---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_task2_fold0
  results: []
---

<!-- 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. -->

# arabert_baseline_development_task2_fold0

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4592
- Qwk: 0.2794
- Mse: 0.4600

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Qwk     | Mse    |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
| No log        | 0.3333 | 2    | 5.4721          | -0.0129 | 5.4748 |
| No log        | 0.6667 | 4    | 2.5151          | 0.0507  | 2.5239 |
| No log        | 1.0    | 6    | 1.3235          | 0.0123  | 1.3253 |
| No log        | 1.3333 | 8    | 0.6015          | 0.0645  | 0.6018 |
| No log        | 1.6667 | 10   | 0.5523          | 0.1695  | 0.5523 |
| No log        | 2.0    | 12   | 0.6138          | -0.0138 | 0.6123 |
| No log        | 2.3333 | 14   | 0.6765          | 0.0331  | 0.6760 |
| No log        | 2.6667 | 16   | 0.8075          | 0.0645  | 0.8118 |
| No log        | 3.0    | 18   | 1.2170          | 0.0000  | 1.2213 |
| No log        | 3.3333 | 20   | 0.9705          | 0.1348  | 0.9751 |
| No log        | 3.6667 | 22   | 0.5286          | 0.2674  | 0.5292 |
| No log        | 4.0    | 24   | 0.5438          | 0.1600  | 0.5431 |
| No log        | 4.3333 | 26   | 0.5876          | 0.0     | 0.5872 |
| No log        | 4.6667 | 28   | 0.5812          | 0.0     | 0.5809 |
| No log        | 5.0    | 30   | 0.5243          | 0.1600  | 0.5239 |
| No log        | 5.3333 | 32   | 0.4585          | 0.2794  | 0.4579 |
| No log        | 5.6667 | 34   | 0.4400          | 0.2699  | 0.4394 |
| No log        | 6.0    | 36   | 0.5014          | 0.2581  | 0.5003 |
| No log        | 6.3333 | 38   | 0.5619          | 0.1947  | 0.5601 |
| No log        | 6.6667 | 40   | 0.5416          | 0.1947  | 0.5393 |
| No log        | 7.0    | 42   | 0.5359          | 0.1947  | 0.5336 |
| No log        | 7.3333 | 44   | 0.5271          | 0.1947  | 0.5250 |
| No log        | 7.6667 | 46   | 0.4913          | 0.2596  | 0.4901 |
| No log        | 8.0    | 48   | 0.4604          | 0.2674  | 0.4603 |
| No log        | 8.3333 | 50   | 0.4564          | 0.2794  | 0.4567 |
| No log        | 8.6667 | 52   | 0.4600          | 0.2794  | 0.4606 |
| No log        | 9.0    | 54   | 0.4613          | 0.2794  | 0.4620 |
| No log        | 9.3333 | 56   | 0.4606          | 0.2794  | 0.4614 |
| No log        | 9.6667 | 58   | 0.4598          | 0.2794  | 0.4606 |
| No log        | 10.0   | 60   | 0.4592          | 0.2794  | 0.4600 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1