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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_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_task7_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: 0.7372
- Qwk: 0.0
- Mse: 0.7250
## 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 | 0.0317 | 2 | 3.4222 | 0.0005 | 3.4448 |
| No log | 0.0635 | 4 | 0.8344 | -0.0075 | 0.8385 |
| No log | 0.0952 | 6 | 0.6004 | 0.0456 | 0.5963 |
| No log | 0.1270 | 8 | 0.5812 | -0.0227 | 0.5744 |
| No log | 0.1587 | 10 | 0.6585 | 0.0 | 0.6498 |
| No log | 0.1905 | 12 | 0.6873 | 0.0 | 0.6781 |
| No log | 0.2222 | 14 | 0.6603 | 0.0 | 0.6514 |
| No log | 0.2540 | 16 | 0.5985 | -0.0496 | 0.5919 |
| No log | 0.2857 | 18 | 0.5749 | -0.0344 | 0.5697 |
| No log | 0.3175 | 20 | 0.5691 | -0.0546 | 0.5649 |
| No log | 0.3492 | 22 | 0.5753 | -0.0344 | 0.5700 |
| No log | 0.3810 | 24 | 0.6027 | -0.0886 | 0.5953 |
| No log | 0.4127 | 26 | 0.6013 | -0.0886 | 0.5936 |
| No log | 0.4444 | 28 | 0.6360 | -0.0252 | 0.6265 |
| No log | 0.4762 | 30 | 0.6499 | -0.0252 | 0.6399 |
| No log | 0.5079 | 32 | 0.7649 | 0.0 | 0.7525 |
| No log | 0.5397 | 34 | 0.8350 | 0.0 | 0.8221 |
| No log | 0.5714 | 36 | 0.8330 | 0.0 | 0.8214 |
| No log | 0.6032 | 38 | 0.7620 | 0.0 | 0.7524 |
| No log | 0.6349 | 40 | 0.7292 | 0.0 | 0.7198 |
| No log | 0.6667 | 42 | 0.6967 | 0.0 | 0.6875 |
| No log | 0.6984 | 44 | 0.7020 | 0.0 | 0.6922 |
| No log | 0.7302 | 46 | 0.7157 | 0.0 | 0.7048 |
| No log | 0.7619 | 48 | 0.7198 | 0.0 | 0.7083 |
| No log | 0.7937 | 50 | 0.6970 | 0.0 | 0.6856 |
| No log | 0.8254 | 52 | 0.6743 | 0.0 | 0.6632 |
| No log | 0.8571 | 54 | 0.6647 | 0.0 | 0.6537 |
| No log | 0.8889 | 56 | 0.6819 | 0.0 | 0.6706 |
| No log | 0.9206 | 58 | 0.7064 | 0.0 | 0.6946 |
| No log | 0.9524 | 60 | 0.7251 | 0.0 | 0.7130 |
| No log | 0.9841 | 62 | 0.7372 | 0.0 | 0.7250 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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