---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
- layoutmlv3
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