---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model4_arabertv2_base_T1_WS_A100
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Model4_arabertv2_base_T1_WS_A100

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1569
- F1: 0.8398
- F1 Macro: 0.7742
- Roc Auc: 0.9021
- Accuracy: 0.8073

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|:--------:|
| 0.0988        | 1.0   | 507  | 0.1569          | 0.8398 | 0.7742   | 0.9021  | 0.8073   |
| 0.056         | 2.0   | 1014 | 0.2023          | 0.8267 | 0.7610   | 0.8938  | 0.7912   |
| 0.0358        | 3.0   | 1521 | 0.1959          | 0.8529 | 0.7889   | 0.9089  | 0.8275   |
| 0.0204        | 4.0   | 2028 | 0.2132          | 0.8496 | 0.7971   | 0.9079  | 0.8226   |
| 0.0157        | 5.0   | 2535 | 0.2288          | 0.8434 | 0.7789   | 0.9047  | 0.8163   |


### Framework versions

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