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---
license: mit
tags:
- generated_from_keras_callback
base_model: microsoft/layoutlm-base-uncased
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 [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: 0.2406
- Validation Loss: 0.7155
- Train Overall Precision: 0.7459
- Train Overall Recall: 0.7893
- Train Overall F1: 0.7669
- Train Overall Accuracy: 0.8064
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7115 | 1.4279 | 0.2575 | 0.2965 | 0.2757 | 0.4884 | 0 |
| 1.1520 | 0.8490 | 0.5994 | 0.6854 | 0.6395 | 0.7372 | 1 |
| 0.7816 | 0.7069 | 0.6391 | 0.7471 | 0.6889 | 0.7808 | 2 |
| 0.5815 | 0.6601 | 0.7089 | 0.7672 | 0.7369 | 0.7992 | 3 |
| 0.4460 | 0.6306 | 0.7093 | 0.7787 | 0.7424 | 0.8060 | 4 |
| 0.3658 | 0.6575 | 0.7372 | 0.7812 | 0.7586 | 0.8111 | 5 |
| 0.2926 | 0.6658 | 0.7240 | 0.7832 | 0.7525 | 0.8096 | 6 |
| 0.2406 | 0.7155 | 0.7459 | 0.7893 | 0.7669 | 0.8064 | 7 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.16.1
- Datasets 2.19.2
- Tokenizers 0.19.1
|