---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv2_output
  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. -->

# layoutlmv2_output

This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3471
- Precision: 0.8712
- Recall: 0.8742
- F1: 0.8727
- Accuracy: 0.9288

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3415        | 0.8772 | 500  | 0.4834          | 0.8227    | 0.8343 | 0.8285 | 0.8966   |
| 0.228         | 1.7544 | 1000 | 0.3607          | 0.8591    | 0.8528 | 0.8559 | 0.9170   |
| 0.1769        | 2.6316 | 1500 | 0.3408          | 0.8571    | 0.8556 | 0.8563 | 0.9208   |
| 0.1183        | 3.5088 | 2000 | 0.3570          | 0.8661    | 0.8579 | 0.8620 | 0.9208   |
| 0.0915        | 4.3860 | 2500 | 0.3603          | 0.8644    | 0.8702 | 0.8673 | 0.9256   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1