---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLM_2
  results: []
---

<!-- 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. -->

# LayoutLM_2

This model is a fine-tuned version of [BadreddineHug/LayoutLM_1](https://huggingface.co/BadreddineHug/LayoutLM_1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4785
- Precision: 0.6599
- Recall: 0.7638
- F1: 0.7080
- Accuracy: 0.9097

## 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: 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: 1500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 3.7   | 100  | 0.4266          | 0.6597    | 0.7480 | 0.7011 | 0.9110   |
| No log        | 7.41  | 200  | 0.4415          | 0.6575    | 0.7559 | 0.7033 | 0.9084   |
| No log        | 11.11 | 300  | 0.4478          | 0.6575    | 0.7559 | 0.7033 | 0.9084   |
| No log        | 14.81 | 400  | 0.4481          | 0.6690    | 0.7638 | 0.7132 | 0.9123   |
| 0.0237        | 18.52 | 500  | 0.4551          | 0.6644    | 0.7638 | 0.7106 | 0.9097   |
| 0.0237        | 22.22 | 600  | 0.4542          | 0.6736    | 0.7638 | 0.7159 | 0.9097   |
| 0.0237        | 25.93 | 700  | 0.4536          | 0.6783    | 0.7638 | 0.7185 | 0.9123   |
| 0.0237        | 29.63 | 800  | 0.4662          | 0.6644    | 0.7638 | 0.7106 | 0.9097   |
| 0.0237        | 33.33 | 900  | 0.4716          | 0.6486    | 0.7559 | 0.6982 | 0.9071   |
| 0.0146        | 37.04 | 1000 | 0.4644          | 0.6577    | 0.7717 | 0.7101 | 0.9097   |
| 0.0146        | 40.74 | 1100 | 0.4732          | 0.6599    | 0.7638 | 0.7080 | 0.9097   |
| 0.0146        | 44.44 | 1200 | 0.4727          | 0.6667    | 0.7717 | 0.7153 | 0.9110   |
| 0.0146        | 48.15 | 1300 | 0.4774          | 0.6531    | 0.7559 | 0.7007 | 0.9097   |
| 0.0146        | 51.85 | 1400 | 0.4780          | 0.6599    | 0.7638 | 0.7080 | 0.9097   |
| 0.0128        | 55.56 | 1500 | 0.4785          | 0.6599    | 0.7638 | 0.7080 | 0.9097   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3