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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task7_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_grammar_task7_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: 0.5050
- Qwk: 0.6844
- Mse: 0.4943
## 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 | 1.0262 | 0.2825 | 1.0304 |
| No log | 0.6667 | 4 | 0.6994 | 0.6208 | 0.7254 |
| No log | 1.0 | 6 | 0.8144 | 0.4225 | 0.8374 |
| No log | 1.3333 | 8 | 0.6492 | 0.5810 | 0.6643 |
| No log | 1.6667 | 10 | 0.6577 | 0.4 | 0.6679 |
| No log | 2.0 | 12 | 0.5578 | 0.5957 | 0.5665 |
| No log | 2.3333 | 14 | 0.5481 | 0.6030 | 0.5532 |
| No log | 2.6667 | 16 | 0.4901 | 0.6290 | 0.4927 |
| No log | 3.0 | 18 | 0.4569 | 0.6780 | 0.4570 |
| No log | 3.3333 | 20 | 0.4974 | 0.6780 | 0.4927 |
| No log | 3.6667 | 22 | 0.5556 | 0.5326 | 0.5459 |
| No log | 4.0 | 24 | 0.5207 | 0.6370 | 0.5092 |
| No log | 4.3333 | 26 | 0.5155 | 0.6370 | 0.5024 |
| No log | 4.6667 | 28 | 0.5426 | 0.6370 | 0.5277 |
| No log | 5.0 | 30 | 0.5586 | 0.6416 | 0.5432 |
| No log | 5.3333 | 32 | 0.5285 | 0.6844 | 0.5150 |
| No log | 5.6667 | 34 | 0.4857 | 0.6844 | 0.4750 |
| No log | 6.0 | 36 | 0.4315 | 0.6780 | 0.4244 |
| No log | 6.3333 | 38 | 0.4483 | 0.6780 | 0.4406 |
| No log | 6.6667 | 40 | 0.5122 | 0.6844 | 0.5019 |
| No log | 7.0 | 42 | 0.5586 | 0.6283 | 0.5467 |
| No log | 7.3333 | 44 | 0.5142 | 0.6844 | 0.5032 |
| No log | 7.6667 | 46 | 0.4644 | 0.6844 | 0.4552 |
| No log | 8.0 | 48 | 0.4307 | 0.6780 | 0.4234 |
| No log | 8.3333 | 50 | 0.4377 | 0.6780 | 0.4300 |
| No log | 8.6667 | 52 | 0.4662 | 0.6780 | 0.4571 |
| No log | 9.0 | 54 | 0.4977 | 0.6844 | 0.4873 |
| No log | 9.3333 | 56 | 0.5069 | 0.6844 | 0.4961 |
| No log | 9.6667 | 58 | 0.5095 | 0.6844 | 0.4985 |
| No log | 10.0 | 60 | 0.5050 | 0.6844 | 0.4943 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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