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# marazzi2.0

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: 0.0477
- Precision: 0.8218
- Recall: 0.7386
- F1: 0.7780
- Accuracy: 0.9937

## 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        | 0.24  | 100  | 0.1429          | 0.5870    | 0.0882 | 0.1534 | 0.9809   |
| No log        | 0.47  | 200  | 0.1163          | 0.5870    | 0.0882 | 0.1534 | 0.9809   |
| No log        | 0.71  | 300  | 0.0919          | 0.5690    | 0.1078 | 0.1813 | 0.9815   |
| No log        | 0.95  | 400  | 0.0787          | 0.6304    | 0.2843 | 0.3919 | 0.9858   |
| 0.0844        | 1.18  | 500  | 0.0755          | 0.6522    | 0.4412 | 0.5263 | 0.9873   |
| 0.0844        | 1.42  | 600  | 0.0621          | 0.6533    | 0.4804 | 0.5537 | 0.9872   |
| 0.0844        | 1.66  | 700  | 0.0631          | 0.7415    | 0.4967 | 0.5949 | 0.9895   |
| 0.0844        | 1.9   | 800  | 0.0463          | 0.7764    | 0.6013 | 0.6777 | 0.9912   |
| 0.0844        | 2.13  | 900  | 0.0429          | 0.7821    | 0.6569 | 0.7140 | 0.9922   |
| 0.0265        | 2.37  | 1000 | 0.0421          | 0.7881    | 0.6928 | 0.7374 | 0.9929   |
| 0.0265        | 2.61  | 1100 | 0.0516          | 0.8050    | 0.6340 | 0.7093 | 0.9919   |
| 0.0265        | 2.84  | 1200 | 0.0474          | 0.7854    | 0.6340 | 0.7016 | 0.9917   |
| 0.0265        | 3.08  | 1300 | 0.0378          | 0.8134    | 0.7549 | 0.7831 | 0.9942   |
| 0.0265        | 3.32  | 1400 | 0.0374          | 0.8143    | 0.7451 | 0.7782 | 0.9938   |
| 0.0116        | 3.55  | 1500 | 0.0466          | 0.8213    | 0.7059 | 0.7592 | 0.9933   |
| 0.0116        | 3.79  | 1600 | 0.0444          | 0.8172    | 0.7157 | 0.7631 | 0.9933   |
| 0.0116        | 4.03  | 1700 | 0.0442          | 0.8218    | 0.7386 | 0.7780 | 0.9937   |
| 0.0116        | 4.27  | 1800 | 0.0473          | 0.8118    | 0.7190 | 0.7626 | 0.9933   |
| 0.0116        | 4.5   | 1900 | 0.0520          | 0.8030    | 0.7059 | 0.7513 | 0.9932   |
| 0.0074        | 4.74  | 2000 | 0.0476          | 0.8155    | 0.7222 | 0.7660 | 0.9936   |
| 0.0074        | 4.98  | 2100 | 0.0504          | 0.8038    | 0.6830 | 0.7385 | 0.9931   |
| 0.0074        | 5.21  | 2200 | 0.0475          | 0.8267    | 0.7484 | 0.7856 | 0.9937   |
| 0.0074        | 5.45  | 2300 | 0.0506          | 0.8081    | 0.7157 | 0.7591 | 0.9933   |
| 0.0074        | 5.69  | 2400 | 0.0508          | 0.8168    | 0.7288 | 0.7703 | 0.9936   |
| 0.005         | 5.92  | 2500 | 0.0477          | 0.8218    | 0.7386 | 0.7780 | 0.9937   |


### 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": "marazzi2.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8218181818181818, "name": "Precision"}, {"type": "recall", "value": 0.738562091503268, "name": "Recall"}, {"type": "f1", "value": 0.7779690189328744, "name": "F1"}, {"type": "accuracy", "value": 0.9937027707808564, "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 

marazzi2.0
==========


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: 0.0477
* Precision: 0.8218
* Recall: 0.7386
* F1: 0.7780
* Accuracy: 0.9937


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 #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: 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 #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: 2500### Training results### Framework versions


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