---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice
  results: []
---

<!-- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2568
- Precision: 0.7955
- Recall: 0.6931
- F1: 0.7407
- Accuracy: 0.9524

## 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: 2000

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:--------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 9.0909   | 100  | 0.8724          | 0.0270    | 0.0099 | 0.0145 | 0.7931   |
| No log        | 18.1818  | 200  | 0.3880          | 0.4299    | 0.4554 | 0.4423 | 0.9126   |
| No log        | 27.2727  | 300  | 0.2870          | 0.6       | 0.4158 | 0.4912 | 0.9229   |
| No log        | 36.3636  | 400  | 0.3227          | 0.6389    | 0.4554 | 0.5318 | 0.9242   |
| 0.6024        | 45.4545  | 500  | 0.3251          | 0.6092    | 0.5248 | 0.5638 | 0.9280   |
| 0.6024        | 54.5455  | 600  | 0.2188          | 0.6842    | 0.6436 | 0.6633 | 0.9422   |
| 0.6024        | 63.6364  | 700  | 0.2146          | 0.7159    | 0.6238 | 0.6667 | 0.9447   |
| 0.6024        | 72.7273  | 800  | 0.2138          | 0.8202    | 0.7228 | 0.7684 | 0.9563   |
| 0.6024        | 81.8182  | 900  | 0.2128          | 0.7927    | 0.6436 | 0.7104 | 0.9499   |
| 0.0428        | 90.9091  | 1000 | 0.2400          | 0.7753    | 0.6832 | 0.7263 | 0.9512   |
| 0.0428        | 100.0    | 1100 | 0.2498          | 0.7821    | 0.6040 | 0.6816 | 0.9434   |
| 0.0428        | 109.0909 | 1200 | 0.2614          | 0.7805    | 0.6337 | 0.6995 | 0.9447   |
| 0.0428        | 118.1818 | 1300 | 0.2742          | 0.7821    | 0.6040 | 0.6816 | 0.9447   |
| 0.0428        | 127.2727 | 1400 | 0.2744          | 0.7471    | 0.6436 | 0.6915 | 0.9473   |
| 0.0091        | 136.3636 | 1500 | 0.2568          | 0.7955    | 0.6931 | 0.7407 | 0.9524   |
| 0.0091        | 145.4545 | 1600 | 0.2711          | 0.7701    | 0.6634 | 0.7128 | 0.9486   |
| 0.0091        | 154.5455 | 1700 | 0.3043          | 0.7778    | 0.6238 | 0.6923 | 0.9434   |
| 0.0091        | 163.6364 | 1800 | 0.2746          | 0.7683    | 0.6238 | 0.6885 | 0.9434   |
| 0.0091        | 172.7273 | 1900 | 0.2646          | 0.7955    | 0.6931 | 0.7407 | 0.9524   |
| 0.0056        | 181.8182 | 2000 | 0.2681          | 0.7955    | 0.6931 | 0.7407 | 0.9524   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.2+cpu
- Datasets 2.19.0
- Tokenizers 0.19.1