---
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_trainer
datasets:
- funsd
model-index:
- name: layoutlm-funsd
  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-funsd

This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9828
- Question: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1}
- Overall Precision: 1.0
- Overall Recall: 1.0
- Overall F1: 1.0
- Overall Accuracy: 1.0

## 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: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Question                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 1.585         | 1.0   | 38   | 1.3020          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | 1.0               | 1.0            | 1.0        | 1.0              |
| 1.1814        | 2.0   | 76   | 1.1133          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | 1.0               | 1.0            | 1.0        | 1.0              |
| 1.0181        | 3.0   | 114  | 1.0476          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | 1.0               | 1.0            | 1.0        | 1.0              |
| 0.9213        | 4.0   | 152  | 1.0004          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | 1.0               | 1.0            | 1.0        | 1.0              |
| 0.8337        | 5.0   | 190  | 0.9828          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | 1.0               | 1.0            | 1.0        | 1.0              |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2