---
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: 0.8876459143968871
    - name: Recall
      type: recall
      value: 0.9066070541480378
    - name: F1
      type: f1
      value: 0.8970262963873188
    - name: Accuracy
      type: accuracy
      value: 0.86009746820397
---

<!-- 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: 0.6568
- Precision: 0.8876
- Recall: 0.9066
- F1: 0.8970
- Accuracy: 0.8601

## 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  | 0.6157          | 0.7621    | 0.8400 | 0.7991 | 0.8051   |
| No log        | 2.67  | 200  | 0.4834          | 0.7915    | 0.8902 | 0.8380 | 0.8334   |
| No log        | 4.0   | 300  | 0.4929          | 0.8484    | 0.8922 | 0.8697 | 0.8493   |
| No log        | 5.33  | 400  | 0.5191          | 0.8746    | 0.9006 | 0.8874 | 0.8556   |
| 0.5561        | 6.67  | 500  | 0.5553          | 0.8671    | 0.9041 | 0.8852 | 0.8487   |
| 0.5561        | 8.0   | 600  | 0.5766          | 0.8723    | 0.9091 | 0.8903 | 0.8388   |
| 0.5561        | 9.33  | 700  | 0.6486          | 0.8816    | 0.8917 | 0.8866 | 0.8511   |
| 0.5561        | 10.67 | 800  | 0.6188          | 0.8861    | 0.9086 | 0.8972 | 0.8608   |
| 0.5561        | 12.0  | 900  | 0.6317          | 0.8890    | 0.9071 | 0.8980 | 0.8630   |
| 0.1298        | 13.33 | 1000 | 0.6568          | 0.8876    | 0.9066 | 0.8970 | 0.8601   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3