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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_fold1
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_task6_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: 0.6146
- Qwk: 0.4250
- Mse: 0.6146
## 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 | 0.0328 | 2 | 3.4679 | 0.0168 | 3.4679 |
| No log | 0.0656 | 4 | 1.6537 | 0.0514 | 1.6537 |
| No log | 0.0984 | 6 | 1.1313 | 0.1099 | 1.1313 |
| No log | 0.1311 | 8 | 0.9535 | 0.1805 | 0.9535 |
| No log | 0.1639 | 10 | 1.0794 | 0.3174 | 1.0794 |
| No log | 0.1967 | 12 | 0.6168 | 0.4395 | 0.6168 |
| No log | 0.2295 | 14 | 0.6033 | 0.4645 | 0.6033 |
| No log | 0.2623 | 16 | 0.6737 | 0.4499 | 0.6737 |
| No log | 0.2951 | 18 | 1.0668 | 0.3641 | 1.0668 |
| No log | 0.3279 | 20 | 1.3034 | 0.3203 | 1.3034 |
| No log | 0.3607 | 22 | 1.0248 | 0.3778 | 1.0248 |
| No log | 0.3934 | 24 | 0.6797 | 0.4447 | 0.6797 |
| No log | 0.4262 | 26 | 0.6365 | 0.4647 | 0.6365 |
| No log | 0.4590 | 28 | 0.7543 | 0.4079 | 0.7543 |
| No log | 0.4918 | 30 | 1.0103 | 0.3524 | 1.0103 |
| No log | 0.5246 | 32 | 0.8599 | 0.3860 | 0.8599 |
| No log | 0.5574 | 34 | 0.6772 | 0.4252 | 0.6772 |
| No log | 0.5902 | 36 | 0.5781 | 0.4282 | 0.5781 |
| No log | 0.6230 | 38 | 0.5748 | 0.4282 | 0.5748 |
| No log | 0.6557 | 40 | 0.6074 | 0.4195 | 0.6074 |
| No log | 0.6885 | 42 | 0.6402 | 0.3992 | 0.6402 |
| No log | 0.7213 | 44 | 0.7139 | 0.3932 | 0.7139 |
| No log | 0.7541 | 46 | 0.7877 | 0.3858 | 0.7877 |
| No log | 0.7869 | 48 | 0.7654 | 0.3896 | 0.7654 |
| No log | 0.8197 | 50 | 0.6949 | 0.4032 | 0.6949 |
| No log | 0.8525 | 52 | 0.6439 | 0.4209 | 0.6439 |
| No log | 0.8852 | 54 | 0.6372 | 0.4216 | 0.6372 |
| No log | 0.9180 | 56 | 0.6231 | 0.4191 | 0.6231 |
| No log | 0.9508 | 58 | 0.6184 | 0.4250 | 0.6184 |
| No log | 0.9836 | 60 | 0.6146 | 0.4250 | 0.6146 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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