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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_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_task7_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: 0.7581
- Qwk: 0.0
- Mse: 0.7581
## 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 | 0.0308 | 2 | 7.8306 | -0.0005 | 7.8306 |
| No log | 0.0615 | 4 | 4.1936 | 0.0 | 4.1936 |
| No log | 0.0923 | 6 | 2.0851 | 0.0593 | 2.0851 |
| No log | 0.1231 | 8 | 1.2404 | 0.0 | 1.2404 |
| No log | 0.1538 | 10 | 0.8586 | 0.0093 | 0.8586 |
| No log | 0.1846 | 12 | 0.7508 | 0.0707 | 0.7508 |
| No log | 0.2154 | 14 | 0.7356 | 0.0372 | 0.7356 |
| No log | 0.2462 | 16 | 0.8138 | 0.1082 | 0.8138 |
| No log | 0.2769 | 18 | 0.9262 | -0.0080 | 0.9262 |
| No log | 0.3077 | 20 | 0.8710 | -0.0045 | 0.8710 |
| No log | 0.3385 | 22 | 0.7502 | -0.0408 | 0.7502 |
| No log | 0.3692 | 24 | 0.7389 | 0.0 | 0.7389 |
| No log | 0.4 | 26 | 0.7855 | 0.0 | 0.7855 |
| No log | 0.4308 | 28 | 0.7754 | 0.0 | 0.7754 |
| No log | 0.4615 | 30 | 0.7485 | 0.0 | 0.7485 |
| No log | 0.4923 | 32 | 0.7451 | 0.0 | 0.7451 |
| No log | 0.5231 | 34 | 0.7615 | 0.0 | 0.7615 |
| No log | 0.5538 | 36 | 0.7804 | 0.0 | 0.7804 |
| No log | 0.5846 | 38 | 0.7731 | 0.0 | 0.7731 |
| No log | 0.6154 | 40 | 0.7812 | 0.0 | 0.7812 |
| No log | 0.6462 | 42 | 0.8026 | 0.0 | 0.8026 |
| No log | 0.6769 | 44 | 0.8454 | 0.0 | 0.8454 |
| No log | 0.7077 | 46 | 0.8541 | 0.0 | 0.8541 |
| No log | 0.7385 | 48 | 0.8250 | 0.0 | 0.8250 |
| No log | 0.7692 | 50 | 0.8021 | 0.0 | 0.8021 |
| No log | 0.8 | 52 | 0.7828 | 0.0 | 0.7828 |
| No log | 0.8308 | 54 | 0.7701 | 0.0 | 0.7701 |
| No log | 0.8615 | 56 | 0.7633 | 0.0 | 0.7633 |
| No log | 0.8923 | 58 | 0.7561 | 0.0 | 0.7561 |
| No log | 0.9231 | 60 | 0.7554 | 0.0 | 0.7554 |
| No log | 0.9538 | 62 | 0.7563 | 0.0 | 0.7563 |
| No log | 0.9846 | 64 | 0.7581 | 0.0 | 0.7581 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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