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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_fold6
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_cross_vocabulary_task6_fold6
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: 0.4868
- Qwk: 0.6478
- Mse: 0.4856
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log | 0.0308 | 2 | 2.1344 | 0.0845 | 2.1260 |
| No log | 0.0615 | 4 | 1.0808 | 0.2961 | 1.0693 |
| No log | 0.0923 | 6 | 1.3454 | 0.2890 | 1.3254 |
| No log | 0.1231 | 8 | 0.6739 | 0.5314 | 0.6662 |
| No log | 0.1538 | 10 | 0.5779 | 0.6649 | 0.5736 |
| No log | 0.1846 | 12 | 0.5912 | 0.7569 | 0.5902 |
| No log | 0.2154 | 14 | 0.5775 | 0.7630 | 0.5772 |
| No log | 0.2462 | 16 | 0.5694 | 0.6622 | 0.5684 |
| No log | 0.2769 | 18 | 0.7642 | 0.5844 | 0.7634 |
| No log | 0.3077 | 20 | 1.2490 | 0.4005 | 1.2461 |
| No log | 0.3385 | 22 | 1.2661 | 0.3780 | 1.2624 |
| No log | 0.3692 | 24 | 0.8020 | 0.5334 | 0.8002 |
| No log | 0.4 | 26 | 0.6377 | 0.6083 | 0.6361 |
| No log | 0.4308 | 28 | 0.5794 | 0.6047 | 0.5774 |
| No log | 0.4615 | 30 | 0.5299 | 0.6342 | 0.5280 |
| No log | 0.4923 | 32 | 0.4877 | 0.6511 | 0.4861 |
| No log | 0.5231 | 34 | 0.4827 | 0.6483 | 0.4810 |
| No log | 0.5538 | 36 | 0.4477 | 0.7136 | 0.4467 |
| No log | 0.5846 | 38 | 0.4513 | 0.6644 | 0.4498 |
| No log | 0.6154 | 40 | 0.4864 | 0.6268 | 0.4842 |
| No log | 0.6462 | 42 | 0.5576 | 0.5786 | 0.5544 |
| No log | 0.6769 | 44 | 0.6809 | 0.4995 | 0.6764 |
| No log | 0.7077 | 46 | 0.7399 | 0.4954 | 0.7349 |
| No log | 0.7385 | 48 | 0.6881 | 0.4918 | 0.6838 |
| No log | 0.7692 | 50 | 0.6232 | 0.5309 | 0.6197 |
| No log | 0.8 | 52 | 0.5631 | 0.5592 | 0.5605 |
| No log | 0.8308 | 54 | 0.5054 | 0.6188 | 0.5036 |
| No log | 0.8615 | 56 | 0.4969 | 0.6158 | 0.4954 |
| No log | 0.8923 | 58 | 0.4962 | 0.6158 | 0.4947 |
| No log | 0.9231 | 60 | 0.4915 | 0.6233 | 0.4901 |
| No log | 0.9538 | 62 | 0.4898 | 0.6318 | 0.4885 |
| No log | 0.9846 | 64 | 0.4868 | 0.6478 | 0.4856 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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