---
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: 0.0654
- F1: 0.8501
- Roc Auc: 0.9178
- Accuracy: 0.7616

## 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  | 0.1020          | 0.7502 | 0.8274  | 0.6443   |
| No log        | 2.0   | 386  | 0.0759          | 0.8068 | 0.8678  | 0.7114   |
| 0.1069        | 3.0   | 579  | 0.0728          | 0.8240 | 0.8890  | 0.7393   |
| 0.1069        | 4.0   | 772  | 0.0670          | 0.8418 | 0.9112  | 0.7635   |
| 0.1069        | 5.0   | 965  | 0.0654          | 0.8501 | 0.9178  | 0.7616   |
| 0.0318        | 6.0   | 1158 | 0.0669          | 0.8467 | 0.9197  | 0.7579   |
| 0.0318        | 7.0   | 1351 | 0.0686          | 0.8471 | 0.9190  | 0.7672   |
| 0.0141        | 8.0   | 1544 | 0.0705          | 0.8493 | 0.9259  | 0.7561   |
| 0.0141        | 9.0   | 1737 | 0.0732          | 0.8450 | 0.9248  | 0.7486   |


### Framework versions

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