
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# perioli_vgm_v3.1

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on the sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1395
- Precision: 0.6842
- Recall: 0.6341
- F1: 0.6582
- Accuracy: 0.9880

## 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        | 1.08  | 100  | 0.1117          | 0.4396    | 0.3252 | 0.3738 | 0.9796   |
| No log        | 2.15  | 200  | 0.1082          | 0.5957    | 0.4553 | 0.5161 | 0.9849   |
| No log        | 3.23  | 300  | 0.1041          | 0.5752    | 0.5285 | 0.5508 | 0.9844   |
| No log        | 4.3   | 400  | 0.1024          | 0.6944    | 0.6098 | 0.6494 | 0.9872   |
| 0.0553        | 5.38  | 500  | 0.0826          | 0.6364    | 0.6260 | 0.6311 | 0.9880   |
| 0.0553        | 6.45  | 600  | 0.0795          | 0.672     | 0.6829 | 0.6774 | 0.9888   |
| 0.0553        | 7.53  | 700  | 0.1035          | 0.6903    | 0.6341 | 0.6610 | 0.9883   |
| 0.0553        | 8.6   | 800  | 0.0913          | 0.8081    | 0.6504 | 0.7207 | 0.9905   |
| 0.0553        | 9.68  | 900  | 0.0901          | 0.6860    | 0.6748 | 0.6803 | 0.9886   |
| 0.0048        | 10.75 | 1000 | 0.0868          | 0.7168    | 0.6585 | 0.6864 | 0.9891   |
| 0.0048        | 11.83 | 1100 | 0.1281          | 0.7179    | 0.6829 | 0.7000 | 0.9877   |
| 0.0048        | 12.9  | 1200 | 0.0936          | 0.6803    | 0.6748 | 0.6776 | 0.9886   |
| 0.0048        | 13.98 | 1300 | 0.0862          | 0.6183    | 0.6585 | 0.6378 | 0.9883   |
| 0.0048        | 15.05 | 1400 | 0.1058          | 0.7009    | 0.6667 | 0.6833 | 0.9877   |
| 0.0013        | 16.13 | 1500 | 0.1182          | 0.6754    | 0.6260 | 0.6498 | 0.9874   |
| 0.0013        | 17.2  | 1600 | 0.1192          | 0.7069    | 0.6667 | 0.6862 | 0.9883   |
| 0.0013        | 18.28 | 1700 | 0.1209          | 0.6583    | 0.6423 | 0.6502 | 0.9880   |
| 0.0013        | 19.35 | 1800 | 0.1324          | 0.6552    | 0.6179 | 0.6360 | 0.9874   |
| 0.0013        | 20.43 | 1900 | 0.1310          | 0.6610    | 0.6341 | 0.6473 | 0.9874   |
| 0.0004        | 21.51 | 2000 | 0.1352          | 0.6610    | 0.6341 | 0.6473 | 0.9874   |
| 0.0004        | 22.58 | 2100 | 0.1379          | 0.6724    | 0.6341 | 0.6527 | 0.9877   |
| 0.0004        | 23.66 | 2200 | 0.1397          | 0.6991    | 0.6423 | 0.6695 | 0.9883   |
| 0.0004        | 24.73 | 2300 | 0.1384          | 0.6964    | 0.6341 | 0.6638 | 0.9886   |
| 0.0004        | 25.81 | 2400 | 0.1391          | 0.6964    | 0.6341 | 0.6638 | 0.9886   |
| 0.0002        | 26.88 | 2500 | 0.1395          | 0.6842    | 0.6341 | 0.6582 | 0.9880   |


### 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_v3.1", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.6842105263157895, "name": "Precision"}, {"type": "recall", "value": 0.6341463414634146, "name": "Recall"}, {"type": "f1", "value": 0.6582278481012659, "name": "F1"}, {"type": "accuracy", "value": 0.9880022321428571, "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\_v3.1
==================


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


* Loss: 0.1395
* Precision: 0.6842
* Recall: 0.6341
* F1: 0.6582
* Accuracy: 0.9880


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