---
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-ap8_2_stitched_8_batch_4e5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# layoutlmv3-ap8_2_stitched_8_batch_4e5

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: 0.1770
- Precision: 1.0
- Recall: 0.0291
- F1: 0.0566
- Accuracy: 0.9795

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 0.1
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4099        | 16.6667 | 250  | 0.1770          | 1.0       | 0.0291 | 0.0566 | 0.9795   |
| 0.0277        | 33.3333 | 500  | 0.2041          | 0.1739    | 0.0388 | 0.0635 | 0.9787   |
| 0.0059        | 50.0    | 750  | 0.2190          | 0.3       | 0.0874 | 0.1353 | 0.9782   |
| 0.0033        | 66.6667 | 1000 | 0.2216          | 0.1923    | 0.0485 | 0.0775 | 0.9783   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1