---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model4_arabertv2_base_T2_WS_A100
  results: []
---

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# Model4_arabertv2_base_T2_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: 0.0694
- F1: 0.8430
- Roc Auc: 0.9128
- Accuracy: 0.7523

## 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     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 193  | 0.0694          | 0.8430 | 0.9128  | 0.7523   |
| No log        | 2.0   | 386  | 0.0713          | 0.8489 | 0.9184  | 0.7598   |
| 0.0183        | 3.0   | 579  | 0.0779          | 0.8377 | 0.9226  | 0.7412   |
| 0.0183        | 4.0   | 772  | 0.0727          | 0.8455 | 0.9181  | 0.7523   |
| 0.0183        | 5.0   | 965  | 0.0749          | 0.8555 | 0.9264  | 0.7672   |


### Framework versions

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