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---
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: willmyrick/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. -->
# willmyrick/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: 0.2395
- Validation Loss: 0.6723
- Train Overall Precision: 0.7269
- Train Overall Recall: 0.8013
- Train Overall F1: 0.7623
- Train Overall Accuracy: 0.8071
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6854 | 1.3883 | 0.2671 | 0.2494 | 0.2579 | 0.4942 | 0 |
| 1.1172 | 0.8636 | 0.5871 | 0.6392 | 0.6121 | 0.7287 | 1 |
| 0.7701 | 0.7274 | 0.6558 | 0.7170 | 0.6850 | 0.7690 | 2 |
| 0.5880 | 0.6978 | 0.6814 | 0.7501 | 0.7141 | 0.7747 | 3 |
| 0.4569 | 0.7022 | 0.6984 | 0.7612 | 0.7285 | 0.7710 | 4 |
| 0.3594 | 0.6280 | 0.7095 | 0.7903 | 0.7477 | 0.8118 | 5 |
| 0.3095 | 0.6566 | 0.7298 | 0.7832 | 0.7556 | 0.8085 | 6 |
| 0.2395 | 0.6723 | 0.7269 | 0.8013 | 0.7623 | 0.8071 | 7 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.16.1
- Datasets 2.19.2
- Tokenizers 0.19.1
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