---
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
datasets:
- ajgt_twitter_ar
metrics:
- accuracy
model-index:
- name: Testmeee
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: ajgt_twitter_ar
      type: ajgt_twitter_ar
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.95
---

<!-- 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. -->

# Testmeee

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the ajgt_twitter_ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3318
- Accuracy: 0.95

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4258        | 1.11  | 50   | 0.2875          | 0.88     |
| 0.1848        | 2.22  | 100  | 0.2274          | 0.93     |
| 0.1117        | 3.33  | 150  | 0.2743          | 0.9      |
| 0.0598        | 4.44  | 200  | 0.2292          | 0.94     |
| 0.0354        | 5.56  | 250  | 0.2714          | 0.95     |
| 0.0319        | 6.67  | 300  | 0.2870          | 0.95     |
| 0.0195        | 7.78  | 350  | 0.3029          | 0.95     |
| 0.0136        | 8.89  | 400  | 0.3097          | 0.95     |
| 0.0078        | 10.0  | 450  | 0.3197          | 0.95     |
| 0.0088        | 11.11 | 500  | 0.3227          | 0.95     |
| 0.0057        | 12.22 | 550  | 0.3263          | 0.95     |
| 0.0058        | 13.33 | 600  | 0.3283          | 0.95     |
| 0.0051        | 14.44 | 650  | 0.3318          | 0.95     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1