Full notebook:

https://github.com/MustafaAlahmid/hugging_face_models/blob/main/layoutlm_funsd.ipynb


---
tags:
- generated_from_keras_callback
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: 0.0691
- Validation Loss: 0.7709
- Train Overall Precision: 0.7410
- Train Overall Recall: 0.7953
- Train Overall F1: 0.7672
- Train Overall Accuracy: 0.8057
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.1546     | 0.6939          | 0.6387                  | 0.7381               | 0.6848           | 0.7761                 | 0     |
| 0.6170     | 0.5872          | 0.7099                  | 0.7832               | 0.7448           | 0.7949                 | 1     |
| 0.4005     | 0.6761          | 0.6766                  | 0.7777               | 0.7236           | 0.7729                 | 2     |
| 0.2921     | 0.6447          | 0.7169                  | 0.7852               | 0.7495           | 0.7934                 | 3     |
| 0.2029     | 0.7472          | 0.7019                  | 0.7953               | 0.7457           | 0.7852                 | 4     |
| 0.1383     | 0.7195          | 0.7327                  | 0.7938               | 0.7620           | 0.8048                 | 5     |
| 0.0932     | 0.7851          | 0.7272                  | 0.7998               | 0.7618           | 0.8063                 | 6     |
| 0.0691     | 0.7709          | 0.7410                  | 0.7953               | 0.7672           | 0.8057                 | 7     |


### Framework versions

- Transformers 4.26.0
- TensorFlow 2.10.0
- Datasets 2.9.0
- Tokenizers 0.13.2

{}
transformers tf tensorboard layoutlm token-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #autotrain_compatible #endpoints_compatible #region-us 

Full notebook:


URL




---


tags:


* generated\_from\_keras\_callback
model-index:
* name: layoutlm-funsd-tf
results: []




---


layoutlm-funsd-tf
=================


This model is a fine-tuned version of microsoft/layoutlm-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.0691
* Validation Loss: 0.7709
* Train Overall Precision: 0.7410
* Train Overall Recall: 0.7953
* Train Overall F1: 0.7672
* Train Overall Accuracy: 0.8057
* 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



### Framework versions


* Transformers 4.26.0
* TensorFlow 2.10.0
* Datasets 2.9.0
* Tokenizers 0.13.2



### 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 ### Framework versions


* Transformers 4.26.0
* TensorFlow 2.10.0
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.0
* TensorFlow 2.10.0
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.26.0
* TensorFlow 2.10.0
* Datasets 2.9.0
* Tokenizers 0.13.2