---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task2_fold5
  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_cross_vocabulary_task2_fold5

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: 0.3302
- Qwk: 0.7915
- Mse: 0.3302

## 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        | 0.0351 | 2    | 1.9408          | 0.0725 | 1.9408 |
| No log        | 0.0702 | 4    | 1.1558          | 0.2495 | 1.1558 |
| No log        | 0.1053 | 6    | 0.8278          | 0.5475 | 0.8278 |
| No log        | 0.1404 | 8    | 0.9051          | 0.5890 | 0.9051 |
| No log        | 0.1754 | 10   | 1.0541          | 0.6265 | 1.0541 |
| No log        | 0.2105 | 12   | 0.9617          | 0.6991 | 0.9617 |
| No log        | 0.2456 | 14   | 0.6753          | 0.8007 | 0.6753 |
| No log        | 0.2807 | 16   | 0.4157          | 0.7665 | 0.4157 |
| No log        | 0.3158 | 18   | 0.4162          | 0.7231 | 0.4162 |
| No log        | 0.3509 | 20   | 0.3927          | 0.7223 | 0.3927 |
| No log        | 0.3860 | 22   | 0.3990          | 0.7945 | 0.3990 |
| No log        | 0.4211 | 24   | 0.4409          | 0.8243 | 0.4409 |
| No log        | 0.4561 | 26   | 0.4391          | 0.8320 | 0.4391 |
| No log        | 0.4912 | 28   | 0.3760          | 0.8013 | 0.3760 |
| No log        | 0.5263 | 30   | 0.3677          | 0.7769 | 0.3677 |
| No log        | 0.5614 | 32   | 0.3664          | 0.8062 | 0.3664 |
| No log        | 0.5965 | 34   | 0.3925          | 0.8156 | 0.3925 |
| No log        | 0.6316 | 36   | 0.4350          | 0.8384 | 0.4350 |
| No log        | 0.6667 | 38   | 0.4400          | 0.8249 | 0.4400 |
| No log        | 0.7018 | 40   | 0.4146          | 0.8159 | 0.4146 |
| No log        | 0.7368 | 42   | 0.3750          | 0.8086 | 0.3750 |
| No log        | 0.7719 | 44   | 0.3465          | 0.7933 | 0.3465 |
| No log        | 0.8070 | 46   | 0.3355          | 0.7897 | 0.3355 |
| No log        | 0.8421 | 48   | 0.3314          | 0.7870 | 0.3314 |
| No log        | 0.8772 | 50   | 0.3317          | 0.7828 | 0.3317 |
| No log        | 0.9123 | 52   | 0.3312          | 0.7828 | 0.3312 |
| No log        | 0.9474 | 54   | 0.3303          | 0.7906 | 0.3303 |
| No log        | 0.9825 | 56   | 0.3302          | 0.7915 | 0.3302 |


### Framework versions

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