
<!-- 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_manifesti_v3.4

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: 0.2080
- Precision: 0.7645
- Recall: 0.8239
- F1: 0.7931
- Accuracy: 0.9555

## 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        | 1.37  | 100  | 0.2707          | 0.6027    | 0.6723 | 0.6356 | 0.9309   |
| No log        | 2.74  | 200  | 0.1815          | 0.7131    | 0.7860 | 0.7477 | 0.9469   |
| No log        | 4.11  | 300  | 0.1749          | 0.7786    | 0.8258 | 0.8015 | 0.9580   |
| No log        | 5.48  | 400  | 0.1742          | 0.7982    | 0.8390 | 0.8181 | 0.9601   |
| 0.2249        | 6.85  | 500  | 0.1471          | 0.7700    | 0.8371 | 0.8022 | 0.9590   |
| 0.2249        | 8.22  | 600  | 0.1908          | 0.7851    | 0.8371 | 0.8103 | 0.9580   |
| 0.2249        | 9.59  | 700  | 0.1710          | 0.7880    | 0.8447 | 0.8154 | 0.9601   |
| 0.2249        | 10.96 | 800  | 0.1801          | 0.7578    | 0.8239 | 0.7895 | 0.9580   |
| 0.2249        | 12.33 | 900  | 0.1796          | 0.7686    | 0.8239 | 0.7952 | 0.9569   |
| 0.0454        | 13.7  | 1000 | 0.1868          | 0.7776    | 0.8277 | 0.8018 | 0.9580   |
| 0.0454        | 15.07 | 1100 | 0.2048          | 0.7592    | 0.8239 | 0.7902 | 0.9562   |
| 0.0454        | 16.44 | 1200 | 0.1944          | 0.7627    | 0.8277 | 0.7938 | 0.9572   |
| 0.0454        | 17.81 | 1300 | 0.1980          | 0.7583    | 0.8201 | 0.7880 | 0.9558   |
| 0.0454        | 19.18 | 1400 | 0.2098          | 0.7632    | 0.8239 | 0.7923 | 0.9555   |
| 0.0269        | 20.55 | 1500 | 0.2080          | 0.7645    | 0.8239 | 0.7931 | 0.9555   |


### 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": "perioli_manifesti_v3.4", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.7644991212653779, "name": "Precision"}, {"type": "recall", "value": 0.8238636363636364, "name": "Recall"}, {"type": "f1", "value": 0.7930720145852325, "name": "F1"}, {"type": "accuracy", "value": 0.955468471677948, "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\_manifesti\_v3.4
========================


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: 0.2080
* Precision: 0.7645
* Recall: 0.8239
* F1: 0.7931
* Accuracy: 0.9555


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 4.28.0.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: 1500 ### 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: 1500 ### 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: 1500### Training results### Framework versions


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