---
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: 0.8925979680696662
    - name: Recall
      type: recall
      value: 0.9165424739195231
    - name: F1
      type: f1
      value: 0.9044117647058824
    - 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: 0.6509
- Precision: 0.8926
- Recall: 0.9165
- F1: 0.9044
- 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  | 0.7445          | 0.7475    | 0.7869 | 0.7667 | 0.7630   |
| No log        | 2.67  | 200  | 0.5447          | 0.8075    | 0.8793 | 0.8419 | 0.8194   |
| No log        | 4.0   | 300  | 0.5183          | 0.8425    | 0.8957 | 0.8683 | 0.8418   |
| No log        | 5.33  | 400  | 0.5603          | 0.8281    | 0.8952 | 0.8603 | 0.8307   |
| 0.5735        | 6.67  | 500  | 0.5571          | 0.8535    | 0.9001 | 0.8762 | 0.8376   |
| 0.5735        | 8.0   | 600  | 0.5647          | 0.8824    | 0.9096 | 0.8958 | 0.8536   |
| 0.5735        | 9.33  | 700  | 0.5896          | 0.8802    | 0.9121 | 0.8958 | 0.8547   |
| 0.5735        | 10.67 | 800  | 0.6298          | 0.8935    | 0.9165 | 0.9049 | 0.8587   |
| 0.5735        | 12.0  | 900  | 0.6280          | 0.8965    | 0.9210 | 0.9086 | 0.8615   |
| 0.1395        | 13.33 | 1000 | 0.6509          | 0.8926    | 0.9165 | 0.9044 | 0.8601   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3