---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- generated
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: generated
      type: generated
      config: sroie
      split: test
      args: sroie
    metrics:
    - name: Precision
      type: precision
      value: 0.9698795180722891
    - name: Recall
      type: recall
      value: 0.9797160243407708
    - name: F1
      type: f1
      value: 0.9747729566094854
    - name: Accuracy
      type: accuracy
      value: 0.9964187908152518
---

<!-- 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. -->

# layoutlmv3-finetuned-invoice

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0826
- Precision: 0.9699
- Recall: 0.9797
- F1: 0.9748
- Accuracy: 0.9964

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 100  | 0.1528          | 0.9478    | 0.9574 | 0.9526 | 0.9941   |
| No log        | 2.0   | 200  | 0.0826          | 0.9699    | 0.9797 | 0.9748 | 0.9964   |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1