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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-passport
results: []
datasets:
- EphronM/Annotated_passport_images
language:
- en
pipeline_tag: token-classification
---
<!-- 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. -->
# layoutlmv3-finetuned-passport
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co./microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0655
- Precision: 0.9735
- Recall: 0.9847
- F1: 0.9790
- Accuracy: 0.9892
## 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: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:--------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 3.4483 | 100 | 0.6286 | 0.7930 | 0.7778 | 0.7853 | 0.8898 |
| No log | 6.8966 | 200 | 0.1945 | 0.9423 | 0.9387 | 0.9405 | 0.9719 |
| No log | 10.3448 | 300 | 0.0832 | 0.9730 | 0.9655 | 0.9692 | 0.9870 |
| No log | 13.7931 | 400 | 0.0558 | 0.9660 | 0.9808 | 0.9734 | 0.9870 |
| 0.398 | 17.2414 | 500 | 0.0524 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.398 | 20.6897 | 600 | 0.0462 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.398 | 24.1379 | 700 | 0.0543 | 0.9660 | 0.9808 | 0.9734 | 0.9870 |
| 0.398 | 27.5862 | 800 | 0.0463 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.398 | 31.0345 | 900 | 0.0569 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0139 | 34.4828 | 1000 | 0.0729 | 0.9515 | 0.9770 | 0.9641 | 0.9849 |
| 0.0139 | 37.9310 | 1100 | 0.0656 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0139 | 41.3793 | 1200 | 0.0609 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0139 | 44.8276 | 1300 | 0.0525 | 0.9732 | 0.9732 | 0.9732 | 0.9892 |
| 0.0139 | 48.2759 | 1400 | 0.0735 | 0.9515 | 0.9770 | 0.9641 | 0.9849 |
| 0.0072 | 51.7241 | 1500 | 0.0491 | 0.9547 | 0.9693 | 0.9620 | 0.9870 |
| 0.0072 | 55.1724 | 1600 | 0.0416 | 0.9773 | 0.9885 | 0.9829 | 0.9914 |
| 0.0072 | 58.6207 | 1700 | 0.0472 | 0.9773 | 0.9885 | 0.9829 | 0.9914 |
| 0.0072 | 62.0690 | 1800 | 0.0543 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0072 | 65.5172 | 1900 | 0.0619 | 0.9662 | 0.9847 | 0.9753 | 0.9892 |
| 0.0029 | 68.9655 | 2000 | 0.0670 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0029 | 72.4138 | 2100 | 0.0770 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0029 | 75.8621 | 2200 | 0.0700 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0029 | 79.3103 | 2300 | 0.0655 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0029 | 82.7586 | 2400 | 0.0684 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0012 | 86.2069 | 2500 | 0.0700 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0012 | 89.6552 | 2600 | 0.0696 | 0.9624 | 0.9808 | 0.9715 | 0.9870 |
| 0.0012 | 93.1034 | 2700 | 0.0619 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0012 | 96.5517 | 2800 | 0.0630 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0012 | 100.0 | 2900 | 0.0703 | 0.9733 | 0.9770 | 0.9751 | 0.9892 |
| 0.0009 | 103.4483 | 3000 | 0.0655 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0009 | 106.8966 | 3100 | 0.0653 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0009 | 110.3448 | 3200 | 0.0657 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0009 | 113.7931 | 3300 | 0.0660 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0009 | 117.2414 | 3400 | 0.0655 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0008 | 120.6897 | 3500 | 0.0663 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0008 | 124.1379 | 3600 | 0.0663 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0008 | 127.5862 | 3700 | 0.0666 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0008 | 131.0345 | 3800 | 0.0648 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0008 | 134.4828 | 3900 | 0.0660 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
| 0.0009 | 137.9310 | 4000 | 0.0660 | 0.9735 | 0.9847 | 0.9790 | 0.9892 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |