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---
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: 0.6164
- Validation Loss: 1.0914
- Train Overall Precision: 0.4921
- Train Overall Recall: 0.5178
- Train Overall F1: 0.5046
- Train Overall Accuracy: 0.6136
- 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': 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: float32
### Training results
| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6889 | 1.4840 | 0.1755 | 0.3307 | 0.2293 | 0.3586 | 0 |
| 1.3467 | 1.2410 | 0.3182 | 0.4827 | 0.3836 | 0.4680 | 1 |
| 1.1412 | 1.1634 | 0.3303 | 0.5028 | 0.3986 | 0.5209 | 2 |
| 1.0429 | 1.1068 | 0.3727 | 0.5289 | 0.4373 | 0.5592 | 3 |
| 0.8937 | 1.0652 | 0.4460 | 0.5569 | 0.4953 | 0.6060 | 4 |
| 0.7579 | 1.0765 | 0.4660 | 0.5640 | 0.5103 | 0.5983 | 5 |
| 0.7126 | 1.1322 | 0.4677 | 0.5845 | 0.5196 | 0.6209 | 6 |
| 0.6164 | 1.0914 | 0.4921 | 0.5178 | 0.5046 | 0.6136 | 7 |
### Framework versions
- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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