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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task1_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_mechanics_task1_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: 0.5507
- Qwk: 0.4324
- Mse: 0.5505
## 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 | 4.9042 | 0.0 | 4.9234 |
| No log | 0.6667 | 4 | 2.0020 | -0.0299 | 2.0282 |
| No log | 1.0 | 6 | 1.2914 | 0.0769 | 1.3136 |
| No log | 1.3333 | 8 | 1.0020 | 0.0500 | 1.0184 |
| No log | 1.6667 | 10 | 0.7738 | 0.125 | 0.7839 |
| No log | 2.0 | 12 | 0.8249 | 0.2105 | 0.8327 |
| No log | 2.3333 | 14 | 1.0118 | 0.0851 | 1.0228 |
| No log | 2.6667 | 16 | 0.7586 | 0.1905 | 0.7651 |
| No log | 3.0 | 18 | 0.4977 | 0.375 | 0.5025 |
| No log | 3.3333 | 20 | 0.5065 | 0.3429 | 0.5107 |
| No log | 3.6667 | 22 | 0.5186 | 0.4118 | 0.5205 |
| No log | 4.0 | 24 | 0.7202 | 0.2564 | 0.7199 |
| No log | 4.3333 | 26 | 0.6120 | 0.3889 | 0.6080 |
| No log | 4.6667 | 28 | 0.5684 | 0.3784 | 0.5637 |
| No log | 5.0 | 30 | 0.5531 | 0.3889 | 0.5482 |
| No log | 5.3333 | 32 | 0.6399 | 0.3784 | 0.6320 |
| No log | 5.6667 | 34 | 0.8218 | 0.2632 | 0.8129 |
| No log | 6.0 | 36 | 0.8057 | 0.2632 | 0.7976 |
| No log | 6.3333 | 38 | 0.6262 | 0.3784 | 0.6183 |
| No log | 6.6667 | 40 | 0.6028 | 0.3889 | 0.5950 |
| No log | 7.0 | 42 | 0.6011 | 0.3889 | 0.5943 |
| No log | 7.3333 | 44 | 0.6488 | 0.3158 | 0.6438 |
| No log | 7.6667 | 46 | 0.5939 | 0.3158 | 0.5907 |
| No log | 8.0 | 48 | 0.5456 | 0.4324 | 0.5440 |
| No log | 8.3333 | 50 | 0.5191 | 0.4324 | 0.5183 |
| No log | 8.6667 | 52 | 0.4890 | 0.4324 | 0.4889 |
| No log | 9.0 | 54 | 0.4994 | 0.4324 | 0.4996 |
| No log | 9.3333 | 56 | 0.5265 | 0.4324 | 0.5267 |
| No log | 9.6667 | 58 | 0.5469 | 0.4324 | 0.5468 |
| No log | 10.0 | 60 | 0.5507 | 0.4324 | 0.5505 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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