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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task2_fold3
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_task2_fold3
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: 0.7212
- Qwk: 0.7957
- Mse: 0.7212
## 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 | 0.0351 | 2 | 3.3323 | 0.0213 | 3.3323 |
| No log | 0.0702 | 4 | 2.0333 | 0.1468 | 2.0333 |
| No log | 0.1053 | 6 | 1.4923 | 0.3102 | 1.4923 |
| No log | 0.1404 | 8 | 1.6734 | 0.3305 | 1.6734 |
| No log | 0.1754 | 10 | 1.7352 | 0.2966 | 1.7352 |
| No log | 0.2105 | 12 | 1.6360 | 0.2588 | 1.6360 |
| No log | 0.2456 | 14 | 1.5076 | 0.2925 | 1.5076 |
| No log | 0.2807 | 16 | 1.3433 | 0.3646 | 1.3433 |
| No log | 0.3158 | 18 | 1.2343 | 0.4245 | 1.2343 |
| No log | 0.3509 | 20 | 1.1517 | 0.5033 | 1.1517 |
| No log | 0.3860 | 22 | 1.1391 | 0.6144 | 1.1391 |
| No log | 0.4211 | 24 | 1.1438 | 0.6514 | 1.1438 |
| No log | 0.4561 | 26 | 1.1808 | 0.6567 | 1.1808 |
| No log | 0.4912 | 28 | 1.1197 | 0.7055 | 1.1197 |
| No log | 0.5263 | 30 | 0.9660 | 0.7854 | 0.9660 |
| No log | 0.5614 | 32 | 0.8893 | 0.7754 | 0.8893 |
| No log | 0.5965 | 34 | 0.8546 | 0.7866 | 0.8546 |
| No log | 0.6316 | 36 | 0.9013 | 0.7896 | 0.9013 |
| No log | 0.6667 | 38 | 0.9216 | 0.8034 | 0.9216 |
| No log | 0.7018 | 40 | 0.9057 | 0.7971 | 0.9057 |
| No log | 0.7368 | 42 | 0.8462 | 0.7814 | 0.8462 |
| No log | 0.7719 | 44 | 0.7936 | 0.7892 | 0.7936 |
| No log | 0.8070 | 46 | 0.7517 | 0.8069 | 0.7517 |
| No log | 0.8421 | 48 | 0.7133 | 0.7975 | 0.7133 |
| No log | 0.8772 | 50 | 0.6939 | 0.7967 | 0.6939 |
| No log | 0.9123 | 52 | 0.7043 | 0.7937 | 0.7043 |
| No log | 0.9474 | 54 | 0.7171 | 0.7957 | 0.7171 |
| No log | 0.9825 | 56 | 0.7212 | 0.7957 | 0.7212 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|