---
license: mit
tags:
- generated_from_keras_callback
base_model: cor-c/layoutlm-funsd-tf
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 [cor-c/layoutlm-funsd-tf](https://huggingface.co/cor-c/layoutlm-funsd-tf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0632
- Validation Loss: 0.8795
- Train Overall Precision: 0.7424
- Train Overall Recall: 0.8038
- Train Overall F1: 0.7719
- Train Overall Accuracy: 0.8103
- 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 2.9999999242136255e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 0.2119     | 0.7340          | 0.7292                  | 0.8053               | 0.7654           | 0.8046                 | 0     |
| 0.1948     | 0.7521          | 0.7406                  | 0.7963               | 0.7674           | 0.8027                 | 1     |
| 0.1485     | 0.7879          | 0.7256                  | 0.7988               | 0.7604           | 0.8019                 | 2     |
| 0.1220     | 0.7861          | 0.7403                  | 0.7983               | 0.7682           | 0.8073                 | 3     |
| 0.1003     | 0.8253          | 0.7495                  | 0.8018               | 0.7748           | 0.8087                 | 4     |
| 0.0825     | 0.8617          | 0.7491                  | 0.7968               | 0.7722           | 0.8048                 | 5     |
| 0.0676     | 0.8938          | 0.7503                  | 0.8128               | 0.7803           | 0.8062                 | 6     |
| 0.0632     | 0.8795          | 0.7424                  | 0.8038               | 0.7719           | 0.8103                 | 7     |


### Framework versions

- Transformers 4.41.0.dev0
- TensorFlow 2.16.1
- Datasets 2.19.1
- Tokenizers 0.19.1