---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: AraElectra-finetuned-CrossVal-fnd
  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. -->

# AraElectra-finetuned-CrossVal-fnd

This model is a fine-tuned version of [aubmindlab/araelectra-base-discriminator](https://huggingface.co/aubmindlab/araelectra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5165
- Macro F1: 0.8697
- Accuracy: 0.8744
- Precision: 0.8714
- Recall: 0.8682

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 123
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| 0.3422        | 1.0   | 798  | 0.3336          | 0.8589   | 0.8615   | 0.8563    | 0.8652 |
| 0.216         | 2.0   | 1597 | 0.3460          | 0.8658   | 0.8714   | 0.8705    | 0.8624 |
| 0.1504        | 3.0   | 2395 | 0.5448          | 0.8485   | 0.8568   | 0.8609    | 0.8420 |
| 0.0914        | 4.0   | 3192 | 0.5165          | 0.8697   | 0.8744   | 0.8714    | 0.8682 |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2