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# layoutlm-ttform

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: 0.8035
- Validation Loss: 0.6094
- Train Overall Precision: 0.8793
- Train Overall Recall: 0.7969
- Train Overall F1: 0.8361
- Train Overall Accuracy: 0.9204
- 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 |
|:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
| 1.9166     | 1.6851          | 0.125                   | 0.1562               | 0.1389           | 0.6567                 | 0     |
| 1.7084     | 1.4917          | 0.3793                  | 0.3438               | 0.3607           | 0.7811                 | 1     |
| 1.5343     | 1.3162          | 0.4151                  | 0.3438               | 0.3761           | 0.7811                 | 2     |
| 1.3620     | 1.1511          | 0.4528                  | 0.375                | 0.4103           | 0.8159                 | 3     |
| 1.2149     | 0.9970          | 0.5818                  | 0.5                  | 0.5378           | 0.8358                 | 4     |
| 1.0742     | 0.8546          | 0.8393                  | 0.7344               | 0.7833           | 0.8905                 | 5     |
| 0.9422     | 0.7259          | 0.8393                  | 0.7344               | 0.7833           | 0.9154                 | 6     |
| 0.8035     | 0.6094          | 0.8793                  | 0.7969               | 0.8361           | 0.9204                 | 7     |


### Framework versions

- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "layoutlm-ttform", "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 

layoutlm-ttform
===============


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: 0.8035
* Validation Loss: 0.6094
* Train Overall Precision: 0.8793
* Train Overall Recall: 0.7969
* Train Overall F1: 0.8361
* Train Overall Accuracy: 0.9204
* 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 2.9.2
* 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 2.9.2
* Datasets 2.9.0
* Tokenizers 0.13.2
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 4.26.0
* TensorFlow 2.9.2
* Datasets 2.9.0
* Tokenizers 0.13.2
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 4.26.0
* TensorFlow 2.9.2
* Datasets 2.9.0
* Tokenizers 0.13.2