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# passive_invoices_v3.8.2

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: 0.1409
- Precision: 0.8350
- Recall: 0.8635
- F1: 0.8490
- Accuracy: 0.9680

## 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: 9000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9509        | 0.48  | 500  | 0.7700          | 0.2732    | 0.1659 | 0.2065 | 0.8042   |
| 0.411         | 0.96  | 1000 | 0.5019          | 0.4891    | 0.4064 | 0.4439 | 0.8746   |
| 0.254         | 1.45  | 1500 | 0.3585          | 0.5987    | 0.5927 | 0.5957 | 0.9104   |
| 0.1751        | 1.93  | 2000 | 0.2843          | 0.6884    | 0.6445 | 0.6657 | 0.9287   |
| 0.1341        | 2.41  | 2500 | 0.2556          | 0.6824    | 0.7243 | 0.7027 | 0.9348   |
| 0.1199        | 2.89  | 3000 | 0.2163          | 0.7250    | 0.7380 | 0.7314 | 0.9439   |
| 0.0946        | 3.37  | 3500 | 0.1940          | 0.7449    | 0.7803 | 0.7622 | 0.9500   |
| 0.0848        | 3.85  | 4000 | 0.1788          | 0.7952    | 0.7950 | 0.7951 | 0.9561   |
| 0.0685        | 4.34  | 4500 | 0.1779          | 0.7991    | 0.8057 | 0.8024 | 0.9580   |
| 0.0675        | 4.82  | 5000 | 0.1592          | 0.8178    | 0.8249 | 0.8213 | 0.9641   |
| 0.0547        | 5.3   | 5500 | 0.1518          | 0.8179    | 0.8331 | 0.8254 | 0.9629   |
| 0.0586        | 5.78  | 6000 | 0.1496          | 0.8093    | 0.8434 | 0.8260 | 0.9633   |
| 0.0469        | 6.26  | 6500 | 0.1499          | 0.8166    | 0.8474 | 0.8317 | 0.9650   |
| 0.0477        | 6.74  | 7000 | 0.1435          | 0.8200    | 0.8593 | 0.8392 | 0.9657   |
| 0.0394        | 7.23  | 7500 | 0.1447          | 0.8229    | 0.8532 | 0.8377 | 0.9664   |
| 0.0418        | 7.71  | 8000 | 0.1399          | 0.8325    | 0.8589 | 0.8455 | 0.9676   |
| 0.0393        | 8.19  | 8500 | 0.1407          | 0.8299    | 0.8663 | 0.8477 | 0.9679   |
| 0.0334        | 8.67  | 9000 | 0.1409          | 0.8350    | 0.8635 | 0.8490 | 0.9680   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.2.2
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["sroie"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "passive_invoices_v3.8.2", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8349621980453623, "name": "Precision"}, {"type": "recall", "value": 0.8634630053394355, "name": "Recall"}, {"type": "f1", "value": 0.8489734695790757, "name": "F1"}, {"type": "accuracy", "value": 0.9679576483700195, "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