---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Model4_arabertv2_base_T1_WS_A100_2nd
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T1-ArabertTv2-Bas-WS-A100/runs/tr0iviop)
# Model4_arabertv2_base_T1_WS_A100_2nd

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: 0.1510
- F1 Micro: 0.8382
- F1 Macro: 0.7689
- Roc Auc: 0.8969
- Accuracy: 0.8024

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------:|:--------:|
| 0.1687        | 1.0   | 507  | 0.1510          | 0.8382   | 0.7689   | 0.8969  | 0.8024   |
| 0.0892        | 2.0   | 1014 | 0.1634          | 0.8337   | 0.7637   | 0.8925  | 0.7982   |
| 0.0539        | 3.0   | 1521 | 0.1884          | 0.8318   | 0.7630   | 0.8968  | 0.7996   |
| 0.0331        | 4.0   | 2028 | 0.2067          | 0.8419   | 0.7700   | 0.9041  | 0.8108   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3