---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: layoutlmv3_document_classification
  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_document_classification

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6852
- Accuracy: 0.8480
- F1: 0.8373

## 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: 3e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 4.1758        | 0.5   | 100  | 3.6479          | 0.1754   | 0.0743 |
| 3.1634        | 1.0   | 200  | 2.5074          | 0.4645   | 0.3598 |
| 2.2494        | 1.5   | 300  | 1.9309          | 0.5856   | 0.4950 |
| 1.8063        | 2.0   | 400  | 1.5119          | 0.6817   | 0.6152 |
| 1.458         | 2.5   | 500  | 1.2952          | 0.7126   | 0.6529 |
| 1.2453        | 3.0   | 600  | 1.1118          | 0.7728   | 0.7327 |
| 1.046         | 3.5   | 700  | 1.0126          | 0.7987   | 0.7681 |
| 0.966         | 4.0   | 800  | 0.9096          | 0.8154   | 0.7929 |
| 0.7941        | 4.5   | 900  | 0.8714          | 0.8179   | 0.7972 |
| 0.7796        | 5.0   | 1000 | 0.8019          | 0.8329   | 0.8126 |
| 0.6561        | 5.5   | 1100 | 0.7623          | 0.8421   | 0.8235 |
| 0.6419        | 6.0   | 1200 | 0.7399          | 0.8421   | 0.8262 |
| 0.5715        | 6.5   | 1300 | 0.7127          | 0.8480   | 0.8321 |
| 0.4991        | 7.0   | 1400 | 0.7502          | 0.8396   | 0.8257 |
| 0.4697        | 7.5   | 1500 | 0.7124          | 0.8429   | 0.8305 |
| 0.4618        | 8.0   | 1600 | 0.6976          | 0.8463   | 0.8330 |
| 0.4117        | 8.5   | 1700 | 0.6892          | 0.8546   | 0.8429 |
| 0.4274        | 9.0   | 1800 | 0.6915          | 0.8496   | 0.8390 |
| 0.383         | 9.5   | 1900 | 0.6830          | 0.8471   | 0.8349 |
| 0.3604        | 10.0  | 2000 | 0.6852          | 0.8480   | 0.8373 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0