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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.8569
- Qwk: 0.4778
- Mse: 0.8569
## 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 | 2.4863 | -0.0641 | 2.4863 |
| No log | 0.6667 | 4 | 1.3863 | 0.0 | 1.3863 |
| No log | 1.0 | 6 | 1.0547 | 0.1389 | 1.0547 |
| No log | 1.3333 | 8 | 1.0296 | 0.2049 | 1.0296 |
| No log | 1.6667 | 10 | 0.9224 | 0.2049 | 0.9224 |
| No log | 2.0 | 12 | 0.8332 | 0.3787 | 0.8332 |
| No log | 2.3333 | 14 | 0.8196 | 0.2895 | 0.8196 |
| No log | 2.6667 | 16 | 0.8152 | 0.2895 | 0.8152 |
| No log | 3.0 | 18 | 0.8909 | 0.2895 | 0.8909 |
| No log | 3.3333 | 20 | 0.9518 | 0.2736 | 0.9518 |
| No log | 3.6667 | 22 | 0.8848 | 0.2895 | 0.8848 |
| No log | 4.0 | 24 | 0.9478 | 0.4663 | 0.9478 |
| No log | 4.3333 | 26 | 1.0547 | 0.3316 | 1.0547 |
| No log | 4.6667 | 28 | 1.0817 | 0.3516 | 1.0817 |
| No log | 5.0 | 30 | 1.0055 | 0.4643 | 1.0055 |
| No log | 5.3333 | 32 | 0.8978 | 0.5068 | 0.8978 |
| No log | 5.6667 | 34 | 0.8372 | 0.5479 | 0.8372 |
| No log | 6.0 | 36 | 0.8407 | 0.5455 | 0.8407 |
| No log | 6.3333 | 38 | 0.9061 | 0.4778 | 0.9061 |
| No log | 6.6667 | 40 | 0.9725 | 0.4643 | 0.9725 |
| No log | 7.0 | 42 | 0.9463 | 0.4778 | 0.9463 |
| No log | 7.3333 | 44 | 0.8661 | 0.5455 | 0.8661 |
| No log | 7.6667 | 46 | 0.8220 | 0.5844 | 0.8220 |
| No log | 8.0 | 48 | 0.8110 | 0.5844 | 0.8110 |
| No log | 8.3333 | 50 | 0.8224 | 0.5844 | 0.8224 |
| No log | 8.6667 | 52 | 0.8540 | 0.4778 | 0.8540 |
| No log | 9.0 | 54 | 0.8631 | 0.4778 | 0.8631 |
| No log | 9.3333 | 56 | 0.8567 | 0.4778 | 0.8567 |
| No log | 9.6667 | 58 | 0.8579 | 0.4778 | 0.8579 |
| No log | 10.0 | 60 | 0.8569 | 0.4778 | 0.8569 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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