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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task3_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_task3_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: 0.6808
- Qwk: 0.5680
- Mse: 0.6804
## 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 | 0.0323 | 2 | 4.4744 | -0.0256 | 4.4706 |
| No log | 0.0645 | 4 | 2.3045 | 0.0249 | 2.3004 |
| No log | 0.0968 | 6 | 1.2805 | 0.1391 | 1.2779 |
| No log | 0.1290 | 8 | 1.0125 | 0.1335 | 1.0109 |
| No log | 0.1613 | 10 | 1.0701 | 0.1914 | 1.0686 |
| No log | 0.1935 | 12 | 1.2785 | 0.2037 | 1.2768 |
| No log | 0.2258 | 14 | 1.2274 | 0.2479 | 1.2257 |
| No log | 0.2581 | 16 | 1.0548 | 0.3135 | 1.0534 |
| No log | 0.2903 | 18 | 0.9068 | 0.4200 | 0.9058 |
| No log | 0.3226 | 20 | 0.8042 | 0.4719 | 0.8035 |
| No log | 0.3548 | 22 | 0.7409 | 0.5318 | 0.7404 |
| No log | 0.3871 | 24 | 0.7832 | 0.5356 | 0.7827 |
| No log | 0.4194 | 26 | 0.8927 | 0.5031 | 0.8924 |
| No log | 0.4516 | 28 | 1.1506 | 0.4441 | 1.1505 |
| No log | 0.4839 | 30 | 1.4202 | 0.3909 | 1.4201 |
| No log | 0.5161 | 32 | 1.1610 | 0.4441 | 1.1608 |
| No log | 0.5484 | 34 | 0.8093 | 0.5444 | 0.8088 |
| No log | 0.5806 | 36 | 0.6806 | 0.5981 | 0.6803 |
| No log | 0.6129 | 38 | 0.6480 | 0.5752 | 0.6477 |
| No log | 0.6452 | 40 | 0.6549 | 0.5691 | 0.6546 |
| No log | 0.6774 | 42 | 0.7025 | 0.5317 | 0.7021 |
| No log | 0.7097 | 44 | 0.7321 | 0.5105 | 0.7317 |
| No log | 0.7419 | 46 | 0.7334 | 0.5066 | 0.7330 |
| No log | 0.7742 | 48 | 0.7273 | 0.5221 | 0.7269 |
| No log | 0.8065 | 50 | 0.7075 | 0.5309 | 0.7071 |
| No log | 0.8387 | 52 | 0.6855 | 0.5374 | 0.6852 |
| No log | 0.8710 | 54 | 0.6736 | 0.5635 | 0.6733 |
| No log | 0.9032 | 56 | 0.6784 | 0.5680 | 0.6781 |
| No log | 0.9355 | 58 | 0.6858 | 0.5657 | 0.6855 |
| No log | 0.9677 | 60 | 0.6828 | 0.5669 | 0.6825 |
| No log | 1.0 | 62 | 0.6808 | 0.5680 | 0.6804 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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