---
base_model: aubmindlab/bert-large-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Araberv2_large
  results: []
---

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# Araberv2_large

This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3745
- F1: 0.5436
- F1 Macro: 0.1187
- Roc Auc: 0.7222
- Accuracy: 0.5531

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F1 Macro | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|:--------:|
| 0.3412        | 1.0   | 507  | 0.3815          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3775        | 2.0   | 1014 | 0.3745          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3768        | 3.0   | 1521 | 0.3914          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3764        | 4.0   | 2028 | 0.3745          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3714        | 5.0   | 2535 | 0.3870          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3697        | 6.0   | 3042 | 0.3835          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3688        | 7.0   | 3549 | 0.4026          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3654        | 8.0   | 4056 | 0.4771          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3