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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task7_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_task7_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: 0.1556
- Qwk: 0.3529
- Mse: 0.1556
## 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 | 0.3146 | 0.1946 | 0.3146 |
| No log | 0.6667 | 4 | 0.2014 | 0.5139 | 0.2014 |
| No log | 1.0 | 6 | 0.3227 | 0.2282 | 0.3227 |
| No log | 1.3333 | 8 | 0.3751 | 0.2780 | 0.3751 |
| No log | 1.6667 | 10 | 0.1512 | 0.4083 | 0.1512 |
| No log | 2.0 | 12 | 0.1822 | 0.5139 | 0.1822 |
| No log | 2.3333 | 14 | 0.2006 | 0.3836 | 0.2006 |
| No log | 2.6667 | 16 | 0.1882 | 0.1946 | 0.1882 |
| No log | 3.0 | 18 | 0.1835 | 0.1946 | 0.1835 |
| No log | 3.3333 | 20 | 0.1790 | 0.2925 | 0.1790 |
| No log | 3.6667 | 22 | 0.1666 | 0.3365 | 0.1666 |
| No log | 4.0 | 24 | 0.1570 | 0.4012 | 0.1570 |
| No log | 4.3333 | 26 | 0.1650 | 0.5139 | 0.1650 |
| No log | 4.6667 | 28 | 0.1468 | 0.3919 | 0.1468 |
| No log | 5.0 | 30 | 0.1342 | 0.3919 | 0.1342 |
| No log | 5.3333 | 32 | 0.1362 | 0.3289 | 0.1362 |
| No log | 5.6667 | 34 | 0.1387 | 0.3289 | 0.1387 |
| No log | 6.0 | 36 | 0.1474 | 0.3919 | 0.1474 |
| No log | 6.3333 | 38 | 0.1652 | 0.3919 | 0.1652 |
| No log | 6.6667 | 40 | 0.1889 | 0.4483 | 0.1889 |
| No log | 7.0 | 42 | 0.1978 | 0.4483 | 0.1978 |
| No log | 7.3333 | 44 | 0.1910 | 0.4483 | 0.1910 |
| No log | 7.6667 | 46 | 0.1747 | 0.2568 | 0.1747 |
| No log | 8.0 | 48 | 0.1647 | 0.4083 | 0.1647 |
| No log | 8.3333 | 50 | 0.1586 | 0.4083 | 0.1586 |
| No log | 8.6667 | 52 | 0.1552 | 0.3529 | 0.1552 |
| No log | 9.0 | 54 | 0.1544 | 0.3529 | 0.1544 |
| No log | 9.3333 | 56 | 0.1548 | 0.3529 | 0.1548 |
| No log | 9.6667 | 58 | 0.1554 | 0.3529 | 0.1554 |
| No log | 10.0 | 60 | 0.1556 | 0.3529 | 0.1556 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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