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# passive_invoices_v3.8

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: 0.1456
- Precision: 0.8156
- Recall: 0.8503
- F1: 0.8326
- Accuracy: 0.9656

## 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: 7500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9245        | 0.48  | 500  | 0.7352          | 0.2664    | 0.1571 | 0.1977 | 0.8109   |
| 0.3981        | 0.96  | 1000 | 0.4784          | 0.5309    | 0.4771 | 0.5026 | 0.8823   |
| 0.2447        | 1.45  | 1500 | 0.3460          | 0.6253    | 0.6117 | 0.6185 | 0.9146   |
| 0.1739        | 1.93  | 2000 | 0.2771          | 0.6737    | 0.6674 | 0.6706 | 0.9289   |
| 0.1345        | 2.41  | 2500 | 0.2453          | 0.6857    | 0.7132 | 0.6992 | 0.9334   |
| 0.1196        | 2.89  | 3000 | 0.2141          | 0.7322    | 0.7551 | 0.7435 | 0.9459   |
| 0.0952        | 3.37  | 3500 | 0.1960          | 0.7483    | 0.7830 | 0.7653 | 0.9508   |
| 0.0876        | 3.85  | 4000 | 0.1675          | 0.8002    | 0.8055 | 0.8028 | 0.9594   |
| 0.0711        | 4.34  | 4500 | 0.1644          | 0.7788    | 0.8164 | 0.7971 | 0.9575   |
| 0.0678        | 4.82  | 5000 | 0.1630          | 0.7991    | 0.8192 | 0.8090 | 0.9614   |
| 0.0556        | 5.3   | 5500 | 0.1553          | 0.7951    | 0.8339 | 0.8140 | 0.9609   |
| 0.0599        | 5.78  | 6000 | 0.1532          | 0.8001    | 0.8404 | 0.8198 | 0.9627   |
| 0.0483        | 6.26  | 6500 | 0.1548          | 0.8019    | 0.8431 | 0.8220 | 0.9631   |
| 0.0506        | 6.74  | 7000 | 0.1452          | 0.8131    | 0.8469 | 0.8296 | 0.9658   |
| 0.0438        | 7.23  | 7500 | 0.1456          | 0.8156    | 0.8503 | 0.8326 | 0.9656   |


### 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_v3.8", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8156209987195903, "name": "Precision"}, {"type": "recall", "value": 0.8503051106025934, "name": "Recall"}, {"type": "f1", "value": 0.8326019979460367, "name": "F1"}, {"type": "accuracy", "value": 0.9655738212439243, "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