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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_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_mechanics_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: 0.3250
- Qwk: 0.7258
- Mse: 0.3234
## 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 | 0.9603 | 0.2687 | 0.9651 |
| No log | 0.6667 | 4 | 0.6926 | 0.5364 | 0.7202 |
| No log | 1.0 | 6 | 0.7727 | 0.6067 | 0.8086 |
| No log | 1.3333 | 8 | 0.7221 | 0.3538 | 0.7310 |
| No log | 1.6667 | 10 | 0.6375 | 0.4368 | 0.6487 |
| No log | 2.0 | 12 | 0.5211 | 0.6263 | 0.5378 |
| No log | 2.3333 | 14 | 0.4993 | 0.5911 | 0.5125 |
| No log | 2.6667 | 16 | 0.5624 | 0.6433 | 0.5686 |
| No log | 3.0 | 18 | 0.5828 | 0.6023 | 0.5851 |
| No log | 3.3333 | 20 | 0.4962 | 0.6576 | 0.4985 |
| No log | 3.6667 | 22 | 0.4100 | 0.6702 | 0.4135 |
| No log | 4.0 | 24 | 0.4169 | 0.6702 | 0.4169 |
| No log | 4.3333 | 26 | 0.4947 | 0.6509 | 0.4883 |
| No log | 4.6667 | 28 | 0.6006 | 0.5556 | 0.5893 |
| No log | 5.0 | 30 | 0.5615 | 0.6121 | 0.5504 |
| No log | 5.3333 | 32 | 0.4063 | 0.6702 | 0.4018 |
| No log | 5.6667 | 34 | 0.3483 | 0.7083 | 0.3470 |
| No log | 6.0 | 36 | 0.3490 | 0.7258 | 0.3465 |
| No log | 6.3333 | 38 | 0.3721 | 0.7258 | 0.3681 |
| No log | 6.6667 | 40 | 0.3827 | 0.7337 | 0.3782 |
| No log | 7.0 | 42 | 0.4201 | 0.6757 | 0.4135 |
| No log | 7.3333 | 44 | 0.4186 | 0.6757 | 0.4120 |
| No log | 7.6667 | 46 | 0.3821 | 0.7337 | 0.3775 |
| No log | 8.0 | 48 | 0.3398 | 0.7258 | 0.3377 |
| No log | 8.3333 | 50 | 0.3148 | 0.7258 | 0.3139 |
| No log | 8.6667 | 52 | 0.3098 | 0.7258 | 0.3091 |
| No log | 9.0 | 54 | 0.3110 | 0.7258 | 0.3101 |
| No log | 9.3333 | 56 | 0.3160 | 0.7258 | 0.3149 |
| No log | 9.6667 | 58 | 0.3224 | 0.7258 | 0.3209 |
| No log | 10.0 | 60 | 0.3250 | 0.7258 | 0.3234 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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