---
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: 0.4674
- Validation Loss: 0.6405
- Train Overall Precision: 0.7082
- Train Overall Recall: 0.7637
- Train Overall F1: 0.7349
- Train Overall Accuracy: 0.7984
- Epoch: 4

## 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7185     | 1.4324          | 0.2236                  | 0.2805               | 0.2488           | 0.5123                 | 0     |
| 1.1768     | 0.9053          | 0.5468                  | 0.6744               | 0.6039           | 0.7257                 | 1     |
| 0.7782     | 0.6968          | 0.6512                  | 0.7250               | 0.6861           | 0.7760                 | 2     |
| 0.5777     | 0.6506          | 0.6826                  | 0.7682               | 0.7229           | 0.7924                 | 3     |
| 0.4674     | 0.6405          | 0.7082                  | 0.7637               | 0.7349           | 0.7984                 | 4     |


### Framework versions

- Transformers 4.33.3
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3