---
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-v6
  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-v6

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: 0.1889
- Precision: 0.9549
- Recall: 0.9322
- F1: 0.9434
- Accuracy: 0.9767

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.3158  | 100  | 0.0637          | 0.9864    | 0.9864 | 0.9864 | 0.9831   |
| No log        | 2.6316  | 200  | 0.1441          | 0.9613    | 0.9254 | 0.9430 | 0.9640   |
| No log        | 3.9474  | 300  | 0.0723          | 0.9685    | 0.9390 | 0.9535 | 0.9682   |
| No log        | 5.2632  | 400  | 0.1235          | 0.9414    | 0.9254 | 0.9333 | 0.9682   |
| 0.031         | 6.5789  | 500  | 0.1814          | 0.9685    | 0.9390 | 0.9535 | 0.9809   |
| 0.031         | 7.8947  | 600  | 0.1842          | 0.9549    | 0.9322 | 0.9434 | 0.9767   |
| 0.031         | 9.2105  | 700  | 0.1873          | 0.9549    | 0.9322 | 0.9434 | 0.9767   |
| 0.031         | 10.5263 | 800  | 0.1938          | 0.9549    | 0.9322 | 0.9434 | 0.9725   |
| 0.031         | 11.8421 | 900  | 0.1938          | 0.9549    | 0.9322 | 0.9434 | 0.9746   |
| 0.0003        | 13.1579 | 1000 | 0.1889          | 0.9549    | 0.9322 | 0.9434 | 0.9767   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0