---
base_model: aubmindlab/bert-large-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model5_Araberv2_large_WS_A100
  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. -->

# Model5_Araberv2_large_WS_A100

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: 0.1496
- F1: 0.8471
- F1 Macro: 0.7728
- Roc Auc: 0.9049
- Accuracy: 0.8198

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|:--------:|
| 0.3258        | 1.0   | 507  | 0.3872          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3014        | 2.0   | 1014 | 0.1685          | 0.8238 | 0.7461   | 0.8929  | 0.7842   |
| 0.1736        | 3.0   | 1521 | 0.1496          | 0.8471 | 0.7728   | 0.9049  | 0.8198   |
| 0.35          | 4.0   | 2028 | 0.3958          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3696        | 5.0   | 2535 | 0.3936          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.3685        | 6.0   | 3042 | 0.4065          | 0.5436 | 0.1187   | 0.7222  | 0.5531   |
| 0.366         | 7.0   | 3549 | 0.4728          | 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