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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_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_style_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: 0.5100
- Qwk: 0.6698
- Mse: 0.5053
## 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 | 5.4651 | -0.0419 | 5.4241 |
| No log | 0.6667 | 4 | 2.3074 | 0.1693 | 2.2743 |
| No log | 1.0 | 6 | 1.2115 | 0.1561 | 1.2001 |
| No log | 1.3333 | 8 | 0.9959 | 0.4358 | 0.9923 |
| No log | 1.6667 | 10 | 0.7290 | 0.4921 | 0.7317 |
| No log | 2.0 | 12 | 0.7145 | 0.5587 | 0.7193 |
| No log | 2.3333 | 14 | 0.7329 | 0.5435 | 0.7351 |
| No log | 2.6667 | 16 | 0.7694 | 0.5219 | 0.7660 |
| No log | 3.0 | 18 | 0.9233 | 0.4358 | 0.9210 |
| No log | 3.3333 | 20 | 0.8596 | 0.4516 | 0.8545 |
| No log | 3.6667 | 22 | 0.7445 | 0.5743 | 0.7322 |
| No log | 4.0 | 24 | 0.7760 | 0.4773 | 0.7614 |
| No log | 4.3333 | 26 | 0.6783 | 0.5743 | 0.6684 |
| No log | 4.6667 | 28 | 0.7836 | 0.5152 | 0.7834 |
| No log | 5.0 | 30 | 0.7387 | 0.5188 | 0.7401 |
| No log | 5.3333 | 32 | 0.5679 | 0.5743 | 0.5656 |
| No log | 5.6667 | 34 | 0.5183 | 0.5743 | 0.5136 |
| No log | 6.0 | 36 | 0.5055 | 0.5743 | 0.5017 |
| No log | 6.3333 | 38 | 0.5518 | 0.5188 | 0.5511 |
| No log | 6.6667 | 40 | 0.6558 | 0.5188 | 0.6585 |
| No log | 7.0 | 42 | 0.6773 | 0.6025 | 0.6812 |
| No log | 7.3333 | 44 | 0.6216 | 0.6025 | 0.6242 |
| No log | 7.6667 | 46 | 0.5382 | 0.6698 | 0.5375 |
| No log | 8.0 | 48 | 0.5083 | 0.6698 | 0.5056 |
| No log | 8.3333 | 50 | 0.5045 | 0.6698 | 0.5004 |
| No log | 8.6667 | 52 | 0.5059 | 0.7151 | 0.5009 |
| No log | 9.0 | 54 | 0.5070 | 0.7151 | 0.5018 |
| No log | 9.3333 | 56 | 0.5069 | 0.7151 | 0.5016 |
| No log | 9.6667 | 58 | 0.5086 | 0.7151 | 0.5037 |
| No log | 10.0 | 60 | 0.5100 | 0.6698 | 0.5053 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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