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# 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: 0.3061
- Validation Loss: 0.6626
- Train Overall Precision: 0.7205
- Train Overall Recall: 0.7863
- Train Overall F1: 0.7519
- Train Overall Accuracy: 0.8006
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.6700     | 1.3895          | 0.2812                  | 0.2880               | 0.2846           | 0.5333                 | 0     |
| 1.1465     | 0.8828          | 0.5819                  | 0.6433               | 0.6111           | 0.7324                 | 1     |
| 0.7878     | 0.7302          | 0.6497                  | 0.7240               | 0.6849           | 0.7791                 | 2     |
| 0.6195     | 0.6630          | 0.6844                  | 0.7692               | 0.7243           | 0.7949                 | 3     |
| 0.5031     | 0.6265          | 0.6929                  | 0.7903               | 0.7384           | 0.8112                 | 4     |
| 0.4202     | 0.6244          | 0.7329                  | 0.7863               | 0.7587           | 0.8124                 | 5     |
| 0.3479     | 0.6233          | 0.7275                  | 0.7702               | 0.7482           | 0.8127                 | 6     |
| 0.3061     | 0.6626          | 0.7205                  | 0.7863               | 0.7519           | 0.8006                 | 7     |


### Framework versions

- Transformers 4.25.1
- TensorFlow 2.9.0
- Datasets 2.8.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "layoutlm-funsd-tf", "results": []}]}
transformers tf tensorboard layoutlm token-classification generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

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: 0.3061
* Validation Loss: 0.6626
* Train Overall Precision: 0.7205
* Train Overall Recall: 0.7863
* Train Overall F1: 0.7519
* Train Overall Accuracy: 0.8006
* 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 4.25.1
* TensorFlow 2.9.0
* Datasets 2.8.0
* 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 4.25.1
* TensorFlow 2.9.0
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #generated_from_keras_callback #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 4.25.1
* TensorFlow 2.9.0
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #tensorboard #layoutlm #token-classification #generated_from_keras_callback #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 4.25.1
* TensorFlow 2.9.0
* Datasets 2.8.0
* Tokenizers 0.13.2