0.8507

## 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        | 1.3333  | 100  | 0.6686          | 0.7452    | 0.8251 | 0.7831 | 0.7535   |
| No log        | 2.6667  | 200  | 0.4724          | 0.8064    | 0.8713 | 0.8376 | 0.8389   |
| No log        | 4.0     | 300  | 0.4922          | 0.8612    | 0.8942 | 0.8774 | 0.8481   |
| No log        | 5.3333  | 400  | 0.4632          | 0.8587    | 0.8997 | 0.8787 | 0.8521   |
| 0.544         | 6.6667  | 500  | 0.4850          | 0.8632    | 0.9031 | 0.8827 | 0.8474   |
| 0.544         | 8.0     | 600  | 0.5024          | 0.8744    | 0.8992 | 0.8866 | 0.8451   |
| 0.544         | 9.3333  | 700  | 0.5394          | 0.8768    | 0.9155 | 0.8957 | 0.8565   |
| 0.544         | 10.6667 | 800  | 0.5647          | 0.8800    | 0.9146 | 0.8970 | 0.8550   |
| 0.544         | 12.0    | 900  | 0.5798          | 0.8847    | 0.9106 | 0.8974 | 0.8545   |
| 0.1288        | 13.3333 | 1000 | 0.5799          | 0.8808    | 0.9106 | 0.8955 | 0.8507   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.19.1