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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold4
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_task7_fold4
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: 0.9341
- Qwk: 0.8036
- Mse: 0.9341
## 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 | 3.7363 | 0.0136 | 3.7363 |
| No log | 0.0702 | 4 | 2.3106 | 0.1619 | 2.3106 |
| No log | 0.1053 | 6 | 1.8172 | 0.1692 | 1.8172 |
| No log | 0.1404 | 8 | 1.6116 | 0.2787 | 1.6116 |
| No log | 0.1754 | 10 | 1.8910 | 0.3258 | 1.8910 |
| No log | 0.2105 | 12 | 1.8785 | 0.4430 | 1.8785 |
| No log | 0.2456 | 14 | 1.8131 | 0.4299 | 1.8131 |
| No log | 0.2807 | 16 | 2.0288 | 0.5063 | 2.0288 |
| No log | 0.3158 | 18 | 1.6252 | 0.5783 | 1.6252 |
| No log | 0.3509 | 20 | 1.4668 | 0.6465 | 1.4668 |
| No log | 0.3860 | 22 | 1.1133 | 0.6929 | 1.1133 |
| No log | 0.4211 | 24 | 0.8668 | 0.7249 | 0.8668 |
| No log | 0.4561 | 26 | 0.9262 | 0.7457 | 0.9262 |
| No log | 0.4912 | 28 | 1.0096 | 0.7462 | 1.0096 |
| No log | 0.5263 | 30 | 1.0968 | 0.7380 | 1.0968 |
| No log | 0.5614 | 32 | 1.1232 | 0.7473 | 1.1232 |
| No log | 0.5965 | 34 | 1.1632 | 0.7453 | 1.1632 |
| No log | 0.6316 | 36 | 1.1137 | 0.7662 | 1.1137 |
| No log | 0.6667 | 38 | 1.0328 | 0.7794 | 1.0328 |
| No log | 0.7018 | 40 | 0.8546 | 0.8110 | 0.8546 |
| No log | 0.7368 | 42 | 0.7276 | 0.7840 | 0.7276 |
| No log | 0.7719 | 44 | 0.6916 | 0.7793 | 0.6916 |
| No log | 0.8070 | 46 | 0.7025 | 0.7855 | 0.7025 |
| No log | 0.8421 | 48 | 0.7202 | 0.7971 | 0.7202 |
| No log | 0.8772 | 50 | 0.7770 | 0.8095 | 0.7770 |
| No log | 0.9123 | 52 | 0.8545 | 0.8154 | 0.8545 |
| No log | 0.9474 | 54 | 0.9105 | 0.8088 | 0.9105 |
| No log | 0.9825 | 56 | 0.9341 | 0.8036 | 0.9341 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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