---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: impira/layoutlm-invoices
tags:
- generated_from_trainer
model-index:
- name: layoutlm-finetuned
  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-finetuned

This model is a fine-tuned version of [impira/layoutlm-invoices](https://huggingface.co/impira/layoutlm-invoices) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0064

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0837        | 0.2116 | 100  | 0.0147          |
| 0.0603        | 0.4233 | 200  | 0.0101          |
| 0.0396        | 0.6349 | 300  | 0.0093          |
| 0.0442        | 0.8466 | 400  | 0.0086          |
| 0.0287        | 1.0571 | 500  | 0.0073          |
| 0.0396        | 1.2688 | 600  | 0.0084          |
| 0.0179        | 1.4804 | 700  | 0.0080          |
| 0.0391        | 1.6921 | 800  | 0.0069          |
| 0.0261        | 1.9037 | 900  | 0.0064          |
| 0.0146        | 2.1143 | 1000 | 0.0068          |
| 0.0192        | 2.3259 | 1100 | 0.0089          |
| 0.0233        | 2.5376 | 1200 | 0.0070          |
| 0.0129        | 2.7492 | 1300 | 0.0072          |
| 0.0173        | 2.9608 | 1400 | 0.0068          |
| 0.0217        | 3.1714 | 1500 | 0.0076          |
| 0.0198        | 3.3831 | 1600 | 0.0066          |
| 0.0163        | 3.5947 | 1700 | 0.0068          |
| 0.0142        | 3.8063 | 1800 | 0.0078          |
| 0.0144        | 4.0169 | 1900 | 0.0065          |
| 0.0143        | 4.2286 | 2000 | 0.0065          |
| 0.0125        | 4.4402 | 2100 | 0.0071          |
| 0.0108        | 4.6519 | 2200 | 0.0077          |
| 0.0138        | 4.8635 | 2300 | 0.0071          |
| 0.0146        | 5.0741 | 2400 | 0.0076          |
| 0.0135        | 5.2857 | 2500 | 0.0084          |
| 0.0213        | 5.4974 | 2600 | 0.0081          |
| 0.0117        | 5.7090 | 2700 | 0.0083          |
| 0.0181        | 5.9206 | 2800 | 0.0092          |
| 0.0124        | 6.1312 | 2900 | 0.0090          |
| 0.0102        | 6.3429 | 3000 | 0.0090          |
| 0.0110        | 6.5545 | 3100 | 0.0081          |
| 0.0100        | 6.7661 | 3200 | 0.0089          |
| 0.0111        | 6.9778 | 3300 | 0.0106          |
| 0.0127        | 7.1884 | 3400 | 0.0107          |
| 0.0075        | 7.4    | 3500 | 0.0106          |
| 0.0155        | 7.6116 | 3600 | 0.0104          |
| 0.0114        | 7.8233 | 3700 | 0.0104          |
| 0.0084        | 8.0339 | 3800 | 0.0100          |
| 0.0075        | 8.2455 | 3900 | 0.0112          |
| 0.0095        | 8.4571 | 4000 | 0.0115          |
| 0.0117        | 8.6688 | 4100 | 0.0115          |
| 0.0083        | 8.8804 | 4200 | 0.0118          |
| 0.0060        | 9.0910 | 4300 | 0.0118          |
| 0.0049        | 9.3026 | 4400 | 0.0130          |
| 0.0082        | 9.5143 | 4500 | 0.0129          |
| 0.0083        | 9.7259 | 4600 | 0.0131          |
| 0.0076        | 9.9376 | 4700 | 0.0130          |
| 0.0062        | 10.0   | 4730 | 0.0130          |


### Framework versions

- Transformers 5.11.0
- Pytorch 2.6.0+cu124
- Datasets 5.0.0
- Tokenizers 0.22.2