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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: 0.2438
- Validation Loss: 0.6811
- Train Overall Precision: 0.7239
- Train Overall Recall: 0.7933
- Train Overall F1: 0.7570
- Train Overall Accuracy: 0.8147
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6796 | 1.3763 | 0.2522 | 0.3171 | 0.2810 | 0.5028 | 0 |
| 1.1052 | 0.8212 | 0.6124 | 0.6849 | 0.6466 | 0.7375 | 1 |
| 0.7212 | 0.7138 | 0.6471 | 0.7461 | 0.6931 | 0.7665 | 2 |
| 0.5566 | 0.6209 | 0.7053 | 0.7792 | 0.7404 | 0.8104 | 3 |
| 0.4273 | 0.6530 | 0.71 | 0.7837 | 0.7451 | 0.7999 | 4 |
| 0.3538 | 0.6343 | 0.7188 | 0.7913 | 0.7533 | 0.8134 | 5 |
| 0.2872 | 0.6603 | 0.7316 | 0.8013 | 0.7648 | 0.8153 | 6 |
| 0.2438 | 0.6811 | 0.7239 | 0.7933 | 0.7570 | 0.8147 | 7 |
### Framework versions
- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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