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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_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_development_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: 0.5458
- Qwk: 0.4658
- Mse: 0.5512
## 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 | 5.2478 | -0.0019 | 5.2043 |
| No log | 0.6667 | 4 | 2.1589 | 0.0283 | 2.1601 |
| No log | 1.0 | 6 | 1.4355 | 0.0541 | 1.4399 |
| No log | 1.3333 | 8 | 0.6301 | 0.2222 | 0.6340 |
| No log | 1.6667 | 10 | 0.6183 | 0.1498 | 0.6241 |
| No log | 2.0 | 12 | 1.0561 | 0.0474 | 1.0672 |
| No log | 2.3333 | 14 | 1.4163 | 0.0173 | 1.4254 |
| No log | 2.6667 | 16 | 0.7226 | 0.1868 | 0.7270 |
| No log | 3.0 | 18 | 0.4156 | 0.3931 | 0.4169 |
| No log | 3.3333 | 20 | 0.3843 | 0.3824 | 0.3843 |
| No log | 3.6667 | 22 | 0.4180 | 0.3265 | 0.4208 |
| No log | 4.0 | 24 | 0.6135 | 0.2391 | 0.6210 |
| No log | 4.3333 | 26 | 0.6975 | 0.3265 | 0.7080 |
| No log | 4.6667 | 28 | 0.4353 | 0.3666 | 0.4431 |
| No log | 5.0 | 30 | 0.3291 | 0.5318 | 0.3307 |
| No log | 5.3333 | 32 | 0.3685 | 0.6995 | 0.3686 |
| No log | 5.6667 | 34 | 0.4312 | 0.5092 | 0.4349 |
| No log | 6.0 | 36 | 0.7352 | 0.3824 | 0.7472 |
| No log | 6.3333 | 38 | 0.8022 | 0.3824 | 0.8152 |
| No log | 6.6667 | 40 | 0.6388 | 0.3988 | 0.6477 |
| No log | 7.0 | 42 | 0.5174 | 0.4043 | 0.5223 |
| No log | 7.3333 | 44 | 0.4579 | 0.4988 | 0.4598 |
| No log | 7.6667 | 46 | 0.4255 | 0.6171 | 0.4251 |
| No log | 8.0 | 48 | 0.4172 | 0.6171 | 0.4166 |
| No log | 8.3333 | 50 | 0.4446 | 0.4989 | 0.4459 |
| No log | 8.6667 | 52 | 0.5029 | 0.5155 | 0.5068 |
| No log | 9.0 | 54 | 0.5447 | 0.4658 | 0.5502 |
| No log | 9.3333 | 56 | 0.5508 | 0.4658 | 0.5564 |
| No log | 9.6667 | 58 | 0.5519 | 0.4658 | 0.5575 |
| No log | 10.0 | 60 | 0.5458 | 0.4658 | 0.5512 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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