---
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: 0.8889970788704966
    - name: Recall
      type: recall
      value: 0.907103825136612
    - name: F1
      type: f1
      value: 0.8979591836734693
    - name: Accuracy
      type: accuracy
      value: 0.8665161060263877
---

<!-- 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: 0.5474
- Precision: 0.8890
- Recall: 0.9071
- F1: 0.8980
- Accuracy: 0.8665

## 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  | 0.5976          | 0.7412    | 0.8296 | 0.7829 | 0.8001   |
| No log        | 2.67  | 200  | 0.5019          | 0.8259    | 0.8698 | 0.8473 | 0.8269   |
| No log        | 4.0   | 300  | 0.4829          | 0.8701    | 0.8982 | 0.8839 | 0.8540   |
| No log        | 5.33  | 400  | 0.4490          | 0.8829    | 0.9141 | 0.8982 | 0.8725   |
| 0.5303        | 6.67  | 500  | 0.5120          | 0.8721    | 0.9046 | 0.8881 | 0.8574   |
| 0.5303        | 8.0   | 600  | 0.5212          | 0.8802    | 0.9011 | 0.8905 | 0.8644   |
| 0.5303        | 9.33  | 700  | 0.5447          | 0.8918    | 0.9086 | 0.9001 | 0.8559   |
| 0.5303        | 10.67 | 800  | 0.5304          | 0.8875    | 0.9056 | 0.8965 | 0.8713   |
| 0.5303        | 12.0  | 900  | 0.5496          | 0.8878    | 0.9081 | 0.8978 | 0.8630   |
| 0.1291        | 13.33 | 1000 | 0.5474          | 0.8890    | 0.9071 | 0.8980 | 0.8665   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2