---
library_name: transformers
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: layoutlm-receipts
  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. -->

# layoutlm-receipts

This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2190
- Precision: 0.2222
- Recall: 0.4
- F1: 0.2857

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.7275        | 1.0   | 8    | 0.8111          | 0.0       | 0.0    | 0.0    |
| 0.6014        | 2.0   | 16   | 0.6757          | 0.0       | 0.0    | 0.0    |
| 0.5061        | 3.0   | 24   | 0.5598          | 0.0       | 0.0    | 0.0    |
| 0.4025        | 4.0   | 32   | 0.4736          | 0.0       | 0.0    | 0.0    |
| 0.3486        | 5.0   | 40   | 0.4236          | 0.0571    | 0.1    | 0.0727 |
| 0.3318        | 6.0   | 48   | 0.3784          | 0.0377    | 0.1    | 0.0548 |
| 0.2649        | 7.0   | 56   | 0.3338          | 0.1064    | 0.25   | 0.1493 |
| 0.1982        | 8.0   | 64   | 0.2808          | 0.25      | 0.4    | 0.3077 |
| 0.1658        | 9.0   | 72   | 0.2388          | 0.1778    | 0.4    | 0.2462 |
| 0.1637        | 10.0  | 80   | 0.2190          | 0.2222    | 0.4    | 0.2857 |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0