---
tags:
- generated_from_keras_callback
model-index:
- name: jinhybr/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. -->

# jinhybr/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: 0.2987
- Validation Loss: 0.6835
- Train Overall Precision: 0.7270
- Train Overall Recall: 0.7777
- Train Overall F1: 0.7515
- Train Overall Accuracy: 0.8056
- Epoch: 6

## 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6886     | 1.4100          | 0.2324                  | 0.2313               | 0.2318           | 0.5009                 | 0     |
| 1.1702     | 0.8486          | 0.5971                  | 0.6618               | 0.6278           | 0.7338                 | 1     |
| 0.7521     | 0.7032          | 0.6561                  | 0.7341               | 0.6929           | 0.7687                 | 2     |
| 0.5727     | 0.6268          | 0.6736                  | 0.7662               | 0.7169           | 0.7957                 | 3     |
| 0.4586     | 0.6322          | 0.6909                  | 0.7772               | 0.7315           | 0.7999                 | 4     |
| 0.3725     | 0.6378          | 0.7134                  | 0.7782               | 0.7444           | 0.8096                 | 5     |
| 0.2987     | 0.6835          | 0.7270                  | 0.7777               | 0.7515           | 0.8056                 | 6     |


### Framework versions

- Transformers 4.23.1
- TensorFlow 2.6.0
- Datasets 2.6.1
- Tokenizers 0.13.1