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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task2_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_task2_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: 0.7896
- Qwk: -0.0578
- Mse: 0.7896
## 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 | 8.5786 | 0.0 | 8.5786 |
| No log | 0.0615 | 4 | 4.7361 | 0.0027 | 4.7361 |
| No log | 0.0923 | 6 | 2.4849 | -0.0164 | 2.4849 |
| No log | 0.1231 | 8 | 1.0682 | 0.0 | 1.0682 |
| No log | 0.1538 | 10 | 1.0484 | -0.2071 | 1.0484 |
| No log | 0.1846 | 12 | 1.1580 | -0.1541 | 1.1580 |
| No log | 0.2154 | 14 | 0.7197 | 0.0071 | 0.7197 |
| No log | 0.2462 | 16 | 0.7275 | 0.1341 | 0.7275 |
| No log | 0.2769 | 18 | 0.8223 | 0.0676 | 0.8223 |
| No log | 0.3077 | 20 | 0.8068 | 0.0447 | 0.8068 |
| No log | 0.3385 | 22 | 0.7532 | -0.0157 | 0.7532 |
| No log | 0.3692 | 24 | 0.7525 | -0.0155 | 0.7525 |
| No log | 0.4 | 26 | 0.7808 | -0.0217 | 0.7808 |
| No log | 0.4308 | 28 | 0.7874 | -0.0658 | 0.7874 |
| No log | 0.4615 | 30 | 0.7780 | 0.0 | 0.7780 |
| No log | 0.4923 | 32 | 0.8462 | 0.0 | 0.8462 |
| No log | 0.5231 | 34 | 0.9212 | 0.0 | 0.9212 |
| No log | 0.5538 | 36 | 0.9624 | 0.0 | 0.9624 |
| No log | 0.5846 | 38 | 0.9977 | 0.0 | 0.9977 |
| No log | 0.6154 | 40 | 0.9965 | 0.0 | 0.9965 |
| No log | 0.6462 | 42 | 0.9605 | 0.0 | 0.9605 |
| No log | 0.6769 | 44 | 0.8767 | 0.0 | 0.8767 |
| No log | 0.7077 | 46 | 0.8153 | 0.0 | 0.8153 |
| No log | 0.7385 | 48 | 0.7919 | 0.0 | 0.7919 |
| No log | 0.7692 | 50 | 0.7850 | -0.0371 | 0.7850 |
| No log | 0.8 | 52 | 0.7871 | -0.0777 | 0.7871 |
| No log | 0.8308 | 54 | 0.7856 | -0.0777 | 0.7856 |
| No log | 0.8615 | 56 | 0.7873 | -0.0777 | 0.7873 |
| No log | 0.8923 | 58 | 0.7877 | -0.0578 | 0.7877 |
| No log | 0.9231 | 60 | 0.7921 | -0.0777 | 0.7921 |
| No log | 0.9538 | 62 | 0.7919 | -0.0777 | 0.7919 |
| No log | 0.9846 | 64 | 0.7896 | -0.0578 | 0.7896 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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