
<!-- 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_v3.7

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: 0.1610
- Precision: 0.7931
- Recall: 0.8332
- F1: 0.8127
- Accuracy: 0.9613

## 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: 7000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9404        | 0.54  | 500  | 0.8597          | 0.2831    | 0.2266 | 0.2517 | 0.7917   |
| 0.3655        | 1.07  | 1000 | 0.4766          | 0.5287    | 0.4630 | 0.4937 | 0.8832   |
| 0.2272        | 1.61  | 1500 | 0.3522          | 0.6272    | 0.5935 | 0.6099 | 0.9087   |
| 0.1695        | 2.14  | 2000 | 0.2882          | 0.6667    | 0.6524 | 0.6595 | 0.9253   |
| 0.1247        | 2.68  | 2500 | 0.2446          | 0.7052    | 0.7248 | 0.7149 | 0.9373   |
| 0.1051        | 3.21  | 3000 | 0.2153          | 0.7287    | 0.7513 | 0.7398 | 0.9439   |
| 0.0911        | 3.75  | 3500 | 0.2013          | 0.7439    | 0.7792 | 0.7611 | 0.9471   |
| 0.0809        | 4.28  | 4000 | 0.1890          | 0.7592    | 0.7983 | 0.7783 | 0.9534   |
| 0.0705        | 4.82  | 4500 | 0.1859          | 0.7567    | 0.8155 | 0.7850 | 0.9538   |
| 0.0603        | 5.35  | 5000 | 0.1719          | 0.7852    | 0.8078 | 0.7963 | 0.9584   |
| 0.0599        | 5.89  | 5500 | 0.1666          | 0.7869    | 0.8213 | 0.8037 | 0.9598   |
| 0.052         | 6.42  | 6000 | 0.1642          | 0.7881    | 0.8318 | 0.8094 | 0.9605   |
| 0.0497        | 6.96  | 6500 | 0.1595          | 0.7913    | 0.8290 | 0.8097 | 0.9614   |
| 0.0455        | 7.49  | 7000 | 0.1610          | 0.7931    | 0.8332 | 0.8127 | 0.9613   |


### 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_v3.7", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.7931339977851606, "name": "Precision"}, {"type": "recall", "value": 0.8331782224290367, "name": "Recall"}, {"type": "f1", "value": 0.8126631113128333, "name": "F1"}, {"type": "accuracy", "value": 0.9612806863007928, "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