---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task5_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_mechanics_task5_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: 0.6569
- Qwk: 0.7179
- Mse: 0.6569

## 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    | 1.9122          | 0.0290 | 1.9122 |
| No log        | 0.6667 | 4    | 0.8359          | 0.0    | 0.8359 |
| No log        | 1.0    | 6    | 0.5865          | 0.3478 | 0.5865 |
| No log        | 1.3333 | 8    | 0.5525          | 0.1739 | 0.5525 |
| No log        | 1.6667 | 10   | 0.5082          | 0.25   | 0.5082 |
| No log        | 2.0    | 12   | 0.5342          | 0.3636 | 0.5342 |
| No log        | 2.3333 | 14   | 0.5194          | 0.3478 | 0.5194 |
| No log        | 2.6667 | 16   | 0.5004          | 0.5714 | 0.5004 |
| No log        | 3.0    | 18   | 0.5279          | 0.4848 | 0.5279 |
| No log        | 3.3333 | 20   | 0.5491          | 0.4848 | 0.5491 |
| No log        | 3.6667 | 22   | 0.6345          | 0.6154 | 0.6345 |
| No log        | 4.0    | 24   | 0.7154          | 0.6111 | 0.7154 |
| No log        | 4.3333 | 26   | 0.8157          | 0.5882 | 0.8157 |
| No log        | 4.6667 | 28   | 0.8595          | 0.6667 | 0.8595 |
| No log        | 5.0    | 30   | 0.7144          | 0.6842 | 0.7144 |
| No log        | 5.3333 | 32   | 0.6153          | 0.6    | 0.6153 |
| No log        | 5.6667 | 34   | 0.6974          | 0.6154 | 0.6974 |
| No log        | 6.0    | 36   | 0.7895          | 0.7    | 0.7895 |
| No log        | 6.3333 | 38   | 0.8393          | 0.6667 | 0.8393 |
| No log        | 6.6667 | 40   | 0.8578          | 0.6667 | 0.8578 |
| No log        | 7.0    | 42   | 0.8027          | 0.6667 | 0.8027 |
| No log        | 7.3333 | 44   | 0.7182          | 0.6667 | 0.7182 |
| No log        | 7.6667 | 46   | 0.6647          | 0.6842 | 0.6647 |
| No log        | 8.0    | 48   | 0.6573          | 0.6    | 0.6573 |
| No log        | 8.3333 | 50   | 0.6541          | 0.6842 | 0.6541 |
| No log        | 8.6667 | 52   | 0.6499          | 0.6842 | 0.6499 |
| No log        | 9.0    | 54   | 0.6477          | 0.7179 | 0.6477 |
| No log        | 9.3333 | 56   | 0.6501          | 0.7179 | 0.6501 |
| No log        | 9.6667 | 58   | 0.6545          | 0.7179 | 0.6545 |
| No log        | 10.0   | 60   | 0.6569          | 0.7179 | 0.6569 |


### Framework versions

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