---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Output_LayoutLMv3_v5
  results: []
datasets:
- Noureddinesa/LayoutLmv3_v1
---

<!-- 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. -->

# Output_LayoutLMv3_v5

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3054
- Precision: 0.8505
- Recall: 0.8273
- F1: 0.8387
- Accuracy: 0.9723

## 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-06
- train_batch_size: 3
- weight_decay = 0.1 (Regularization)
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.38  | 100  | 0.2910          | 0.7636    | 0.7636 | 0.7636 | 0.9637   |
| No log        | 4.76  | 200  | 0.2822          | 0.8318    | 0.8091 | 0.8203 | 0.9706   |
| No log        | 7.14  | 300  | 0.2942          | 0.8148    | 0.8    | 0.8073 | 0.9689   |
| No log        | 9.52  | 400  | 0.2821          | 0.7909    | 0.7909 | 0.7909 | 0.9671   |
| 0.0005        | 11.9  | 500  | 0.2896          | 0.7909    | 0.7909 | 0.7909 | 0.9671   |
| 0.0005        | 14.29 | 600  | 0.2914          | 0.8241    | 0.8091 | 0.8165 | 0.9706   |
| 0.0005        | 16.67 | 700  | 0.2912          | 0.8095    | 0.7727 | 0.7907 | 0.9689   |
| 0.0005        | 19.05 | 800  | 0.2578          | 0.8241    | 0.8091 | 0.8165 | 0.9706   |
| 0.0005        | 21.43 | 900  | 0.2830          | 0.8241    | 0.8091 | 0.8165 | 0.9706   |
| 0.0005        | 23.81 | 1000 | 0.2878          | 0.8411    | 0.8182 | 0.8295 | 0.9723   |
| 0.0005        | 26.19 | 1100 | 0.3151          | 0.8113    | 0.7818 | 0.7963 | 0.9689   |
| 0.0005        | 28.57 | 1200 | 0.3142          | 0.7706    | 0.7636 | 0.7671 | 0.9637   |
| 0.0005        | 30.95 | 1300 | 0.2972          | 0.8273    | 0.8273 | 0.8273 | 0.9723   |
| 0.0005        | 33.33 | 1400 | 0.2866          | 0.8148    | 0.8    | 0.8073 | 0.9706   |
| 0.0004        | 35.71 | 1500 | 0.2737          | 0.8288    | 0.8364 | 0.8326 | 0.9723   |
| 0.0004        | 38.1  | 1600 | 0.2653          | 0.8532    | 0.8455 | 0.8493 | 0.9740   |
| 0.0004        | 40.48 | 1700 | 0.2740          | 0.8108    | 0.8182 | 0.8145 | 0.9706   |
| 0.0004        | 42.86 | 1800 | 0.2861          | 0.8198    | 0.8273 | 0.8235 | 0.9706   |
| 0.0004        | 45.24 | 1900 | 0.2904          | 0.7788    | 0.8    | 0.7892 | 0.9671   |
| 0.0004        | 47.62 | 2000 | 0.2899          | 0.7788    | 0.8    | 0.7892 | 0.9671   |
| 0.0004        | 50.0  | 2100 | 0.2957          | 0.8108    | 0.8182 | 0.8145 | 0.9689   |
| 0.0004        | 52.38 | 2200 | 0.2962          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0004        | 54.76 | 2300 | 0.2962          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0004        | 57.14 | 2400 | 0.3057          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0002        | 59.52 | 2500 | 0.3070          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0002        | 61.9  | 2600 | 0.3050          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0002        | 64.29 | 2700 | 0.3050          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0002        | 66.67 | 2800 | 0.3052          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0002        | 69.05 | 2900 | 0.3052          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |
| 0.0           | 71.43 | 3000 | 0.3054          | 0.8505    | 0.8273 | 0.8387 | 0.9723   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3