---
license: mit
tags:
- generated_from_keras_callback
base_model: microsoft/layoutlm-base-uncased
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: 0.2406
- Validation Loss: 0.7155
- Train Overall Precision: 0.7459
- Train Overall Recall: 0.7893
- Train Overall F1: 0.7669
- Train Overall Accuracy: 0.8064
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7115     | 1.4279          | 0.2575                  | 0.2965               | 0.2757           | 0.4884                 | 0     |
| 1.1520     | 0.8490          | 0.5994                  | 0.6854               | 0.6395           | 0.7372                 | 1     |
| 0.7816     | 0.7069          | 0.6391                  | 0.7471               | 0.6889           | 0.7808                 | 2     |
| 0.5815     | 0.6601          | 0.7089                  | 0.7672               | 0.7369           | 0.7992                 | 3     |
| 0.4460     | 0.6306          | 0.7093                  | 0.7787               | 0.7424           | 0.8060                 | 4     |
| 0.3658     | 0.6575          | 0.7372                  | 0.7812               | 0.7586           | 0.8111                 | 5     |
| 0.2926     | 0.6658          | 0.7240                  | 0.7832               | 0.7525           | 0.8096                 | 6     |
| 0.2406     | 0.7155          | 0.7459                  | 0.7893               | 0.7669           | 0.8064                 | 7     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.16.1
- Datasets 2.19.2
- Tokenizers 0.19.1