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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_task7_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_organization_task7_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: 0.4509
- Qwk: 0.6
- Mse: 0.4509
## 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 | 1.2538 | 0.1333 | 1.2538 |
| No log | 0.6667 | 4 | 0.6732 | 0.5116 | 0.6732 |
| No log | 1.0 | 6 | 1.0128 | 0.3810 | 1.0128 |
| No log | 1.3333 | 8 | 0.6424 | 0.5455 | 0.6424 |
| No log | 1.6667 | 10 | 0.6331 | 0.5455 | 0.6331 |
| No log | 2.0 | 12 | 0.6841 | 0.5455 | 0.6841 |
| No log | 2.3333 | 14 | 0.6488 | 0.5306 | 0.6488 |
| No log | 2.6667 | 16 | 0.7438 | 0.5185 | 0.7438 |
| No log | 3.0 | 18 | 1.0106 | 0.3636 | 1.0106 |
| No log | 3.3333 | 20 | 1.0009 | 0.3810 | 1.0009 |
| No log | 3.6667 | 22 | 0.6870 | 0.5098 | 0.6870 |
| No log | 4.0 | 24 | 0.5375 | 0.5106 | 0.5375 |
| No log | 4.3333 | 26 | 0.5197 | 0.55 | 0.5197 |
| No log | 4.6667 | 28 | 0.5082 | 0.5366 | 0.5082 |
| No log | 5.0 | 30 | 0.5130 | 0.5652 | 0.5130 |
| No log | 5.3333 | 32 | 0.5730 | 0.56 | 0.5730 |
| No log | 5.6667 | 34 | 0.5916 | 0.56 | 0.5916 |
| No log | 6.0 | 36 | 0.5065 | 0.5306 | 0.5065 |
| No log | 6.3333 | 38 | 0.4667 | 0.6 | 0.4667 |
| No log | 6.6667 | 40 | 0.4403 | 0.6 | 0.4403 |
| No log | 7.0 | 42 | 0.4374 | 0.6 | 0.4374 |
| No log | 7.3333 | 44 | 0.4427 | 0.6 | 0.4427 |
| No log | 7.6667 | 46 | 0.4590 | 0.6 | 0.4590 |
| No log | 8.0 | 48 | 0.4783 | 0.6275 | 0.4783 |
| No log | 8.3333 | 50 | 0.4751 | 0.6275 | 0.4751 |
| No log | 8.6667 | 52 | 0.4701 | 0.6275 | 0.4701 |
| No log | 9.0 | 54 | 0.4678 | 0.6275 | 0.4678 |
| No log | 9.3333 | 56 | 0.4574 | 0.6275 | 0.4574 |
| No log | 9.6667 | 58 | 0.4535 | 0.6 | 0.4535 |
| No log | 10.0 | 60 | 0.4509 | 0.6 | 0.4509 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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