---
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: layoutlm-funsd-tf
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# layoutlm-funsd-tf

This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2579
- Validation Loss: 0.6970
- Train Overall Precision: 0.7286
- Train Overall Recall: 0.8003
- Train Overall F1: 0.7628
- Train Overall Accuracy: 0.8045
- Epoch: 7

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7062     | 1.4015          | 0.2826                  | 0.3011               | 0.2915           | 0.5146                 | 0     |
| 1.1524     | 0.8928          | 0.5942                  | 0.6598               | 0.6253           | 0.7216                 | 1     |
| 0.8106     | 0.7383          | 0.6540                  | 0.7190               | 0.6850           | 0.7634                 | 2     |
| 0.5949     | 0.7057          | 0.6936                  | 0.7441               | 0.7180           | 0.7715                 | 3     |
| 0.4676     | 0.6148          | 0.7246                  | 0.7842               | 0.7533           | 0.8096                 | 4     |
| 0.3782     | 0.6263          | 0.7230                  | 0.8028               | 0.7608           | 0.8140                 | 5     |
| 0.3083     | 0.6780          | 0.7175                  | 0.7978               | 0.7555           | 0.8010                 | 6     |
| 0.2579     | 0.6970          | 0.7286                  | 0.8003               | 0.7628           | 0.8045                 | 7     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1