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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task5_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_vocabulary_task5_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: 0.8715
- Qwk: 0.6491
- Mse: 0.8715
## 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 | 2.2168 | 0.1714 | 2.2168 |
| No log | 0.6667 | 4 | 2.0041 | 0.0 | 2.0041 |
| No log | 1.0 | 6 | 1.8058 | 0.0 | 1.8058 |
| No log | 1.3333 | 8 | 1.6307 | 0.0 | 1.6307 |
| No log | 1.6667 | 10 | 1.5228 | 0.1055 | 1.5228 |
| No log | 2.0 | 12 | 1.4956 | 0.1325 | 1.4956 |
| No log | 2.3333 | 14 | 1.4414 | 0.1842 | 1.4414 |
| No log | 2.6667 | 16 | 1.3583 | 0.3623 | 1.3583 |
| No log | 3.0 | 18 | 1.2822 | 0.4602 | 1.2822 |
| No log | 3.3333 | 20 | 1.2058 | 0.4783 | 1.2058 |
| No log | 3.6667 | 22 | 1.1388 | 0.5430 | 1.1388 |
| No log | 4.0 | 24 | 1.0848 | 0.5778 | 1.0848 |
| No log | 4.3333 | 26 | 1.0520 | 0.5161 | 1.0520 |
| No log | 4.6667 | 28 | 1.0213 | 0.5161 | 1.0213 |
| No log | 5.0 | 30 | 0.9946 | 0.4866 | 0.9946 |
| No log | 5.3333 | 32 | 0.9759 | 0.5368 | 0.9759 |
| No log | 5.6667 | 34 | 0.9511 | 0.5368 | 0.9511 |
| No log | 6.0 | 36 | 0.9260 | 0.5662 | 0.9260 |
| No log | 6.3333 | 38 | 0.9142 | 0.5662 | 0.9142 |
| No log | 6.6667 | 40 | 0.8995 | 0.5662 | 0.8995 |
| No log | 7.0 | 42 | 0.9024 | 0.5940 | 0.9024 |
| No log | 7.3333 | 44 | 0.9102 | 0.5368 | 0.9102 |
| No log | 7.6667 | 46 | 0.9036 | 0.6258 | 0.9036 |
| No log | 8.0 | 48 | 0.8943 | 0.6304 | 0.8943 |
| No log | 8.3333 | 50 | 0.8872 | 0.6042 | 0.8872 |
| No log | 8.6667 | 52 | 0.8828 | 0.6042 | 0.8828 |
| No log | 9.0 | 54 | 0.8785 | 0.6491 | 0.8785 |
| No log | 9.3333 | 56 | 0.8747 | 0.6491 | 0.8747 |
| No log | 9.6667 | 58 | 0.8725 | 0.6491 | 0.8725 |
| No log | 10.0 | 60 | 0.8715 | 0.6491 | 0.8715 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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