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---
license: mit
tags:
- generated_from_keras_callback
base_model: cor-c/layoutlm-funsd-tf
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 [cor-c/layoutlm-funsd-tf](https://huggingface.co/cor-c/layoutlm-funsd-tf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0632
- Validation Loss: 0.8795
- Train Overall Precision: 0.7424
- Train Overall Recall: 0.8038
- Train Overall F1: 0.7719
- Train Overall Accuracy: 0.8103
- 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 2.9999999242136255e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
### Training results
| Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 0.2119 | 0.7340 | 0.7292 | 0.8053 | 0.7654 | 0.8046 | 0 |
| 0.1948 | 0.7521 | 0.7406 | 0.7963 | 0.7674 | 0.8027 | 1 |
| 0.1485 | 0.7879 | 0.7256 | 0.7988 | 0.7604 | 0.8019 | 2 |
| 0.1220 | 0.7861 | 0.7403 | 0.7983 | 0.7682 | 0.8073 | 3 |
| 0.1003 | 0.8253 | 0.7495 | 0.8018 | 0.7748 | 0.8087 | 4 |
| 0.0825 | 0.8617 | 0.7491 | 0.7968 | 0.7722 | 0.8048 | 5 |
| 0.0676 | 0.8938 | 0.7503 | 0.8128 | 0.7803 | 0.8062 | 6 |
| 0.0632 | 0.8795 | 0.7424 | 0.8038 | 0.7719 | 0.8103 | 7 |
### Framework versions
- Transformers 4.41.0.dev0
- TensorFlow 2.16.1
- Datasets 2.19.1
- Tokenizers 0.19.1
|