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# passive_invoices_v4.01

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: 0.1000
- Precision: 0.8893
- Recall: 0.9180
- F1: 0.9034
- Accuracy: 0.9788

## 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: 18000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0559        | 0.3   | 500   | 0.8477          | 0.1734    | 0.0776 | 0.1072 | 0.7804   |
| 0.5846        | 0.61  | 1000  | 0.5455          | 0.4304    | 0.3548 | 0.3889 | 0.8587   |
| 0.3827        | 0.91  | 1500  | 0.3947          | 0.5436    | 0.5355 | 0.5395 | 0.8916   |
| 0.2532        | 1.22  | 2000  | 0.2986          | 0.6411    | 0.6074 | 0.6238 | 0.9184   |
| 0.2067        | 1.52  | 2500  | 0.2529          | 0.6749    | 0.6923 | 0.6835 | 0.9295   |
| 0.1651        | 1.83  | 3000  | 0.2062          | 0.7290    | 0.7252 | 0.7271 | 0.9413   |
| 0.1332        | 2.13  | 3500  | 0.1804          | 0.7429    | 0.7683 | 0.7554 | 0.9483   |
| 0.1168        | 2.44  | 4000  | 0.1652          | 0.7564    | 0.7987 | 0.7770 | 0.9550   |
| 0.0967        | 2.74  | 4500  | 0.1688          | 0.7818    | 0.7930 | 0.7874 | 0.9556   |
| 0.0978        | 3.05  | 5000  | 0.1371          | 0.8069    | 0.8280 | 0.8173 | 0.9639   |
| 0.0722        | 3.35  | 5500  | 0.1272          | 0.8202    | 0.8454 | 0.8326 | 0.9671   |
| 0.068         | 3.66  | 6000  | 0.1320          | 0.8107    | 0.8519 | 0.8308 | 0.9657   |
| 0.0741        | 3.96  | 6500  | 0.1288          | 0.8154    | 0.8551 | 0.8348 | 0.9658   |
| 0.0602        | 4.27  | 7000  | 0.1241          | 0.8343    | 0.8675 | 0.8506 | 0.9689   |
| 0.0565        | 4.57  | 7500  | 0.1069          | 0.8490    | 0.8808 | 0.8646 | 0.9733   |
| 0.0538        | 4.88  | 8000  | 0.1018          | 0.8575    | 0.8940 | 0.8754 | 0.9752   |
| 0.0474        | 5.18  | 8500  | 0.1176          | 0.8467    | 0.8924 | 0.8690 | 0.9721   |
| 0.0489        | 5.49  | 9000  | 0.1036          | 0.8625    | 0.8879 | 0.8750 | 0.9739   |
| 0.0452        | 5.79  | 9500  | 0.1084          | 0.8644    | 0.8947 | 0.8793 | 0.9750   |
| 0.0366        | 6.1   | 10000 | 0.1012          | 0.8747    | 0.8946 | 0.8845 | 0.9766   |
| 0.0394        | 6.4   | 10500 | 0.1132          | 0.8639    | 0.9014 | 0.8822 | 0.9746   |
| 0.0321        | 6.71  | 11000 | 0.0994          | 0.8766    | 0.9038 | 0.8900 | 0.9775   |
| 0.0434        | 7.01  | 11500 | 0.1044          | 0.8755    | 0.9022 | 0.8886 | 0.9763   |
| 0.033         | 7.32  | 12000 | 0.1056          | 0.8770    | 0.9032 | 0.8899 | 0.9761   |
| 0.0344        | 7.62  | 12500 | 0.0998          | 0.8835    | 0.9049 | 0.8941 | 0.9777   |
| 0.0321        | 7.93  | 13000 | 0.0983          | 0.8813    | 0.9113 | 0.8961 | 0.9777   |
| 0.0301        | 8.23  | 13500 | 0.0999          | 0.8737    | 0.9117 | 0.8923 | 0.9773   |
| 0.0258        | 8.54  | 14000 | 0.1008          | 0.8827    | 0.9137 | 0.8979 | 0.9778   |
| 0.0312        | 8.84  | 14500 | 0.0964          | 0.8796    | 0.9157 | 0.8973 | 0.9789   |
| 0.0235        | 9.15  | 15000 | 0.0943          | 0.8916    | 0.9133 | 0.9024 | 0.9792   |
| 0.0253        | 9.45  | 15500 | 0.1006          | 0.8895    | 0.9164 | 0.9028 | 0.9786   |
| 0.0237        | 9.76  | 16000 | 0.0965          | 0.8902    | 0.9175 | 0.9037 | 0.9789   |
| 0.0278        | 10.06 | 16500 | 0.1009          | 0.8888    | 0.9205 | 0.9044 | 0.9783   |
| 0.021         | 10.37 | 17000 | 0.1010          | 0.8919    | 0.9179 | 0.9047 | 0.9787   |
| 0.0235        | 10.67 | 17500 | 0.1002          | 0.8930    | 0.9172 | 0.9050 | 0.9789   |
| 0.0244        | 10.98 | 18000 | 0.1000          | 0.8893    | 0.9180 | 0.9034 | 0.9788   |


### 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_v4.01", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.889346725040776, "name": "Precision"}, {"type": "recall", "value": 0.9179514442672337, "name": "Recall"}, {"type": "f1", "value": 0.9034227163723567, "name": "F1"}, {"type": "accuracy", "value": 0.9788244695019089, "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