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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task1_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_relevance_task1_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: 0.0669
- Qwk: 0.0233
- Mse: 0.0682
## 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 | 0.9611 | -0.0186 | 0.9691 |
| No log | 0.6667 | 4 | 0.2075 | -0.0851 | 0.2124 |
| No log | 1.0 | 6 | 0.1656 | 0.0207 | 0.1701 |
| No log | 1.3333 | 8 | 0.1145 | 0.0392 | 0.1165 |
| No log | 1.6667 | 10 | 0.1145 | 0.0165 | 0.1165 |
| No log | 2.0 | 12 | 0.1921 | 0.0 | 0.1938 |
| No log | 2.3333 | 14 | 0.2095 | 0.0 | 0.2110 |
| No log | 2.6667 | 16 | 0.1634 | 0.0 | 0.1651 |
| No log | 3.0 | 18 | 0.0995 | 0.0 | 0.1002 |
| No log | 3.3333 | 20 | 0.1102 | 0.0050 | 0.1101 |
| No log | 3.6667 | 22 | 0.1004 | 0.0165 | 0.1002 |
| No log | 4.0 | 24 | 0.0724 | 0.0233 | 0.0728 |
| No log | 4.3333 | 26 | 0.0523 | 0.0233 | 0.0531 |
| No log | 4.6667 | 28 | 0.0574 | 0.0233 | 0.0583 |
| No log | 5.0 | 30 | 0.0614 | 0.0233 | 0.0626 |
| No log | 5.3333 | 32 | 0.0663 | 0.0233 | 0.0676 |
| No log | 5.6667 | 34 | 0.0729 | 0.0233 | 0.0742 |
| No log | 6.0 | 36 | 0.0631 | 0.0308 | 0.0641 |
| No log | 6.3333 | 38 | 0.0561 | 0.0597 | 0.0563 |
| No log | 6.6667 | 40 | 0.0579 | 0.0870 | 0.0579 |
| No log | 7.0 | 42 | 0.0563 | 0.0597 | 0.0566 |
| No log | 7.3333 | 44 | 0.0596 | 0.0308 | 0.0606 |
| No log | 7.6667 | 46 | 0.0661 | 0.0308 | 0.0673 |
| No log | 8.0 | 48 | 0.0735 | 0.0050 | 0.0747 |
| No log | 8.3333 | 50 | 0.0721 | 0.0105 | 0.0733 |
| No log | 8.6667 | 52 | 0.0679 | 0.0233 | 0.0690 |
| No log | 9.0 | 54 | 0.0657 | 0.0233 | 0.0669 |
| No log | 9.3333 | 56 | 0.0652 | 0.0233 | 0.0664 |
| No log | 9.6667 | 58 | 0.0664 | 0.0233 | 0.0677 |
| No log | 10.0 | 60 | 0.0669 | 0.0233 | 0.0682 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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