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# passive_invoices_v4.02

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: 0.1029
- Precision: 0.8956
- Recall: 0.9174
- F1: 0.9064
- Accuracy: 0.9793

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0818        | 0.3   | 500   | 0.8260          | 0.2184    | 0.1434 | 0.1731 | 0.7870   |
| 0.5547        | 0.61  | 1000  | 0.5544          | 0.4160    | 0.2855 | 0.3386 | 0.8546   |
| 0.3672        | 0.91  | 1500  | 0.4098          | 0.5326    | 0.5207 | 0.5266 | 0.8883   |
| 0.2719        | 1.21  | 2000  | 0.3143          | 0.6281    | 0.6116 | 0.6197 | 0.9149   |
| 0.2007        | 1.51  | 2500  | 0.2432          | 0.6739    | 0.6844 | 0.6791 | 0.9323   |
| 0.1677        | 1.82  | 3000  | 0.2037          | 0.7120    | 0.7380 | 0.7248 | 0.9446   |
| 0.1326        | 2.12  | 3500  | 0.1941          | 0.7384    | 0.7613 | 0.7497 | 0.9490   |
| 0.1114        | 2.42  | 4000  | 0.1611          | 0.7648    | 0.7974 | 0.7808 | 0.9556   |
| 0.0981        | 2.72  | 4500  | 0.1568          | 0.7885    | 0.8182 | 0.8030 | 0.9602   |
| 0.091         | 3.03  | 5000  | 0.1408          | 0.8050    | 0.8251 | 0.8149 | 0.9644   |
| 0.0756        | 3.33  | 5500  | 0.1435          | 0.8256    | 0.8519 | 0.8385 | 0.9653   |
| 0.0696        | 3.63  | 6000  | 0.1283          | 0.8353    | 0.8588 | 0.8469 | 0.9691   |
| 0.0671        | 3.93  | 6500  | 0.1286          | 0.8264    | 0.8604 | 0.8431 | 0.9677   |
| 0.0608        | 4.24  | 7000  | 0.1249          | 0.8475    | 0.8696 | 0.8584 | 0.9707   |
| 0.0497        | 4.54  | 7500  | 0.1209          | 0.8484    | 0.8746 | 0.8613 | 0.9706   |
| 0.0535        | 4.84  | 8000  | 0.1156          | 0.8567    | 0.8827 | 0.8695 | 0.9730   |
| 0.0479        | 5.15  | 8500  | 0.1149          | 0.8498    | 0.8857 | 0.8674 | 0.9728   |
| 0.0437        | 5.45  | 9000  | 0.1073          | 0.8724    | 0.8898 | 0.8810 | 0.9754   |
| 0.0487        | 5.75  | 9500  | 0.1067          | 0.8699    | 0.8991 | 0.8842 | 0.9754   |
| 0.0457        | 6.05  | 10000 | 0.1047          | 0.8725    | 0.8992 | 0.8857 | 0.9762   |
| 0.0364        | 6.36  | 10500 | 0.1118          | 0.8606    | 0.8940 | 0.8770 | 0.9743   |
| 0.0394        | 6.66  | 11000 | 0.1072          | 0.8746    | 0.9010 | 0.8876 | 0.9760   |
| 0.0324        | 6.96  | 11500 | 0.1091          | 0.8789    | 0.9036 | 0.8911 | 0.9765   |
| 0.0268        | 7.26  | 12000 | 0.1081          | 0.8744    | 0.9052 | 0.8896 | 0.9762   |
| 0.0337        | 7.57  | 12500 | 0.1035          | 0.8888    | 0.9109 | 0.8997 | 0.9781   |
| 0.0347        | 7.87  | 13000 | 0.1038          | 0.8893    | 0.9080 | 0.8986 | 0.9780   |
| 0.0249        | 8.17  | 13500 | 0.1061          | 0.8880    | 0.9117 | 0.8997 | 0.9779   |
| 0.0301        | 8.47  | 14000 | 0.1046          | 0.8906    | 0.9150 | 0.9026 | 0.9786   |
| 0.0267        | 8.78  | 14500 | 0.1067          | 0.8876    | 0.9100 | 0.8987 | 0.9779   |
| 0.0289        | 9.08  | 15000 | 0.1053          | 0.8898    | 0.9139 | 0.9017 | 0.9792   |
| 0.0264        | 9.38  | 15500 | 0.1005          | 0.8945    | 0.9146 | 0.9044 | 0.9795   |
| 0.0241        | 9.69  | 16000 | 0.0987          | 0.8975    | 0.9176 | 0.9074 | 0.9799   |
| 0.0237        | 9.99  | 16500 | 0.1059          | 0.8916    | 0.9189 | 0.9050 | 0.9786   |
| 0.0194        | 10.29 | 17000 | 0.1041          | 0.8940    | 0.9187 | 0.9062 | 0.9794   |
| 0.0263        | 10.59 | 17500 | 0.1031          | 0.8959    | 0.9171 | 0.9064 | 0.9792   |
| 0.0239        | 10.9  | 18000 | 0.1029          | 0.8956    | 0.9174 | 0.9064 | 0.9793   |


### 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_v4.02", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.8955582232893158, "name": "Precision"}, {"type": "recall", "value": 0.9174279690794097, "name": "Recall"}, {"type": "f1", "value": 0.906361190662154, "name": "F1"}, {"type": "accuracy", "value": 0.9792617292617293, "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