---
library_name: transformers
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-sroie
  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-sroie

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: 0.0742
- Precision: 0.9472
- Recall: 0.9668
- F1: 0.9569
- Accuracy: 0.9872

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.9841  | 250  | 0.0544          | 0.9319    | 0.9592 | 0.9453 | 0.9836   |
| 0.0813        | 3.9683  | 500  | 0.0607          | 0.9280    | 0.9683 | 0.9477 | 0.9844   |
| 0.0813        | 5.9524  | 750  | 0.0530          | 0.9451    | 0.9589 | 0.9519 | 0.9854   |
| 0.023         | 7.9365  | 1000 | 0.0562          | 0.9434    | 0.9643 | 0.9537 | 0.9863   |
| 0.023         | 9.9206  | 1250 | 0.0613          | 0.9486    | 0.9614 | 0.9549 | 0.9867   |
| 0.0128        | 11.9048 | 1500 | 0.0632          | 0.9510    | 0.9650 | 0.9579 | 0.9875   |
| 0.0128        | 13.8889 | 1750 | 0.0705          | 0.9403    | 0.9670 | 0.9535 | 0.9862   |
| 0.0073        | 15.8730 | 2000 | 0.0723          | 0.9485    | 0.9643 | 0.9563 | 0.9871   |
| 0.0073        | 17.8571 | 2250 | 0.0728          | 0.9505    | 0.9653 | 0.9579 | 0.9875   |
| 0.0054        | 19.8413 | 2500 | 0.0742          | 0.9472    | 0.9668 | 0.9569 | 0.9872   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1