---
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: 0.125
    - name: Recall
      type: recall
      value: 0.012170385395537525
    - name: F1
      type: f1
      value: 0.022181146025878003
    - name: Accuracy
      type: accuracy
      value: 0.8763429534442806
---

<!-- 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: 1.9513
- Precision: 0.125
- Recall: 0.0122
- F1: 0.0222
- Accuracy: 0.8763

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.1   | 5    | 1.9513          | 0.125     | 0.0122 | 0.0222 | 0.8763   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1