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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task3_fold2
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_fold2
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: 1.2889
- Qwk: 0.1455
- Mse: 1.2889
## 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 | 0.0282 | 2 | 8.9247 | 0.0 | 8.9247 |
| No log | 0.0563 | 4 | 6.0585 | -0.0018 | 6.0585 |
| No log | 0.0845 | 6 | 3.3683 | 0.0 | 3.3683 |
| No log | 0.1127 | 8 | 1.9295 | 0.0353 | 1.9295 |
| No log | 0.1408 | 10 | 1.1575 | 0.0 | 1.1575 |
| No log | 0.1690 | 12 | 0.8179 | 0.0531 | 0.8179 |
| No log | 0.1972 | 14 | 0.7602 | -0.0155 | 0.7602 |
| No log | 0.2254 | 16 | 0.7582 | -0.0014 | 0.7582 |
| No log | 0.2535 | 18 | 0.7660 | 0.0643 | 0.7660 |
| No log | 0.2817 | 20 | 0.7464 | 0.0434 | 0.7464 |
| No log | 0.3099 | 22 | 0.7568 | 0.0 | 0.7568 |
| No log | 0.3380 | 24 | 0.7822 | 0.0 | 0.7822 |
| No log | 0.3662 | 26 | 0.8311 | 0.0 | 0.8311 |
| No log | 0.3944 | 28 | 0.8980 | 0.0 | 0.8980 |
| No log | 0.4225 | 30 | 0.9093 | 0.0 | 0.9093 |
| No log | 0.4507 | 32 | 0.8669 | 0.0 | 0.8669 |
| No log | 0.4789 | 34 | 0.8507 | 0.0 | 0.8507 |
| No log | 0.5070 | 36 | 0.8627 | 0.0 | 0.8627 |
| No log | 0.5352 | 38 | 0.8443 | 0.0 | 0.8443 |
| No log | 0.5634 | 40 | 0.8722 | 0.0 | 0.8722 |
| No log | 0.5915 | 42 | 0.9229 | 0.0 | 0.9229 |
| No log | 0.6197 | 44 | 0.9827 | 0.0 | 0.9827 |
| No log | 0.6479 | 46 | 1.0396 | 0.0 | 1.0396 |
| No log | 0.6761 | 48 | 1.1196 | 0.0 | 1.1196 |
| No log | 0.7042 | 50 | 1.1654 | 0.0 | 1.1654 |
| No log | 0.7324 | 52 | 1.1934 | 0.0086 | 1.1934 |
| No log | 0.7606 | 54 | 1.2497 | 0.0603 | 1.2497 |
| No log | 0.7887 | 56 | 1.2723 | 0.0272 | 1.2723 |
| No log | 0.8169 | 58 | 1.2595 | 0.1040 | 1.2595 |
| No log | 0.8451 | 60 | 1.2516 | 0.1696 | 1.2516 |
| No log | 0.8732 | 62 | 1.2442 | 0.1807 | 1.2442 |
| No log | 0.9014 | 64 | 1.2514 | 0.1696 | 1.2514 |
| No log | 0.9296 | 66 | 1.2627 | 0.1524 | 1.2627 |
| No log | 0.9577 | 68 | 1.2780 | 0.1455 | 1.2780 |
| No log | 0.9859 | 70 | 1.2889 | 0.1455 | 1.2889 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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