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# rhenus_v2.0

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: 0.2385
- Precision: 0.8050
- Recall: 0.8086
- F1: 0.8068
- Accuracy: 0.9704

## 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: 6000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.25  | 250  | 0.1729          | 0.7857    | 0.7973 | 0.7915 | 0.9687   |
| 0.0306        | 2.5   | 500  | 0.2302          | 0.7665    | 0.7882 | 0.7772 | 0.9614   |
| 0.0306        | 3.75  | 750  | 0.1761          | 0.7438    | 0.8086 | 0.7748 | 0.9648   |
| 0.0216        | 5.0   | 1000 | 0.1935          | 0.7566    | 0.8063 | 0.7807 | 0.9663   |
| 0.0216        | 6.25  | 1250 | 0.2136          | 0.7684    | 0.7928 | 0.7804 | 0.9663   |
| 0.016         | 7.5   | 1500 | 0.2358          | 0.7702    | 0.7894 | 0.7796 | 0.9653   |
| 0.016         | 8.75  | 1750 | 0.2213          | 0.7627    | 0.8007 | 0.7812 | 0.9656   |
| 0.0101        | 10.0  | 2000 | 0.2142          | 0.7840    | 0.8222 | 0.8027 | 0.9690   |
| 0.0101        | 11.25 | 2250 | 0.2440          | 0.7710    | 0.7701 | 0.7705 | 0.9637   |
| 0.0077        | 12.5  | 2500 | 0.2447          | 0.7984    | 0.7848 | 0.7915 | 0.9680   |
| 0.0077        | 13.75 | 2750 | 0.2034          | 0.8045    | 0.8109 | 0.8077 | 0.9696   |
| 0.0057        | 15.0  | 3000 | 0.2531          | 0.8086    | 0.7848 | 0.7966 | 0.9693   |
| 0.0057        | 16.25 | 3250 | 0.2410          | 0.7789    | 0.7939 | 0.7863 | 0.9671   |
| 0.0054        | 17.5  | 3500 | 0.2406          | 0.7930    | 0.7939 | 0.7934 | 0.9677   |
| 0.0054        | 18.75 | 3750 | 0.2512          | 0.7815    | 0.7860 | 0.7837 | 0.9656   |
| 0.0034        | 20.0  | 4000 | 0.2149          | 0.8047    | 0.8120 | 0.8083 | 0.9690   |
| 0.0034        | 21.25 | 4250 | 0.2195          | 0.8149    | 0.8075 | 0.8111 | 0.9701   |
| 0.0022        | 22.5  | 4500 | 0.2185          | 0.7954    | 0.8143 | 0.8047 | 0.9690   |
| 0.0022        | 23.75 | 4750 | 0.2305          | 0.8086    | 0.8086 | 0.8086 | 0.9701   |
| 0.0018        | 25.0  | 5000 | 0.2266          | 0.7921    | 0.8199 | 0.8058 | 0.9693   |
| 0.0018        | 26.25 | 5250 | 0.2275          | 0.7952    | 0.8177 | 0.8063 | 0.9706   |
| 0.0013        | 27.5  | 5500 | 0.2322          | 0.8049    | 0.8177 | 0.8112 | 0.9716   |
| 0.0013        | 28.75 | 5750 | 0.2340          | 0.8054    | 0.8154 | 0.8104 | 0.9714   |
| 0.0011        | 30.0  | 6000 | 0.2385          | 0.8050    | 0.8086 | 0.8068 | 0.9704   |


### Framework versions

- Transformers 4.28.0.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_v2.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8049605411499436, "name": "Precision"}, {"type": "recall", "value": 0.8086070215175538, "name": "Recall"}, {"type": "f1", "value": 0.8067796610169492, "name": "F1"}, {"type": "accuracy", "value": 0.9704417670682731, "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\_v2.0
============


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: 0.2385
* Precision: 0.8050
* Recall: 0.8086
* F1: 0.8068
* Accuracy: 0.9704


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: 6000


### Training results



### Framework versions


* Transformers 4.28.0.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: 6000 ### Training results ### Framework versions


* Transformers 4.28.0.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: 6000 ### Training results ### Framework versions


* Transformers 4.28.0.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: 6000### Training results### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2