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---
license: mit
tags:
- generated_from_keras_callback
base_model: microsoft/layoutlm-base-uncased
model-index:
- name: layoutlm-invoice-tf-1
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-1
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: 0.2994
- Validation Loss: 0.3489
- Train Overall Precision: 0.5682
- Train Overall Recall: 0.5668
- Train Overall F1: 0.5675
- Train Overall Accuracy: 0.8973
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 2.4376 | 2.0394 | 0.0 | 0.0 | 0.0 | 0.3247 | 0 |
| 1.7800 | 1.4827 | 0.0112 | 0.0202 | 0.0144 | 0.5774 | 1 |
| 1.3231 | 1.0832 | 0.0710 | 0.1008 | 0.0833 | 0.6988 | 2 |
| 0.9662 | 0.8311 | 0.1626 | 0.2015 | 0.1800 | 0.7421 | 3 |
| 0.7250 | 0.6259 | 0.2949 | 0.3350 | 0.3137 | 0.8371 | 4 |
| 0.5245 | 0.4803 | 0.4049 | 0.4131 | 0.4090 | 0.8646 | 5 |
| 0.3951 | 0.3957 | 0.5206 | 0.5088 | 0.5146 | 0.8892 | 6 |
| 0.2994 | 0.3489 | 0.5682 | 0.5668 | 0.5675 | 0.8973 | 7 |
### Framework versions
- Transformers 4.41.0.dev0
- TensorFlow 2.16.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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