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---
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: 0.2552
- Validation Loss: 0.6563
- Train Overall Precision: 0.7174
- Train Overall Recall: 0.7988
- Train Overall F1: 0.7559
- Train Overall Accuracy: 0.8073
- 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: mixed_float16
### Training results
| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7065 | 1.3937 | 0.2463 | 0.2418 | 0.2441 | 0.5476 | 0 |
| 1.1571 | 0.8921 | 0.6122 | 0.6352 | 0.6235 | 0.7318 | 1 |
| 0.7498 | 0.6885 | 0.6740 | 0.7376 | 0.7044 | 0.7816 | 2 |
| 0.5523 | 0.6299 | 0.6752 | 0.7852 | 0.7260 | 0.8011 | 3 |
| 0.4503 | 0.6387 | 0.6913 | 0.7943 | 0.7392 | 0.8010 | 4 |
| 0.3554 | 0.6279 | 0.7121 | 0.7792 | 0.7441 | 0.8110 | 5 |
| 0.3005 | 0.6507 | 0.7201 | 0.7782 | 0.7480 | 0.8085 | 6 |
| 0.2552 | 0.6563 | 0.7174 | 0.7988 | 0.7559 | 0.8073 | 7 |
### Framework versions
- Transformers 4.34.0
- TensorFlow 2.12.0
- Datasets 2.14.5
- Tokenizers 0.14.0
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