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---
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: 0.2595
- Validation Loss: 0.6704
- Train Overall Precision: 0.7379
- Train Overall Recall: 0.8038
- Train Overall F1: 0.7695
- Train Overall Accuracy: 0.8080
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7036 | 1.4227 | 0.2407 | 0.3337 | 0.2796 | 0.5026 | 0 |
| 1.1552 | 0.8765 | 0.5724 | 0.6944 | 0.6275 | 0.7181 | 1 |
| 0.7585 | 0.7119 | 0.6652 | 0.7406 | 0.7009 | 0.7820 | 2 |
| 0.5699 | 0.6705 | 0.6880 | 0.7592 | 0.7219 | 0.7822 | 3 |
| 0.4487 | 0.6814 | 0.7087 | 0.7556 | 0.7314 | 0.7798 | 4 |
| 0.3664 | 0.6761 | 0.7033 | 0.7958 | 0.7467 | 0.8027 | 5 |
| 0.3170 | 0.6953 | 0.7162 | 0.7903 | 0.7514 | 0.7984 | 6 |
| 0.2595 | 0.6704 | 0.7379 | 0.8038 | 0.7695 | 0.8080 | 7 |
### Framework versions
- Transformers 4.32.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
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