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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task1_fold0
  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_task1_fold0

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: 0.9563
- Qwk: 0.3128
- Mse: 0.9563

## 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: 64
- eval_batch_size: 64
- 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        | 0.1333 | 2    | 4.7632          | 0.0048 | 4.7632 |
| No log        | 0.2667 | 4    | 2.1783          | 0.0291 | 2.1783 |
| No log        | 0.4    | 6    | 1.1081          | 0.1198 | 1.1081 |
| No log        | 0.5333 | 8    | 1.2015          | 0.1712 | 1.2015 |
| No log        | 0.6667 | 10   | 1.9526          | 0.1246 | 1.9526 |
| No log        | 0.8    | 12   | 1.0676          | 0.2290 | 1.0676 |
| No log        | 0.9333 | 14   | 0.5840          | 0.4151 | 0.5840 |
| No log        | 1.0667 | 16   | 0.5753          | 0.4082 | 0.5753 |
| No log        | 1.2    | 18   | 0.8160          | 0.2285 | 0.8160 |
| No log        | 1.3333 | 20   | 1.0681          | 0.2071 | 1.0681 |
| No log        | 1.4667 | 22   | 0.9546          | 0.2910 | 0.9546 |
| No log        | 1.6    | 24   | 0.8621          | 0.3677 | 0.8621 |
| No log        | 1.7333 | 26   | 0.9054          | 0.3700 | 0.9054 |
| No log        | 1.8667 | 28   | 0.9001          | 0.3161 | 0.9001 |
| No log        | 2.0    | 30   | 0.7765          | 0.3323 | 0.7765 |
| No log        | 2.1333 | 32   | 0.8465          | 0.2482 | 0.8465 |
| No log        | 2.2667 | 34   | 0.7701          | 0.2998 | 0.7701 |
| No log        | 2.4    | 36   | 0.6622          | 0.3947 | 0.6622 |
| No log        | 2.5333 | 38   | 0.8242          | 0.3282 | 0.8242 |
| No log        | 2.6667 | 40   | 1.1963          | 0.2592 | 1.1963 |
| No log        | 2.8    | 42   | 1.0937          | 0.2903 | 1.0937 |
| No log        | 2.9333 | 44   | 0.7877          | 0.3934 | 0.7877 |
| No log        | 3.0667 | 46   | 0.5972          | 0.4479 | 0.5972 |
| No log        | 3.2    | 48   | 0.6227          | 0.4269 | 0.6227 |
| No log        | 3.3333 | 50   | 0.8396          | 0.3376 | 0.8396 |
| No log        | 3.4667 | 52   | 1.0463          | 0.2697 | 1.0463 |
| No log        | 3.6    | 54   | 0.8738          | 0.3001 | 0.8738 |
| No log        | 3.7333 | 56   | 0.6019          | 0.4289 | 0.6019 |
| No log        | 3.8667 | 58   | 0.5198          | 0.4722 | 0.5198 |
| No log        | 4.0    | 60   | 0.5541          | 0.4554 | 0.5541 |
| No log        | 4.1333 | 62   | 0.7597          | 0.3733 | 0.7597 |
| No log        | 4.2667 | 64   | 0.9356          | 0.3432 | 0.9356 |
| No log        | 4.4    | 66   | 0.8464          | 0.3610 | 0.8464 |
| No log        | 4.5333 | 68   | 0.7096          | 0.3687 | 0.7096 |
| No log        | 4.6667 | 70   | 0.7102          | 0.3574 | 0.7102 |
| No log        | 4.8    | 72   | 0.7078          | 0.3669 | 0.7078 |
| No log        | 4.9333 | 74   | 0.8143          | 0.3480 | 0.8143 |
| No log        | 5.0667 | 76   | 0.9307          | 0.3211 | 0.9307 |
| No log        | 5.2    | 78   | 0.9263          | 0.3242 | 0.9263 |
| No log        | 5.3333 | 80   | 0.7661          | 0.3610 | 0.7661 |
| No log        | 5.4667 | 82   | 0.6978          | 0.3853 | 0.6978 |
| No log        | 5.6    | 84   | 0.8151          | 0.3739 | 0.8151 |
| No log        | 5.7333 | 86   | 0.8609          | 0.3869 | 0.8609 |
| No log        | 5.8667 | 88   | 0.7966          | 0.3804 | 0.7966 |
| No log        | 6.0    | 90   | 0.7527          | 0.3801 | 0.7527 |
| No log        | 6.1333 | 92   | 0.7607          | 0.3861 | 0.7607 |
| No log        | 6.2667 | 94   | 0.8652          | 0.3306 | 0.8652 |
| No log        | 6.4    | 96   | 0.9460          | 0.3135 | 0.9460 |
| No log        | 6.5333 | 98   | 1.0831          | 0.2779 | 1.0831 |
| No log        | 6.6667 | 100  | 1.0697          | 0.2892 | 1.0697 |
| No log        | 6.8    | 102  | 0.9442          | 0.3343 | 0.9442 |
| No log        | 6.9333 | 104  | 1.0589          | 0.2994 | 1.0589 |
| No log        | 7.0667 | 106  | 1.1776          | 0.2674 | 1.1776 |
| No log        | 7.2    | 108  | 1.1644          | 0.2696 | 1.1644 |
| No log        | 7.3333 | 110  | 0.9516          | 0.3314 | 0.9516 |
| No log        | 7.4667 | 112  | 0.8591          | 0.3636 | 0.8591 |
| No log        | 7.6    | 114  | 0.9364          | 0.3335 | 0.9364 |
| No log        | 7.7333 | 116  | 0.9971          | 0.3111 | 0.9971 |
| No log        | 7.8667 | 118  | 0.9728          | 0.3155 | 0.9728 |
| No log        | 8.0    | 120  | 0.8721          | 0.3499 | 0.8721 |
| No log        | 8.1333 | 122  | 0.8160          | 0.3628 | 0.8160 |
| No log        | 8.2667 | 124  | 0.8194          | 0.3688 | 0.8194 |
| No log        | 8.4    | 126  | 0.8317          | 0.3748 | 0.8317 |
| No log        | 8.5333 | 128  | 0.8909          | 0.3437 | 0.8909 |
| No log        | 8.6667 | 130  | 0.9882          | 0.3225 | 0.9882 |
| No log        | 8.8    | 132  | 1.0839          | 0.2850 | 1.0839 |
| No log        | 8.9333 | 134  | 1.1055          | 0.2859 | 1.1055 |
| No log        | 9.0667 | 136  | 1.1389          | 0.2859 | 1.1389 |
| No log        | 9.2    | 138  | 1.1417          | 0.2795 | 1.1417 |
| No log        | 9.3333 | 140  | 1.0801          | 0.2923 | 1.0801 |
| No log        | 9.4667 | 142  | 1.0176          | 0.3061 | 1.0176 |
| No log        | 9.6    | 144  | 0.9751          | 0.3091 | 0.9751 |
| No log        | 9.7333 | 146  | 0.9550          | 0.3128 | 0.9550 |
| No log        | 9.8667 | 148  | 0.9569          | 0.3128 | 0.9569 |
| No log        | 10.0   | 150  | 0.9563          | 0.3128 | 0.9563 |


### Framework versions

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