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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: 0.5754
- Validation Loss: 1.0073
- Train Overall Precision: 0.4858
- Train Overall Recall: 0.5735
- Train Overall F1: 0.5260
- Train Overall Accuracy: 0.6411
- 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': {'class_name': 'AdamWeightDecay', 'config': {'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}}, '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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6595 | 1.4718 | 0.1431 | 0.2780 | 0.1889 | 0.4016 | 0 |
| 1.3342 | 1.2762 | 0.2962 | 0.4942 | 0.3704 | 0.4644 | 1 |
| 1.1464 | 1.1828 | 0.3753 | 0.5173 | 0.4350 | 0.5034 | 2 |
| 1.0198 | 1.0195 | 0.4070 | 0.5359 | 0.4626 | 0.6167 | 3 |
| 0.8729 | 1.0543 | 0.4343 | 0.5740 | 0.4945 | 0.6018 | 4 |
| 0.7979 | 1.2603 | 0.4648 | 0.5866 | 0.5186 | 0.5615 | 5 |
| 0.6799 | 1.0257 | 0.5180 | 0.5775 | 0.5461 | 0.6408 | 6 |
| 0.5754 | 1.0073 | 0.4858 | 0.5735 | 0.5260 | 0.6411 | 7 |
### Framework versions
- Transformers 4.33.3
- TensorFlow 2.10.0
- Datasets 2.16.1
- Tokenizers 0.13.2
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