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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_task2_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_baseline_development_task2_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: 0.5447
- Qwk: 0.4714
- Mse: 0.5518
## 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 | 3.5280 | -0.0028 | 3.6293 |
| No log | 0.6667 | 4 | 1.1366 | 0.0251 | 1.1880 |
| No log | 1.0 | 6 | 0.4107 | 0.0 | 0.4259 |
| No log | 1.3333 | 8 | 0.4662 | 0.1765 | 0.4494 |
| No log | 1.6667 | 10 | 0.3079 | 0.2075 | 0.3114 |
| No log | 2.0 | 12 | 0.2932 | 0.4101 | 0.2962 |
| No log | 2.3333 | 14 | 0.3202 | 0.1525 | 0.3155 |
| No log | 2.6667 | 16 | 0.4604 | 0.2410 | 0.4445 |
| No log | 3.0 | 18 | 0.3972 | 0.1765 | 0.3866 |
| No log | 3.3333 | 20 | 0.2887 | 0.1356 | 0.2966 |
| No log | 3.6667 | 22 | 0.3203 | 0.1907 | 0.3343 |
| No log | 4.0 | 24 | 0.3286 | 0.3453 | 0.3381 |
| No log | 4.3333 | 26 | 0.4544 | 0.1674 | 0.4506 |
| No log | 4.6667 | 28 | 0.5203 | 0.1674 | 0.5108 |
| No log | 5.0 | 30 | 0.4560 | 0.4453 | 0.4535 |
| No log | 5.3333 | 32 | 0.4023 | 0.4457 | 0.4083 |
| No log | 5.6667 | 34 | 0.3835 | 0.3453 | 0.3956 |
| No log | 6.0 | 36 | 0.4165 | 0.4231 | 0.4249 |
| No log | 6.3333 | 38 | 0.5295 | 0.4152 | 0.5286 |
| No log | 6.6667 | 40 | 0.6129 | 0.2759 | 0.6063 |
| No log | 7.0 | 42 | 0.6169 | 0.2759 | 0.6109 |
| No log | 7.3333 | 44 | 0.5387 | 0.3971 | 0.5393 |
| No log | 7.6667 | 46 | 0.4830 | 0.3913 | 0.4895 |
| No log | 8.0 | 48 | 0.4890 | 0.3695 | 0.4962 |
| No log | 8.3333 | 50 | 0.5286 | 0.4714 | 0.5334 |
| No log | 8.6667 | 52 | 0.5656 | 0.3971 | 0.5690 |
| No log | 9.0 | 54 | 0.5673 | 0.4714 | 0.5716 |
| No log | 9.3333 | 56 | 0.5533 | 0.4714 | 0.5593 |
| No log | 9.6667 | 58 | 0.5477 | 0.4714 | 0.5545 |
| No log | 10.0 | 60 | 0.5447 | 0.4714 | 0.5518 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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