---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task2_fold1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_baseline_mechanics_task2_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: 0.8879
- Qwk: 0.5758
- Mse: 0.8784

## 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    | 3.5975          | -0.0382 | 3.6807 |
| No log        | 0.6667 | 4    | 1.4679          | 0.1796  | 1.5092 |
| No log        | 1.0    | 6    | 1.0780          | 0.0     | 1.0882 |
| No log        | 1.3333 | 8    | 1.2308          | 0.1695  | 1.2193 |
| No log        | 1.6667 | 10   | 1.2253          | 0.1695  | 1.2102 |
| No log        | 2.0    | 12   | 0.8911          | 0.2451  | 0.8886 |
| No log        | 2.3333 | 14   | 0.8137          | 0.3099  | 0.8139 |
| No log        | 2.6667 | 16   | 0.8083          | 0.3099  | 0.8044 |
| No log        | 3.0    | 18   | 0.9159          | 0.5185  | 0.9080 |
| No log        | 3.3333 | 20   | 1.0465          | 0.4556  | 1.0353 |
| No log        | 3.6667 | 22   | 0.9742          | 0.4731  | 0.9635 |
| No log        | 4.0    | 24   | 0.7724          | 0.3897  | 0.7631 |
| No log        | 4.3333 | 26   | 0.7534          | 0.3636  | 0.7425 |
| No log        | 4.6667 | 28   | 0.7201          | 0.3636  | 0.7079 |
| No log        | 5.0    | 30   | 0.8574          | 0.5586  | 0.8468 |
| No log        | 5.3333 | 32   | 0.9644          | 0.5130  | 0.9546 |
| No log        | 5.6667 | 34   | 0.8585          | 0.608   | 0.8487 |
| No log        | 6.0    | 36   | 0.7248          | 0.5405  | 0.7112 |
| No log        | 6.3333 | 38   | 0.7385          | 0.5405  | 0.7257 |
| No log        | 6.6667 | 40   | 0.8072          | 0.5758  | 0.7967 |
| No log        | 7.0    | 42   | 0.9702          | 0.6513  | 0.9631 |
| No log        | 7.3333 | 44   | 0.9882          | 0.6513  | 0.9815 |
| No log        | 7.6667 | 46   | 0.9719          | 0.6513  | 0.9651 |
| No log        | 8.0    | 48   | 0.9498          | 0.6513  | 0.9425 |
| No log        | 8.3333 | 50   | 0.9073          | 0.6513  | 0.8988 |
| No log        | 8.6667 | 52   | 0.8907          | 0.5758  | 0.8816 |
| No log        | 9.0    | 54   | 0.8763          | 0.5758  | 0.8665 |
| No log        | 9.3333 | 56   | 0.8701          | 0.5758  | 0.8602 |
| No log        | 9.6667 | 58   | 0.8850          | 0.5758  | 0.8754 |
| No log        | 10.0   | 60   | 0.8879          | 0.5758  | 0.8784 |


### Framework versions

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