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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
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