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# layout_lm_fine_tune_funsd_dataset

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: 0.2499
- Validation Loss: 0.6927
- Train Overall Precision: 0.7401
- Train Overall Recall: 0.8159
- Train Overall F1: 0.7761
- Train Overall Accuracy: 0.8046
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.7326     | 1.4249          | 0.2261                  | 0.2052               | 0.2151           | 0.5250                 | 0     |
| 1.1901     | 0.9108          | 0.5753                  | 0.6207               | 0.5972           | 0.7156                 | 1     |
| 0.7777     | 0.7170          | 0.6511                  | 0.7396               | 0.6925           | 0.7679                 | 2     |
| 0.5681     | 0.6626          | 0.6988                  | 0.7777               | 0.7362           | 0.7920                 | 3     |
| 0.4449     | 0.6512          | 0.7236                  | 0.7762               | 0.7490           | 0.8013                 | 4     |
| 0.3576     | 0.6547          | 0.7251                  | 0.7888               | 0.7556           | 0.8073                 | 5     |
| 0.2910     | 0.6700          | 0.7380                  | 0.7958               | 0.7658           | 0.8106                 | 6     |
| 0.2499     | 0.6927          | 0.7401                  | 0.8159               | 0.7761           | 0.8046                 | 7     |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3

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

layout\_lm\_fine\_tune\_funsd\_dataset
======================================


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: 0.2499
* Validation Loss: 0.6927
* Train Overall Precision: 0.7401
* Train Overall Recall: 0.8159
* Train Overall F1: 0.7761
* Train Overall Accuracy: 0.8046
* 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 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #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 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #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 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3