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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: 0.2479
- Validation Loss: 0.6865
- Train Overall Precision: 0.7469
- Train Overall Recall: 0.8098
- Train Overall F1: 0.7771
- Train Overall Accuracy: 0.8111
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7068 | 1.4323 | 0.2302 | 0.2604 | 0.2444 | 0.5097 | 0 |
| 1.1785 | 0.8879 | 0.5487 | 0.6553 | 0.5973 | 0.7149 | 1 |
| 0.7570 | 0.7017 | 0.6315 | 0.7411 | 0.6819 | 0.7810 | 2 |
| 0.5598 | 0.6353 | 0.6893 | 0.7747 | 0.7295 | 0.7954 | 3 |
| 0.4407 | 0.6282 | 0.7144 | 0.7842 | 0.7477 | 0.8015 | 4 |
| 0.3450 | 0.6653 | 0.7174 | 0.7822 | 0.7484 | 0.8036 | 5 |
| 0.2758 | 0.7178 | 0.7002 | 0.7863 | 0.7407 | 0.7920 | 6 |
| 0.2479 | 0.6865 | 0.7469 | 0.8098 | 0.7771 | 0.8111 | 7 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.13.1
- Datasets 2.20.0
- Tokenizers 0.15.2
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