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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task5_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_baseline_relevance_task5_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: 0.3678
- Qwk: 0.2949
- Mse: 0.3678
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log | 0.3333 | 2 | 0.4684 | 0.1304 | 0.4684 |
| No log | 0.6667 | 4 | 0.4252 | 0.0 | 0.4252 |
| No log | 1.0 | 6 | 0.4179 | 0.0 | 0.4179 |
| No log | 1.3333 | 8 | 0.4231 | 0.0 | 0.4231 |
| No log | 1.6667 | 10 | 0.4130 | 0.0 | 0.4130 |
| No log | 2.0 | 12 | 0.4098 | 0.0 | 0.4098 |
| No log | 2.3333 | 14 | 0.4153 | 0.0551 | 0.4153 |
| No log | 2.6667 | 16 | 0.4026 | 0.0551 | 0.4026 |
| No log | 3.0 | 18 | 0.3622 | 0.1837 | 0.3622 |
| No log | 3.3333 | 20 | 0.3561 | 0.1837 | 0.3561 |
| No log | 3.6667 | 22 | 0.3628 | 0.1837 | 0.3628 |
| No log | 4.0 | 24 | 0.3773 | 0.1837 | 0.3773 |
| No log | 4.3333 | 26 | 0.3744 | 0.1837 | 0.3744 |
| No log | 4.6667 | 28 | 0.3673 | 0.1837 | 0.3673 |
| No log | 5.0 | 30 | 0.3744 | 0.1837 | 0.3744 |
| No log | 5.3333 | 32 | 0.3730 | 0.1837 | 0.3730 |
| No log | 5.6667 | 34 | 0.3589 | 0.1333 | 0.3589 |
| No log | 6.0 | 36 | 0.3503 | 0.3464 | 0.3503 |
| No log | 6.3333 | 38 | 0.3556 | 0.2949 | 0.3556 |
| No log | 6.6667 | 40 | 0.3713 | 0.2949 | 0.3713 |
| No log | 7.0 | 42 | 0.3743 | 0.2949 | 0.3743 |
| No log | 7.3333 | 44 | 0.3742 | 0.2949 | 0.3742 |
| No log | 7.6667 | 46 | 0.3719 | 0.2949 | 0.3719 |
| No log | 8.0 | 48 | 0.3699 | 0.2949 | 0.3699 |
| No log | 8.3333 | 50 | 0.3712 | 0.2949 | 0.3712 |
| No log | 8.6667 | 52 | 0.3661 | 0.2949 | 0.3661 |
| No log | 9.0 | 54 | 0.3649 | 0.2157 | 0.3649 |
| No log | 9.3333 | 56 | 0.3664 | 0.1333 | 0.3664 |
| No log | 9.6667 | 58 | 0.3674 | 0.2157 | 0.3674 |
| No log | 10.0 | 60 | 0.3678 | 0.2949 | 0.3678 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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