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---
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: layoutlm-invoice-tf-2
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-invoice-tf-2
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: 0.3115
- Validation Loss: 0.3451
- Train Overall Precision: 0.5831
- Train Overall Recall: 0.5567
- Train Overall F1: 0.5696
- Train Overall Accuracy: 0.8995
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 2.3655 | 2.0025 | 0.0056 | 0.0101 | 0.0072 | 0.3973 | 0 |
| 1.7668 | 1.5306 | 0.0185 | 0.0327 | 0.0237 | 0.5455 | 1 |
| 1.3422 | 1.1230 | 0.0595 | 0.0831 | 0.0693 | 0.6698 | 2 |
| 1.0006 | 0.9051 | 0.1393 | 0.1990 | 0.1639 | 0.7432 | 3 |
| 0.7743 | 0.6738 | 0.2127 | 0.2620 | 0.2348 | 0.8158 | 4 |
| 0.5996 | 0.5262 | 0.4035 | 0.4106 | 0.4070 | 0.8628 | 5 |
| 0.4179 | 0.3998 | 0.4856 | 0.4685 | 0.4769 | 0.8892 | 6 |
| 0.3115 | 0.3451 | 0.5831 | 0.5567 | 0.5696 | 0.8995 | 7 |
### Framework versions
- Transformers 4.41.0.dev0
- TensorFlow 2.16.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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