---
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-ap7_10_stitched_16_batch_3e5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# layoutlmv3-ap7_10_stitched_16_batch_3e5

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: 0.0208
- Precision: 0.7353
- Recall: 0.8621
- F1: 0.7937
- Accuracy: 0.9969

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3001        | 50.0  | 250  | 0.0278          | 0.3939    | 0.4483 | 0.4194 | 0.9948   |
| 0.0061        | 100.0 | 500  | 0.0208          | 0.7353    | 0.8621 | 0.7937 | 0.9969   |
| 0.0017        | 150.0 | 750  | 0.0233          | 0.6579    | 0.8621 | 0.7463 | 0.9960   |
| 0.0012        | 200.0 | 1000 | 0.0266          | 0.6571    | 0.7931 | 0.7188 | 0.9958   |


### Framework versions

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