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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task1_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_cross_vocabulary_task1_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: 0.9107
- Qwk: 0.3160
- Mse: 0.9107
## 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 | 3.6812 | 0.0124 | 3.6812 |
| No log | 0.0702 | 4 | 2.2449 | 0.0807 | 2.2449 |
| No log | 0.1053 | 6 | 1.7920 | 0.1291 | 1.7920 |
| No log | 0.1404 | 8 | 1.1077 | 0.2184 | 1.1077 |
| No log | 0.1754 | 10 | 1.6727 | 0.2157 | 1.6727 |
| No log | 0.2105 | 12 | 2.3411 | 0.1852 | 2.3411 |
| No log | 0.2456 | 14 | 1.4252 | 0.2951 | 1.4252 |
| No log | 0.2807 | 16 | 0.8885 | 0.3981 | 0.8885 |
| No log | 0.3158 | 18 | 0.6824 | 0.4387 | 0.6824 |
| No log | 0.3509 | 20 | 0.6604 | 0.4473 | 0.6604 |
| No log | 0.3860 | 22 | 0.7208 | 0.3880 | 0.7208 |
| No log | 0.4211 | 24 | 1.1639 | 0.2846 | 1.1639 |
| No log | 0.4561 | 26 | 2.0330 | 0.1689 | 2.0330 |
| No log | 0.4912 | 28 | 2.2500 | 0.1485 | 2.2500 |
| No log | 0.5263 | 30 | 1.8145 | 0.1758 | 1.8145 |
| No log | 0.5614 | 32 | 1.1982 | 0.2547 | 1.1982 |
| No log | 0.5965 | 34 | 0.8111 | 0.3192 | 0.8111 |
| No log | 0.6316 | 36 | 0.7359 | 0.3443 | 0.7359 |
| No log | 0.6667 | 38 | 0.8012 | 0.3164 | 0.8012 |
| No log | 0.7018 | 40 | 0.9036 | 0.2985 | 0.9036 |
| No log | 0.7368 | 42 | 1.0075 | 0.2804 | 1.0075 |
| No log | 0.7719 | 44 | 1.0761 | 0.2855 | 1.0761 |
| No log | 0.8070 | 46 | 1.0400 | 0.2883 | 1.0400 |
| No log | 0.8421 | 48 | 1.0379 | 0.2963 | 1.0379 |
| No log | 0.8772 | 50 | 1.0163 | 0.3002 | 1.0163 |
| No log | 0.9123 | 52 | 0.9760 | 0.3168 | 0.9760 |
| No log | 0.9474 | 54 | 0.9286 | 0.3206 | 0.9286 |
| No log | 0.9825 | 56 | 0.9107 | 0.3160 | 0.9107 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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