---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: AraGPT2-finetuned-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. -->

# AraGPT2-finetuned-fnd

This model is a fine-tuned version of [aubmindlab/aragpt2-mega-detector-long](https://huggingface.co/aubmindlab/aragpt2-mega-detector-long) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5249
- Macro F1: 0.7536
- Accuracy: 0.7626
- Precision: 0.7563
- Recall: 0.7517

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 25
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| 0.588         | 1.0   | 798  | 0.5131          | 0.7235   | 0.7384   | 0.7341    | 0.7197 |
| 0.462         | 2.0   | 1596 | 0.5112          | 0.7408   | 0.7574   | 0.7587    | 0.7357 |
| 0.4034        | 3.0   | 2394 | 0.5249          | 0.7536   | 0.7626   | 0.7563    | 0.7517 |
| 0.3234        | 4.0   | 3192 | 0.5967          | 0.7524   | 0.7585   | 0.7516    | 0.7534 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1