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# passive_invoices_v3.10.2

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: 0.1192
- Precision: 0.8509
- Recall: 0.8879
- F1: 0.8690
- Accuracy: 0.9753

## 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: 11000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9583        | 0.4   | 500   | 0.7887          | 0.2330    | 0.1166 | 0.1554 | 0.8001   |
| 0.4605        | 0.8   | 1000  | 0.5073          | 0.4524    | 0.3367 | 0.3861 | 0.8669   |
| 0.2871        | 1.2   | 1500  | 0.3518          | 0.6087    | 0.5382 | 0.5713 | 0.9115   |
| 0.2048        | 1.59  | 2000  | 0.2679          | 0.6648    | 0.6615 | 0.6632 | 0.9263   |
| 0.1425        | 1.99  | 2500  | 0.2294          | 0.6963    | 0.6952 | 0.6957 | 0.9360   |
| 0.1194        | 2.39  | 3000  | 0.2010          | 0.7109    | 0.7515 | 0.7306 | 0.9468   |
| 0.102         | 2.79  | 3500  | 0.1720          | 0.7595    | 0.7825 | 0.7708 | 0.9553   |
| 0.0922        | 3.19  | 4000  | 0.1642          | 0.7760    | 0.8011 | 0.7884 | 0.9569   |
| 0.0758        | 3.59  | 4500  | 0.1523          | 0.7771    | 0.8174 | 0.7968 | 0.9602   |
| 0.071         | 3.99  | 5000  | 0.1407          | 0.8065    | 0.8362 | 0.8211 | 0.9644   |
| 0.0566        | 4.39  | 5500  | 0.1396          | 0.8169    | 0.8435 | 0.8300 | 0.9669   |
| 0.0611        | 4.78  | 6000  | 0.1270          | 0.8183    | 0.8525 | 0.8350 | 0.9690   |
| 0.0488        | 5.18  | 6500  | 0.1298          | 0.8309    | 0.8572 | 0.8438 | 0.9705   |
| 0.0449        | 5.58  | 7000  | 0.1289          | 0.8135    | 0.8577 | 0.8350 | 0.9698   |
| 0.0467        | 5.98  | 7500  | 0.1274          | 0.8278    | 0.8697 | 0.8482 | 0.9698   |
| 0.0367        | 6.38  | 8000  | 0.1276          | 0.8309    | 0.8679 | 0.8490 | 0.9709   |
| 0.042         | 6.78  | 8500  | 0.1179          | 0.8431    | 0.8786 | 0.8605 | 0.9736   |
| 0.0333        | 7.18  | 9000  | 0.1206          | 0.8488    | 0.8807 | 0.8644 | 0.9737   |
| 0.0353        | 7.58  | 9500  | 0.1183          | 0.8515    | 0.8802 | 0.8656 | 0.9752   |
| 0.0317        | 7.97  | 10000 | 0.1176          | 0.8504    | 0.8850 | 0.8674 | 0.9754   |
| 0.0294        | 8.37  | 10500 | 0.1184          | 0.8507    | 0.8891 | 0.8695 | 0.9754   |
| 0.0292        | 8.77  | 11000 | 0.1192          | 0.8509    | 0.8879 | 0.8690 | 0.9753   |


### 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_v3.10.2", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8509220517588718, "name": "Precision"}, {"type": "recall", "value": 0.8879366106080206, "name": "Recall"}, {"type": "f1", "value": 0.8690353723193796, "name": "F1"}, {"type": "accuracy", "value": 0.9752972292838251, "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