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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_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_baseline_development_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: 0.5902
- Qwk: 0.5813
- Mse: 0.5907
## 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 | 4.3908 | -0.0120 | 4.3758 |
| No log | 0.6667 | 4 | 1.6600 | 0.1250 | 1.6454 |
| No log | 1.0 | 6 | 0.7866 | 0.1857 | 0.7857 |
| No log | 1.3333 | 8 | 0.8027 | 0.3213 | 0.8042 |
| No log | 1.6667 | 10 | 0.7663 | 0.4436 | 0.7681 |
| No log | 2.0 | 12 | 0.6285 | 0.5382 | 0.6319 |
| No log | 2.3333 | 14 | 0.5709 | 0.5522 | 0.5784 |
| No log | 2.6667 | 16 | 0.6087 | 0.5551 | 0.6118 |
| No log | 3.0 | 18 | 0.6828 | 0.5551 | 0.6824 |
| No log | 3.3333 | 20 | 0.7735 | 0.5415 | 0.7740 |
| No log | 3.6667 | 22 | 0.6982 | 0.5682 | 0.6989 |
| No log | 4.0 | 24 | 0.7101 | 0.5682 | 0.7116 |
| No log | 4.3333 | 26 | 0.6932 | 0.5682 | 0.6950 |
| No log | 4.6667 | 28 | 0.6914 | 0.5682 | 0.6938 |
| No log | 5.0 | 30 | 0.6162 | 0.5477 | 0.6186 |
| No log | 5.3333 | 32 | 0.5655 | 0.5477 | 0.5678 |
| No log | 5.6667 | 34 | 0.5450 | 0.5445 | 0.5471 |
| No log | 6.0 | 36 | 0.5674 | 0.5477 | 0.5701 |
| No log | 6.3333 | 38 | 0.6194 | 0.5314 | 0.6234 |
| No log | 6.6667 | 40 | 0.5904 | 0.5477 | 0.5926 |
| No log | 7.0 | 42 | 0.5761 | 0.5445 | 0.5768 |
| No log | 7.3333 | 44 | 0.5947 | 0.5813 | 0.5951 |
| No log | 7.6667 | 46 | 0.6094 | 0.5825 | 0.6096 |
| No log | 8.0 | 48 | 0.6288 | 0.5995 | 0.6294 |
| No log | 8.3333 | 50 | 0.6317 | 0.5269 | 0.6325 |
| No log | 8.6667 | 52 | 0.6245 | 0.5995 | 0.6251 |
| No log | 9.0 | 54 | 0.6067 | 0.5825 | 0.6071 |
| No log | 9.3333 | 56 | 0.5975 | 0.5813 | 0.5979 |
| No log | 9.6667 | 58 | 0.5916 | 0.5813 | 0.5921 |
| No log | 10.0 | 60 | 0.5902 | 0.5813 | 0.5907 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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