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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: 0.2350
- Validation Loss: 0.6723
- Train Overall Precision: 0.7420
- Train Overall Recall: 0.7978
- Train Overall F1: 0.7689
- Train Overall Accuracy: 0.8134
- 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: float32
### Training results
| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7200 | 1.4450 | 0.2446 | 0.2479 | 0.2462 | 0.4720 | 0 |
| 1.1874 | 0.8977 | 0.5707 | 0.6563 | 0.6105 | 0.7371 | 1 |
| 0.7800 | 0.7307 | 0.6355 | 0.7471 | 0.6868 | 0.7774 | 2 |
| 0.5924 | 0.6328 | 0.6774 | 0.7817 | 0.7258 | 0.8045 | 3 |
| 0.4601 | 0.6043 | 0.7228 | 0.7878 | 0.7539 | 0.8133 | 4 |
| 0.3731 | 0.6318 | 0.7220 | 0.7988 | 0.7585 | 0.8099 | 5 |
| 0.2933 | 0.6364 | 0.7358 | 0.8023 | 0.7676 | 0.8145 | 6 |
| 0.2350 | 0.6723 | 0.7420 | 0.7978 | 0.7689 | 0.8134 | 7 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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