---
library_name: transformers
license: mit
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: 0.2409
- Validation Loss: 0.6905
- Train Overall Precision: 0.7213
- Train Overall Recall: 0.7858
- Train Overall F1: 0.7522
- Train Overall Accuracy: 0.7998
- 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': np.float32(3e-05), 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6885     | 1.3544          | 0.2506                  | 0.2534               | 0.2520           | 0.5600                 | 0     |
| 1.1672     | 0.8949          | 0.5489                  | 0.5996               | 0.5731           | 0.7115                 | 1     |
| 0.7766     | 0.7345          | 0.6327                  | 0.7476               | 0.6854           | 0.7633                 | 2     |
| 0.5690     | 0.6435          | 0.6684                  | 0.7727               | 0.7168           | 0.7936                 | 3     |
| 0.4387     | 0.6493          | 0.7180                  | 0.7792               | 0.7474           | 0.7962                 | 4     |
| 0.3470     | 0.6380          | 0.7147                  | 0.7893               | 0.7501           | 0.8020                 | 5     |
| 0.2901     | 0.6569          | 0.7317                  | 0.7868               | 0.7582           | 0.8059                 | 6     |
| 0.2409     | 0.6905          | 0.7213                  | 0.7858               | 0.7522           | 0.7998                 | 7     |


### Framework versions

- Transformers 4.46.0
- TensorFlow 2.18.0
- Datasets 3.0.2
- Tokenizers 0.20.1