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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task2_fold1
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_baseline_grammar_task2_fold1
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: 0.5805
- Qwk: 0.4573
- Mse: 0.5856
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
| No log | 0.3333 | 2 | 4.5766 | -0.0114 | 4.6757 |
| No log | 0.6667 | 4 | 1.8451 | 0.0840 | 1.9011 |
| No log | 1.0 | 6 | 1.0385 | 0.0 | 1.0614 |
| No log | 1.3333 | 8 | 0.8509 | 0.0 | 0.8474 |
| No log | 1.6667 | 10 | 0.8477 | 0.0 | 0.8402 |
| No log | 2.0 | 12 | 0.7153 | 0.2184 | 0.7165 |
| No log | 2.3333 | 14 | 0.6748 | 0.2687 | 0.6856 |
| No log | 2.6667 | 16 | 0.7113 | 0.1912 | 0.7272 |
| No log | 3.0 | 18 | 0.7379 | 0.1902 | 0.7546 |
| No log | 3.3333 | 20 | 0.6880 | 0.1923 | 0.7014 |
| No log | 3.6667 | 22 | 0.6478 | 0.3544 | 0.6544 |
| No log | 4.0 | 24 | 0.6652 | 0.3849 | 0.6682 |
| No log | 4.3333 | 26 | 0.6717 | 0.4573 | 0.6748 |
| No log | 4.6667 | 28 | 0.6419 | 0.4304 | 0.6475 |
| No log | 5.0 | 30 | 0.6314 | 0.4573 | 0.6355 |
| No log | 5.3333 | 32 | 0.6776 | 0.3849 | 0.6787 |
| No log | 5.6667 | 34 | 0.6654 | 0.3849 | 0.6671 |
| No log | 6.0 | 36 | 0.6226 | 0.4573 | 0.6260 |
| No log | 6.3333 | 38 | 0.5977 | 0.3544 | 0.6024 |
| No log | 6.6667 | 40 | 0.5953 | 0.1306 | 0.6010 |
| No log | 7.0 | 42 | 0.5909 | 0.1306 | 0.5966 |
| No log | 7.3333 | 44 | 0.5860 | 0.1306 | 0.5916 |
| No log | 7.6667 | 46 | 0.5891 | 0.3544 | 0.5944 |
| No log | 8.0 | 48 | 0.6067 | 0.4573 | 0.6111 |
| No log | 8.3333 | 50 | 0.6190 | 0.4573 | 0.6228 |
| No log | 8.6667 | 52 | 0.6206 | 0.4573 | 0.6243 |
| No log | 9.0 | 54 | 0.6083 | 0.4573 | 0.6124 |
| No log | 9.3333 | 56 | 0.5947 | 0.4573 | 0.5993 |
| No log | 9.6667 | 58 | 0.5850 | 0.4573 | 0.5899 |
| No log | 10.0 | 60 | 0.5805 | 0.4573 | 0.5856 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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