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# passive_invoices_v4.2

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: 0.0997
- Precision: 0.8886
- Recall: 0.9114
- F1: 0.8998
- Accuracy: 0.9789

## 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: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0618        | 0.28  | 500   | 0.8119          | 0.2123    | 0.1210 | 0.1542 | 0.7961   |
| 0.5657        | 0.56  | 1000  | 0.5361          | 0.4304    | 0.4043 | 0.4170 | 0.8610   |
| 0.3674        | 0.84  | 1500  | 0.3867          | 0.5741    | 0.5777 | 0.5759 | 0.9006   |
| 0.2746        | 1.11  | 2000  | 0.2914          | 0.6328    | 0.6493 | 0.6410 | 0.9180   |
| 0.2043        | 1.39  | 2500  | 0.2672          | 0.6404    | 0.6865 | 0.6627 | 0.9231   |
| 0.1649        | 1.67  | 3000  | 0.2108          | 0.7025    | 0.7271 | 0.7146 | 0.9412   |
| 0.1428        | 1.95  | 3500  | 0.1872          | 0.7389    | 0.7634 | 0.7510 | 0.9482   |
| 0.1193        | 2.23  | 4000  | 0.1657          | 0.7607    | 0.7966 | 0.7783 | 0.9537   |
| 0.1039        | 2.51  | 4500  | 0.1568          | 0.8020    | 0.8032 | 0.8026 | 0.9587   |
| 0.1011        | 2.78  | 5000  | 0.1499          | 0.7886    | 0.8224 | 0.8052 | 0.9589   |
| 0.0772        | 3.06  | 5500  | 0.1478          | 0.7993    | 0.8372 | 0.8178 | 0.9619   |
| 0.0686        | 3.34  | 6000  | 0.1265          | 0.8094    | 0.8522 | 0.8302 | 0.9664   |
| 0.0725        | 3.62  | 6500  | 0.1148          | 0.8319    | 0.8549 | 0.8433 | 0.9700   |
| 0.0691        | 3.9   | 7000  | 0.1231          | 0.8191    | 0.8622 | 0.8401 | 0.9677   |
| 0.0594        | 4.18  | 7500  | 0.1139          | 0.8460    | 0.8642 | 0.8550 | 0.9713   |
| 0.0607        | 4.45  | 8000  | 0.1261          | 0.8299    | 0.8638 | 0.8465 | 0.9669   |
| 0.0568        | 4.73  | 8500  | 0.1061          | 0.8531    | 0.8830 | 0.8678 | 0.9727   |
| 0.0458        | 5.01  | 9000  | 0.1037          | 0.8499    | 0.8854 | 0.8673 | 0.9740   |
| 0.0492        | 5.29  | 9500  | 0.1065          | 0.8588    | 0.8852 | 0.8718 | 0.9734   |
| 0.0436        | 5.57  | 10000 | 0.1048          | 0.8597    | 0.8921 | 0.8756 | 0.9748   |
| 0.0402        | 5.85  | 10500 | 0.1060          | 0.8620    | 0.8939 | 0.8777 | 0.9750   |
| 0.0379        | 6.12  | 11000 | 0.1031          | 0.8662    | 0.8968 | 0.8812 | 0.9762   |
| 0.038         | 6.4   | 11500 | 0.0992          | 0.8738    | 0.9018 | 0.8876 | 0.9773   |
| 0.0387        | 6.68  | 12000 | 0.1036          | 0.8753    | 0.8969 | 0.8860 | 0.9760   |
| 0.0397        | 6.96  | 12500 | 0.1003          | 0.8722    | 0.9039 | 0.8878 | 0.9773   |
| 0.0279        | 7.24  | 13000 | 0.1068          | 0.8758    | 0.9033 | 0.8893 | 0.9769   |
| 0.0341        | 7.52  | 13500 | 0.0999          | 0.8823    | 0.9054 | 0.8937 | 0.9779   |
| 0.0344        | 7.8   | 14000 | 0.1075          | 0.8679    | 0.9050 | 0.8861 | 0.9757   |
| 0.0278        | 8.07  | 14500 | 0.1009          | 0.8803    | 0.9071 | 0.8935 | 0.9780   |
| 0.028         | 8.35  | 15000 | 0.0998          | 0.8829    | 0.9074 | 0.8950 | 0.9785   |
| 0.0281        | 8.63  | 15500 | 0.0996          | 0.8863    | 0.9098 | 0.8979 | 0.9786   |
| 0.0278        | 8.91  | 16000 | 0.1015          | 0.8836    | 0.9093 | 0.8963 | 0.9779   |
| 0.0262        | 9.19  | 16500 | 0.0997          | 0.8876    | 0.9091 | 0.8982 | 0.9788   |
| 0.0224        | 9.47  | 17000 | 0.0993          | 0.8812    | 0.9097 | 0.8952 | 0.9785   |
| 0.0231        | 9.74  | 17500 | 0.1010          | 0.8859    | 0.9081 | 0.8969 | 0.9788   |
| 0.0257        | 10.02 | 18000 | 0.0985          | 0.8858    | 0.9091 | 0.8973 | 0.9790   |
| 0.0225        | 10.3  | 18500 | 0.0999          | 0.8838    | 0.9096 | 0.8965 | 0.9787   |
| 0.0188        | 10.58 | 19000 | 0.0998          | 0.8880    | 0.9096 | 0.8987 | 0.9787   |
| 0.0237        | 10.86 | 19500 | 0.0990          | 0.8903    | 0.9113 | 0.9007 | 0.9790   |
| 0.0256        | 11.14 | 20000 | 0.0997          | 0.8886    | 0.9114 | 0.8998 | 0.9789   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- 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_v4.2", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8886114578998474, "name": "Precision"}, {"type": "recall", "value": 0.9113671930573339, "name": "Recall"}, {"type": "f1", "value": 0.8998454839162804, "name": "F1"}, {"type": "accuracy", "value": 0.9788903598507642, "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