---
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: 0.2280
- Validation Loss: 0.6532
- Train Overall Precision: 0.7218
- Train Overall Recall: 0.7878
- Train Overall F1: 0.7534
- Train Overall Accuracy: 0.8144
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6940     | 1.4151          | 0.2686                  | 0.2785               | 0.2735           | 0.5128                 | 0     |
| 1.1731     | 0.8665          | 0.5771                  | 0.6101               | 0.5932           | 0.7267                 | 1     |
| 0.7612     | 0.6849          | 0.6362                  | 0.7336               | 0.6814           | 0.7784                 | 2     |
| 0.5630     | 0.6265          | 0.6748                  | 0.7592               | 0.7145           | 0.8017                 | 3     |
| 0.4441     | 0.6256          | 0.6935                  | 0.7767               | 0.7328           | 0.8036                 | 4     |
| 0.3641     | 0.6402          | 0.7115                  | 0.7772               | 0.7429           | 0.7940                 | 5     |
| 0.2781     | 0.6248          | 0.7176                  | 0.7868               | 0.7506           | 0.8141                 | 6     |
| 0.2280     | 0.6532          | 0.7218                  | 0.7878               | 0.7534           | 0.8144                 | 7     |


### Framework versions

- Transformers 4.22.2
- TensorFlow 2.10.0
- Datasets 2.5.2
- Tokenizers 0.12.1