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# HojadeRuta2.0

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: 0.0127
- Precision: 0.9639
- Recall: 0.9842
- F1: 0.9740
- Accuracy: 0.9986

## 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: 1500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.76  | 100  | 0.0136          | 0.9482    | 0.9632 | 0.9556 | 0.9943   |
| No log        | 1.52  | 200  | 0.0104          | 0.9536    | 0.9737 | 0.9635 | 0.9981   |
| No log        | 2.27  | 300  | 0.0116          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| No log        | 3.03  | 400  | 0.0121          | 0.9536    | 0.9737 | 0.9635 | 0.9981   |
| 0.0139        | 3.79  | 500  | 0.0126          | 0.9536    | 0.9737 | 0.9635 | 0.9981   |
| 0.0139        | 4.55  | 600  | 0.0102          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0139        | 5.3   | 700  | 0.0146          | 0.9536    | 0.9737 | 0.9635 | 0.9981   |
| 0.0139        | 6.06  | 800  | 0.0151          | 0.9536    | 0.9737 | 0.9635 | 0.9981   |
| 0.0139        | 6.82  | 900  | 0.0116          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0005        | 7.58  | 1000 | 0.0126          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0005        | 8.33  | 1100 | 0.0126          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0005        | 9.09  | 1200 | 0.0127          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0005        | 9.85  | 1300 | 0.0127          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0005        | 10.61 | 1400 | 0.0127          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |
| 0.0002        | 11.36 | 1500 | 0.0127          | 0.9639    | 0.9842 | 0.9740 | 0.9986   |


### 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": "HojadeRuta2.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.9639175257731959, "name": "Precision"}, {"type": "recall", "value": 0.9842105263157894, "name": "Recall"}, {"type": "f1", "value": 0.9739583333333334, "name": "F1"}, {"type": "accuracy", "value": 0.9985802176999526, "name": "Accuracy"}]}]}]}
transformers pytorch layoutlmv3 token-classification generated_from_trainer dataset:sroie license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

HojadeRuta2.0
=============


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: 0.0127
* Precision: 0.9639
* Recall: 0.9842
* F1: 0.9740
* Accuracy: 0.9986


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: 1500


### 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: 1500 ### 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 #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #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: 1500 ### Training results ### Framework versions


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