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# rhenus_model

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1560
- Precision: 0.8057
- Recall: 0.8397
- F1: 0.8223
- Accuracy: 0.9734

## 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:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.96  | 100  | 0.7818          | 0.0909    | 0.0042 | 0.0081 | 0.8569   |
| No log        | 3.92  | 200  | 0.5681          | 0.2442    | 0.0886 | 0.1300 | 0.8708   |
| No log        | 5.88  | 300  | 0.4568          | 0.2803    | 0.1857 | 0.2234 | 0.8913   |
| No log        | 7.84  | 400  | 0.3759          | 0.5053    | 0.4051 | 0.4496 | 0.9196   |
| 0.5952        | 9.8   | 500  | 0.2987          | 0.6560    | 0.6034 | 0.6286 | 0.9456   |
| 0.5952        | 11.76 | 600  | 0.2585          | 0.6721    | 0.6920 | 0.6819 | 0.9456   |
| 0.5952        | 13.73 | 700  | 0.2016          | 0.7247    | 0.7553 | 0.7397 | 0.9595   |
| 0.5952        | 15.69 | 800  | 0.2053          | 0.704     | 0.7426 | 0.7228 | 0.9573   |
| 0.5952        | 17.65 | 900  | 0.1845          | 0.7782    | 0.7848 | 0.7815 | 0.9667   |
| 0.1097        | 19.61 | 1000 | 0.1917          | 0.75      | 0.7848 | 0.7670 | 0.9623   |
| 0.1097        | 21.57 | 1100 | 0.1897          | 0.8099    | 0.8270 | 0.8184 | 0.9695   |
| 0.1097        | 23.53 | 1200 | 0.1848          | 0.7901    | 0.8101 | 0.8    | 0.9684   |
| 0.1097        | 25.49 | 1300 | 0.1533          | 0.8016    | 0.8523 | 0.8262 | 0.9734   |
| 0.1097        | 27.45 | 1400 | 0.1534          | 0.8204    | 0.8481 | 0.8340 | 0.9750   |
| 0.0384        | 29.41 | 1500 | 0.1879          | 0.8024    | 0.8397 | 0.8206 | 0.9695   |
| 0.0384        | 31.37 | 1600 | 0.1550          | 0.816     | 0.8608 | 0.8378 | 0.9750   |
| 0.0384        | 33.33 | 1700 | 0.1598          | 0.8279    | 0.8523 | 0.8399 | 0.9756   |
| 0.0384        | 35.29 | 1800 | 0.1643          | 0.8148    | 0.8354 | 0.825  | 0.9728   |
| 0.0384        | 37.25 | 1900 | 0.1558          | 0.792     | 0.8354 | 0.8131 | 0.9728   |
| 0.02          | 39.22 | 2000 | 0.1699          | 0.7944    | 0.8312 | 0.8124 | 0.9717   |
| 0.02          | 41.18 | 2100 | 0.1558          | 0.8138    | 0.8481 | 0.8306 | 0.9750   |
| 0.02          | 43.14 | 2200 | 0.1566          | 0.8024    | 0.8397 | 0.8206 | 0.9728   |
| 0.02          | 45.1  | 2300 | 0.1617          | 0.8049    | 0.8354 | 0.8199 | 0.9734   |
| 0.02          | 47.06 | 2400 | 0.1571          | 0.8016    | 0.8354 | 0.8182 | 0.9723   |
| 0.014         | 49.02 | 2500 | 0.1560          | 0.8057    | 0.8397 | 0.8223 | 0.9734   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["sroie"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "rhenus_model", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.805668016194332, "name": "Precision"}, {"type": "recall", "value": 0.8396624472573839, "name": "Recall"}, {"type": "f1", "value": 0.8223140495867768, "name": "F1"}, {"type": "accuracy", "value": 0.9733777038269551, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:sroie license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

rhenus\_model
=============


This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1560
* Precision: 0.8057
* Recall: 0.8397
* F1: 0.8223
* Accuracy: 0.9734


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:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2500


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2500 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2500 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2500### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2