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---
license: mit
tags:
- generated_from_keras_callback
base_model: microsoft/layoutlm-base-uncased
model-index:
- name: layoutlm-funsd-tf-l
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-l
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: 0.2621
- Validation Loss: 0.6925
- Train Overall Precision: 0.7431
- Train Overall Recall: 0.7822
- Train Overall F1: 0.7622
- Train Overall Accuracy: 0.8060
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6855 | 1.4048 | 0.2655 | 0.2945 | 0.2793 | 0.5163 | 0 |
| 1.1539 | 0.8468 | 0.6205 | 0.6548 | 0.6372 | 0.7410 | 1 |
| 0.7523 | 0.7215 | 0.6573 | 0.7516 | 0.7013 | 0.7662 | 2 |
| 0.5749 | 0.6737 | 0.6735 | 0.7536 | 0.7113 | 0.7868 | 3 |
| 0.4482 | 0.6720 | 0.7027 | 0.7792 | 0.7390 | 0.7917 | 4 |
| 0.3695 | 0.6387 | 0.7142 | 0.7948 | 0.7523 | 0.8047 | 5 |
| 0.3123 | 0.6608 | 0.7443 | 0.7958 | 0.7692 | 0.8154 | 6 |
| 0.2621 | 0.6925 | 0.7431 | 0.7822 | 0.7622 | 0.8060 | 7 |
### Framework versions
- Transformers 4.41.0.dev0
- TensorFlow 2.16.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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