---
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-invoice-parser
  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-invoice-parser

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: 0.5061
- Precision: 0.8242
- Recall: 0.8936
- F1: 0.8575
- Accuracy: 0.8323

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.6703        | 1.0   | 38   | 0.7898          | 0.7234    | 0.8246 | 0.7707 | 0.7616   |
| 0.7077        | 2.0   | 76   | 0.6175          | 0.7751    | 0.8525 | 0.8120 | 0.7997   |
| 0.4946        | 3.0   | 114  | 0.5219          | 0.7856    | 0.8784 | 0.8294 | 0.8223   |
| 0.3819        | 4.0   | 152  | 0.5089          | 0.8109    | 0.8824 | 0.8451 | 0.8293   |
| 0.3178        | 5.0   | 190  | 0.5061          | 0.8242    | 0.8936 | 0.8575 | 0.8323   |


### Framework versions

- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2