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# perioli_vgm_v3.0

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: 0.0975
- Precision: 0.6585
- Recall: 0.5912
- F1: 0.6231
- Accuracy: 0.9881

## 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        | 0.94  | 100  | 0.1390          | 0.1538    | 0.0292 | 0.0491 | 0.9768   |
| No log        | 1.89  | 200  | 0.1011          | 0.4674    | 0.3139 | 0.3755 | 0.9820   |
| No log        | 2.83  | 300  | 0.0857          | 0.4896    | 0.3431 | 0.4034 | 0.9836   |
| No log        | 3.77  | 400  | 0.0836          | 0.6053    | 0.5036 | 0.5498 | 0.9872   |
| 0.0974        | 4.72  | 500  | 0.0751          | 0.5369    | 0.5839 | 0.5594 | 0.9858   |
| 0.0974        | 5.66  | 600  | 0.0808          | 0.6493    | 0.6350 | 0.6421 | 0.9872   |
| 0.0974        | 6.6   | 700  | 0.0760          | 0.6231    | 0.5912 | 0.6067 | 0.9876   |
| 0.0974        | 7.55  | 800  | 0.0906          | 0.5942    | 0.5985 | 0.5964 | 0.9843   |
| 0.0974        | 8.49  | 900  | 0.0831          | 0.6693    | 0.6204 | 0.6439 | 0.9872   |
| 0.0169        | 9.43  | 1000 | 0.0907          | 0.6538    | 0.6204 | 0.6367 | 0.9858   |
| 0.0169        | 10.38 | 1100 | 0.0834          | 0.6535    | 0.6058 | 0.6288 | 0.9879   |
| 0.0169        | 11.32 | 1200 | 0.0861          | 0.6721    | 0.5985 | 0.6332 | 0.9883   |
| 0.0169        | 12.26 | 1300 | 0.0930          | 0.6       | 0.5693 | 0.5843 | 0.9849   |
| 0.0169        | 13.21 | 1400 | 0.0976          | 0.625     | 0.5839 | 0.6038 | 0.9861   |
| 0.0058        | 14.15 | 1500 | 0.0933          | 0.5827    | 0.5912 | 0.5870 | 0.9863   |
| 0.0058        | 15.09 | 1600 | 0.0892          | 0.6429    | 0.5912 | 0.6160 | 0.9885   |
| 0.0058        | 16.04 | 1700 | 0.0889          | 0.6613    | 0.5985 | 0.6284 | 0.9888   |
| 0.0058        | 16.98 | 1800 | 0.0918          | 0.6723    | 0.5839 | 0.625  | 0.9881   |
| 0.0058        | 17.92 | 1900 | 0.0924          | 0.6512    | 0.6131 | 0.6316 | 0.9879   |
| 0.003         | 18.87 | 2000 | 0.0958          | 0.6803    | 0.6058 | 0.6409 | 0.9881   |
| 0.003         | 19.81 | 2100 | 0.0941          | 0.6923    | 0.5912 | 0.6378 | 0.9888   |
| 0.003         | 20.75 | 2200 | 0.0966          | 0.6349    | 0.5839 | 0.6084 | 0.9876   |
| 0.003         | 21.7  | 2300 | 0.0973          | 0.6423    | 0.5766 | 0.6077 | 0.9879   |
| 0.003         | 22.64 | 2400 | 0.0965          | 0.6585    | 0.5912 | 0.6231 | 0.9881   |
| 0.0015        | 23.58 | 2500 | 0.0975          | 0.6585    | 0.5912 | 0.6231 | 0.9881   |


### 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": "perioli_vgm_v3.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.6585365853658537, "name": "Precision"}, {"type": "recall", "value": 0.5912408759124088, "name": "Recall"}, {"type": "f1", "value": 0.6230769230769231, "name": "F1"}, {"type": "accuracy", "value": 0.9880791722896987, "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 

perioli\_vgm\_v3.0
==================


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: 0.0975
* Precision: 0.6585
* Recall: 0.5912
* F1: 0.6231
* Accuracy: 0.9881


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