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# test

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0314
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9933

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 40000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.0381        | 0.13  | 500   | 0.0777          | 0.0       | 0.0    | 0.0 | 0.9745   |
| 0.0669        | 0.26  | 1000  | 0.0545          | 0.0       | 0.0    | 0.0 | 0.9790   |
| 0.0595        | 0.39  | 1500  | 0.0545          | 0.0       | 0.0    | 0.0 | 0.9803   |
| 0.054         | 0.52  | 2000  | 0.0555          | 0.0       | 0.0    | 0.0 | 0.9796   |
| 0.0502        | 0.65  | 2500  | 0.0451          | 0.0       | 0.0    | 0.0 | 0.9828   |
| 0.0474        | 0.78  | 3000  | 0.0486          | 0.0       | 0.0    | 0.0 | 0.9818   |
| 0.0458        | 0.92  | 3500  | 0.0417          | 0.0       | 0.0    | 0.0 | 0.9836   |
| 0.0415        | 1.05  | 4000  | 0.0440          | 0.0       | 0.0    | 0.0 | 0.9827   |
| 0.0372        | 1.18  | 4500  | 0.0432          | 0.0       | 0.0    | 0.0 | 0.9839   |
| 0.0391        | 1.31  | 5000  | 0.0442          | 0.0       | 0.0    | 0.0 | 0.9839   |
| 0.0368        | 1.44  | 5500  | 0.0377          | 0.0       | 0.0    | 0.0 | 0.9856   |
| 0.0388        | 1.57  | 6000  | 0.0417          | 0.0       | 0.0    | 0.0 | 0.9846   |
| 0.0351        | 1.7   | 6500  | 0.0363          | 0.0       | 0.0    | 0.0 | 0.9857   |
| 0.0357        | 1.83  | 7000  | 0.0383          | 0.0       | 0.0    | 0.0 | 0.9858   |
| 0.0336        | 1.96  | 7500  | 0.0371          | 0.0       | 0.0    | 0.0 | 0.9860   |
| 0.0309        | 2.09  | 8000  | 0.0373          | 0.0       | 0.0    | 0.0 | 0.9859   |
| 0.0288        | 2.22  | 8500  | 0.0355          | 0.0       | 0.0    | 0.0 | 0.9870   |
| 0.0288        | 2.35  | 9000  | 0.0359          | 0.0       | 0.0    | 0.0 | 0.9867   |
| 0.0285        | 2.49  | 9500  | 0.0369          | 0.0       | 0.0    | 0.0 | 0.9872   |
| 0.0307        | 2.62  | 10000 | 0.0322          | 0.0       | 0.0    | 0.0 | 0.9880   |
| 0.028         | 2.75  | 10500 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9886   |
| 0.0246        | 2.88  | 11000 | 0.0326          | 0.0       | 0.0    | 0.0 | 0.9881   |
| 0.0267        | 3.01  | 11500 | 0.0346          | 0.0       | 0.0    | 0.0 | 0.9882   |
| 0.022         | 3.14  | 12000 | 0.0316          | 0.0       | 0.0    | 0.0 | 0.9889   |
| 0.0218        | 3.27  | 12500 | 0.0357          | 0.0       | 0.0    | 0.0 | 0.9883   |
| 0.0217        | 3.4   | 13000 | 0.0363          | 0.0       | 0.0    | 0.0 | 0.9883   |
| 0.0208        | 3.53  | 13500 | 0.0340          | 0.0       | 0.0    | 0.0 | 0.9894   |
| 0.0223        | 3.66  | 14000 | 0.0304          | 0.0       | 0.0    | 0.0 | 0.9892   |
| 0.0232        | 3.79  | 14500 | 0.0319          | 0.0       | 0.0    | 0.0 | 0.9894   |
| 0.0229        | 3.92  | 15000 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9901   |
| 0.0192        | 4.06  | 15500 | 0.0310          | 0.0       | 0.0    | 0.0 | 0.9905   |
| 0.0178        | 4.19  | 16000 | 0.0345          | 0.0       | 0.0    | 0.0 | 0.9897   |
| 0.0178        | 4.32  | 16500 | 0.0309          | 0.0       | 0.0    | 0.0 | 0.9902   |
| 0.0173        | 4.45  | 17000 | 0.0328          | 0.0       | 0.0    | 0.0 | 0.9904   |
| 0.0176        | 4.58  | 17500 | 0.0316          | 0.0       | 0.0    | 0.0 | 0.9908   |
| 0.017         | 4.71  | 18000 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9912   |
| 0.0163        | 4.84  | 18500 | 0.0329          | 0.0       | 0.0    | 0.0 | 0.9909   |
| 0.018         | 4.97  | 19000 | 0.0295          | 0.0       | 0.0    | 0.0 | 0.9910   |
| 0.0143        | 5.1   | 19500 | 0.0367          | 0.0       | 0.0    | 0.0 | 0.9903   |
| 0.0144        | 5.23  | 20000 | 0.0317          | 0.0       | 0.0    | 0.0 | 0.9915   |
| 0.0158        | 5.36  | 20500 | 0.0290          | 0.0       | 0.0    | 0.0 | 0.9917   |
| 0.0143        | 5.49  | 21000 | 0.0315          | 0.0       | 0.0    | 0.0 | 0.9917   |
| 0.0137        | 5.63  | 21500 | 0.0310          | 0.0       | 0.0    | 0.0 | 0.9913   |
| 0.0135        | 5.76  | 22000 | 0.0310          | 0.0       | 0.0    | 0.0 | 0.9913   |
| 0.0128        | 5.89  | 22500 | 0.0290          | 0.0       | 0.0    | 0.0 | 0.9917   |
| 0.0132        | 6.02  | 23000 | 0.0314          | 0.0       | 0.0    | 0.0 | 0.9921   |
| 0.0124        | 6.15  | 23500 | 0.0274          | 0.0       | 0.0    | 0.0 | 0.9921   |
| 0.0114        | 6.28  | 24000 | 0.0300          | 0.0       | 0.0    | 0.0 | 0.9921   |
| 0.0111        | 6.41  | 24500 | 0.0291          | 0.0       | 0.0    | 0.0 | 0.9922   |
| 0.0109        | 6.54  | 25000 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9923   |
| 0.0117        | 6.67  | 25500 | 0.0328          | 0.0       | 0.0    | 0.0 | 0.9921   |
| 0.0112        | 6.8   | 26000 | 0.0293          | 0.0       | 0.0    | 0.0 | 0.9924   |
| 0.012         | 6.93  | 26500 | 0.0300          | 0.0       | 0.0    | 0.0 | 0.9924   |
| 0.0102        | 7.06  | 27000 | 0.0330          | 0.0       | 0.0    | 0.0 | 0.9921   |
| 0.0094        | 7.2   | 27500 | 0.0323          | 0.0       | 0.0    | 0.0 | 0.9922   |
| 0.0091        | 7.33  | 28000 | 0.0309          | 0.0       | 0.0    | 0.0 | 0.9924   |
| 0.0087        | 7.46  | 28500 | 0.0331          | 0.0       | 0.0    | 0.0 | 0.9920   |
| 0.0091        | 7.59  | 29000 | 0.0332          | 0.0       | 0.0    | 0.0 | 0.9923   |
| 0.0095        | 7.72  | 29500 | 0.0298          | 0.0       | 0.0    | 0.0 | 0.9925   |
| 0.0083        | 7.85  | 30000 | 0.0303          | 0.0       | 0.0    | 0.0 | 0.9929   |
| 0.0097        | 7.98  | 30500 | 0.0298          | 0.0       | 0.0    | 0.0 | 0.9928   |
| 0.0069        | 8.11  | 31000 | 0.0319          | 0.0       | 0.0    | 0.0 | 0.9926   |
| 0.0086        | 8.24  | 31500 | 0.0314          | 0.0       | 0.0    | 0.0 | 0.9929   |
| 0.0079        | 8.37  | 32000 | 0.0306          | 0.0       | 0.0    | 0.0 | 0.9929   |
| 0.0065        | 8.5   | 32500 | 0.0317          | 0.0       | 0.0    | 0.0 | 0.9926   |
| 0.0072        | 8.63  | 33000 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9927   |
| 0.0082        | 8.77  | 33500 | 0.0306          | 0.0       | 0.0    | 0.0 | 0.9929   |
| 0.0086        | 8.9   | 34000 | 0.0312          | 0.0       | 0.0    | 0.0 | 0.9931   |
| 0.0079        | 9.03  | 34500 | 0.0329          | 0.0       | 0.0    | 0.0 | 0.9929   |
| 0.0061        | 9.16  | 35000 | 0.0326          | 0.0       | 0.0    | 0.0 | 0.9928   |
| 0.0074        | 9.29  | 35500 | 0.0315          | 0.0       | 0.0    | 0.0 | 0.9928   |
| 0.0068        | 9.42  | 36000 | 0.0310          | 0.0       | 0.0    | 0.0 | 0.9931   |
| 0.0059        | 9.55  | 36500 | 0.0318          | 0.0       | 0.0    | 0.0 | 0.9930   |
| 0.0064        | 9.68  | 37000 | 0.0307          | 0.0       | 0.0    | 0.0 | 0.9933   |
| 0.0063        | 9.81  | 37500 | 0.0308          | 0.0       | 0.0    | 0.0 | 0.9930   |
| 0.0062        | 9.94  | 38000 | 0.0311          | 0.0       | 0.0    | 0.0 | 0.9931   |
| 0.0058        | 10.07 | 38500 | 0.0314          | 0.0       | 0.0    | 0.0 | 0.9932   |
| 0.0051        | 10.2  | 39000 | 0.0316          | 0.0       | 0.0    | 0.0 | 0.9933   |
| 0.0065        | 10.33 | 39500 | 0.0315          | 0.0       | 0.0    | 0.0 | 0.9933   |
| 0.0059        | 10.47 | 40000 | 0.0314          | 0.0       | 0.0    | 0.0 | 0.9933   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "microsoft/layoutlmv3-base", "model-index": [{"name": "test", "results": []}]}
transformers tensorboard safetensors layoutlmv3 token-classification generated_from_trainer base_model:microsoft/layoutlmv3-base license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us