
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# passive_invoices_v3.9

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: 0.1352
- Precision: 0.8317
- Recall: 0.8657
- F1: 0.8484
- Accuracy: 0.9695

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9367        | 0.44  | 500  | 0.7897          | 0.2273    | 0.1185 | 0.1557 | 0.8028   |
| 0.45          | 0.88  | 1000 | 0.4876          | 0.4853    | 0.4626 | 0.4737 | 0.8720   |
| 0.2628        | 1.31  | 1500 | 0.3497          | 0.6023    | 0.5851 | 0.5936 | 0.9069   |
| 0.1843        | 1.75  | 2000 | 0.3026          | 0.6354    | 0.6541 | 0.6446 | 0.9163   |
| 0.1395        | 2.19  | 2500 | 0.2346          | 0.6927    | 0.7012 | 0.6969 | 0.9346   |
| 0.124         | 2.63  | 3000 | 0.2015          | 0.7406    | 0.7485 | 0.7445 | 0.9469   |
| 0.095         | 3.06  | 3500 | 0.1906          | 0.7499    | 0.7852 | 0.7672 | 0.9513   |
| 0.0837        | 3.5   | 4000 | 0.1762          | 0.7808    | 0.8056 | 0.7930 | 0.9552   |
| 0.0795        | 3.94  | 4500 | 0.1660          | 0.7828    | 0.8204 | 0.8012 | 0.9594   |
| 0.0601        | 4.38  | 5000 | 0.1596          | 0.7916    | 0.8299 | 0.8103 | 0.9607   |
| 0.0693        | 4.82  | 5500 | 0.1511          | 0.8062    | 0.8409 | 0.8232 | 0.9633   |
| 0.0484        | 5.25  | 6000 | 0.1422          | 0.8149    | 0.8480 | 0.8311 | 0.9666   |
| 0.0522        | 5.69  | 6500 | 0.1413          | 0.8165    | 0.8501 | 0.8330 | 0.9661   |
| 0.0437        | 6.13  | 7000 | 0.1414          | 0.8225    | 0.8598 | 0.8407 | 0.9674   |
| 0.0444        | 6.57  | 7500 | 0.1374          | 0.8289    | 0.8643 | 0.8463 | 0.9683   |
| 0.042         | 7.01  | 8000 | 0.1332          | 0.8346    | 0.8640 | 0.8491 | 0.9698   |
| 0.042         | 7.44  | 8500 | 0.1337          | 0.8355    | 0.8685 | 0.8517 | 0.9700   |
| 0.0347        | 7.88  | 9000 | 0.1352          | 0.8317    | 0.8657 | 0.8484 | 0.9695   |


### 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_v3.9", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8316731386121897, "name": "Precision"}, {"type": "recall", "value": 0.8657293497363796, "name": "Recall"}, {"type": "f1", "value": 0.8483595970033583, "name": "F1"}, {"type": "accuracy", "value": 0.9694626101791299, "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