---
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: 0.9979716024340771
    - name: Recall
      type: recall
      value: 0.9979716024340771
    - name: F1
      type: f1
      value: 0.9979716024340771
    - name: Accuracy
      type: accuracy
      value: 0.9997893406361913
---

<!-- 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: 0.0040
- Precision: 0.9980
- Recall: 0.9980
- F1: 0.9980
- Accuracy: 0.9998

## 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: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 100  | 0.1249          | 0.796     | 0.8073 | 0.8016 | 0.9785   |
| No log        | 2.0   | 200  | 0.0338          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| No log        | 3.0   | 300  | 0.0194          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| No log        | 4.0   | 400  | 0.0153          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1446        | 5.0   | 500  | 0.0126          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
| 0.1446        | 6.0   | 600  | 0.0102          | 0.9739    | 0.9858 | 0.9798 | 0.9973   |
| 0.1446        | 7.0   | 700  | 0.0065          | 0.9959    | 0.9939 | 0.9949 | 0.9994   |
| 0.1446        | 8.0   | 800  | 0.0045          | 0.9959    | 0.9959 | 0.9959 | 0.9996   |
| 0.1446        | 9.0   | 900  | 0.0052          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
| 0.0103        | 10.0  | 1000 | 0.0040          | 0.9980    | 0.9980 | 0.9980 | 0.9998   |


### Framework versions

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