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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task5_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_task5_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: 0.4829
- Qwk: 0.6262
- Mse: 0.4829
## 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 | 2.4374 | 0.0250 | 2.4374 |
| No log | 0.6667 | 4 | 0.9732 | -0.0090 | 0.9732 |
| No log | 1.0 | 6 | 0.5943 | 0.3165 | 0.5943 |
| No log | 1.3333 | 8 | 0.5108 | 0.3182 | 0.5108 |
| No log | 1.6667 | 10 | 0.4747 | 0.3137 | 0.4747 |
| No log | 2.0 | 12 | 0.4634 | 0.3165 | 0.4634 |
| No log | 2.3333 | 14 | 0.4798 | 0.4509 | 0.4798 |
| No log | 2.6667 | 16 | 0.4795 | 0.4737 | 0.4795 |
| No log | 3.0 | 18 | 0.5467 | 0.5327 | 0.5467 |
| No log | 3.3333 | 20 | 0.5831 | 0.5327 | 0.5831 |
| No log | 3.6667 | 22 | 0.5213 | 0.6269 | 0.5213 |
| No log | 4.0 | 24 | 0.6213 | 0.7087 | 0.6213 |
| No log | 4.3333 | 26 | 0.6774 | 0.7236 | 0.6774 |
| No log | 4.6667 | 28 | 0.6694 | 0.7236 | 0.6694 |
| No log | 5.0 | 30 | 0.5668 | 0.7 | 0.5668 |
| No log | 5.3333 | 32 | 0.5235 | 0.7059 | 0.5235 |
| No log | 5.6667 | 34 | 0.5216 | 0.7059 | 0.5216 |
| No log | 6.0 | 36 | 0.5070 | 0.5957 | 0.5070 |
| No log | 6.3333 | 38 | 0.5038 | 0.6047 | 0.5038 |
| No log | 6.6667 | 40 | 0.5220 | 0.6606 | 0.5220 |
| No log | 7.0 | 42 | 0.5420 | 0.6377 | 0.5420 |
| No log | 7.3333 | 44 | 0.5474 | 0.6667 | 0.5474 |
| No log | 7.6667 | 46 | 0.5400 | 0.6262 | 0.5400 |
| No log | 8.0 | 48 | 0.5341 | 0.6262 | 0.5341 |
| No log | 8.3333 | 50 | 0.5282 | 0.6262 | 0.5282 |
| No log | 8.6667 | 52 | 0.5146 | 0.6262 | 0.5146 |
| No log | 9.0 | 54 | 0.4982 | 0.6262 | 0.4982 |
| No log | 9.3333 | 56 | 0.4857 | 0.6262 | 0.4857 |
| No log | 9.6667 | 58 | 0.4846 | 0.6262 | 0.4846 |
| No log | 10.0 | 60 | 0.4829 | 0.6262 | 0.4829 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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