---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_task7_fold1
  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_task7_fold1

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: 0.4808
- Qwk: 0.6800
- Mse: 0.4658

## 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    | 1.1708          | 0.1401 | 1.1442 |
| No log        | 0.6667 | 4    | 0.6797          | 0.4733 | 0.6689 |
| No log        | 1.0    | 6    | 0.8726          | 0.35   | 0.8601 |
| No log        | 1.3333 | 8    | 0.6330          | 0.4407 | 0.6258 |
| No log        | 1.6667 | 10   | 0.4729          | 0.7317 | 0.4705 |
| No log        | 2.0    | 12   | 0.4560          | 0.7727 | 0.4525 |
| No log        | 2.3333 | 14   | 0.4835          | 0.5161 | 0.4748 |
| No log        | 2.6667 | 16   | 0.6021          | 0.4361 | 0.5871 |
| No log        | 3.0    | 18   | 0.5490          | 0.5036 | 0.5343 |
| No log        | 3.3333 | 20   | 0.4924          | 0.5772 | 0.4790 |
| No log        | 3.6667 | 22   | 0.4506          | 0.6531 | 0.4384 |
| No log        | 4.0    | 24   | 0.4816          | 0.6710 | 0.4656 |
| No log        | 4.3333 | 26   | 0.5471          | 0.5818 | 0.5260 |
| No log        | 4.6667 | 28   | 0.5883          | 0.4286 | 0.5652 |
| No log        | 5.0    | 30   | 0.5645          | 0.4971 | 0.5423 |
| No log        | 5.3333 | 32   | 0.4974          | 0.5823 | 0.4779 |
| No log        | 5.6667 | 34   | 0.4623          | 0.6369 | 0.4450 |
| No log        | 6.0    | 36   | 0.4534          | 0.6980 | 0.4376 |
| No log        | 6.3333 | 38   | 0.4859          | 0.6369 | 0.4690 |
| No log        | 6.6667 | 40   | 0.5046          | 0.5823 | 0.4879 |
| No log        | 7.0    | 42   | 0.4998          | 0.6225 | 0.4840 |
| No log        | 7.3333 | 44   | 0.4877          | 0.6434 | 0.4725 |
| No log        | 7.6667 | 46   | 0.4853          | 0.6434 | 0.4702 |
| No log        | 8.0    | 48   | 0.4746          | 0.6434 | 0.4601 |
| No log        | 8.3333 | 50   | 0.4732          | 0.6434 | 0.4588 |
| No log        | 8.6667 | 52   | 0.4819          | 0.6434 | 0.4671 |
| No log        | 9.0    | 54   | 0.4873          | 0.6225 | 0.4722 |
| No log        | 9.3333 | 56   | 0.4833          | 0.6800 | 0.4684 |
| No log        | 9.6667 | 58   | 0.4812          | 0.6800 | 0.4662 |
| No log        | 10.0   | 60   | 0.4808          | 0.6800 | 0.4658 |


### Framework versions

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