---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_fold4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_vocabulary_task6_fold4

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: 0.9017
- Qwk: 0.7854
- Mse: 0.9017

## 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: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Qwk    | Mse    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.0323 | 2    | 3.2692          | 0.0190 | 3.2692 |
| No log        | 0.0645 | 4    | 2.2061          | 0.1047 | 2.2061 |
| No log        | 0.0968 | 6    | 1.4731          | 0.2850 | 1.4731 |
| No log        | 0.1290 | 8    | 1.4939          | 0.3745 | 1.4939 |
| No log        | 0.1613 | 10   | 1.4323          | 0.5432 | 1.4323 |
| No log        | 0.1935 | 12   | 1.1650          | 0.5658 | 1.1650 |
| No log        | 0.2258 | 14   | 1.2574          | 0.6380 | 1.2574 |
| No log        | 0.2581 | 16   | 1.5764          | 0.6494 | 1.5764 |
| No log        | 0.2903 | 18   | 1.5312          | 0.6719 | 1.5312 |
| No log        | 0.3226 | 20   | 1.0794          | 0.7533 | 1.0794 |
| No log        | 0.3548 | 22   | 0.7210          | 0.7812 | 0.7210 |
| No log        | 0.3871 | 24   | 0.6686          | 0.7619 | 0.6686 |
| No log        | 0.4194 | 26   | 0.7673          | 0.8035 | 0.7673 |
| No log        | 0.4516 | 28   | 0.9964          | 0.7709 | 0.9964 |
| No log        | 0.4839 | 30   | 1.0717          | 0.7698 | 1.0717 |
| No log        | 0.5161 | 32   | 1.0503          | 0.7731 | 1.0503 |
| No log        | 0.5484 | 34   | 0.9077          | 0.7987 | 0.9077 |
| No log        | 0.5806 | 36   | 0.7545          | 0.8028 | 0.7545 |
| No log        | 0.6129 | 38   | 0.7792          | 0.8013 | 0.7792 |
| No log        | 0.6452 | 40   | 0.7860          | 0.7981 | 0.7860 |
| No log        | 0.6774 | 42   | 0.7492          | 0.7988 | 0.7492 |
| No log        | 0.7097 | 44   | 0.7053          | 0.8126 | 0.7053 |
| No log        | 0.7419 | 46   | 0.7612          | 0.8056 | 0.7612 |
| No log        | 0.7742 | 48   | 0.8008          | 0.7851 | 0.8008 |
| No log        | 0.8065 | 50   | 0.8570          | 0.7727 | 0.8570 |
| No log        | 0.8387 | 52   | 0.8902          | 0.7709 | 0.8902 |
| No log        | 0.8710 | 54   | 0.9179          | 0.7780 | 0.9179 |
| No log        | 0.9032 | 56   | 0.9185          | 0.7758 | 0.9185 |
| No log        | 0.9355 | 58   | 0.9139          | 0.7854 | 0.9139 |
| No log        | 0.9677 | 60   | 0.9045          | 0.7854 | 0.9045 |
| No log        | 1.0    | 62   | 0.9017          | 0.7854 | 0.9017 |


### Framework versions

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