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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.4740
- Qwk: 0.5263
- Mse: 0.4884
## 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 | 2.7474 | 0.0719 | 2.8478 |
| No log | 0.6667 | 4 | 0.9337 | 0.1600 | 0.9879 |
| No log | 1.0 | 6 | 0.4534 | 0.0 | 0.4764 |
| No log | 1.3333 | 8 | 0.7904 | -0.0408 | 0.7830 |
| No log | 1.6667 | 10 | 0.7018 | 0.0769 | 0.6973 |
| No log | 2.0 | 12 | 0.5298 | 0.2258 | 0.5356 |
| No log | 2.3333 | 14 | 0.4547 | 0.0 | 0.4751 |
| No log | 2.6667 | 16 | 0.4579 | 0.0 | 0.4810 |
| No log | 3.0 | 18 | 0.4621 | 0.0 | 0.4849 |
| No log | 3.3333 | 20 | 0.5042 | 0.1563 | 0.5232 |
| No log | 3.6667 | 22 | 0.5058 | 0.1905 | 0.5230 |
| No log | 4.0 | 24 | 0.4808 | 0.2623 | 0.4947 |
| No log | 4.3333 | 26 | 0.4464 | 0.4828 | 0.4576 |
| No log | 4.6667 | 28 | 0.3793 | 0.2258 | 0.3943 |
| No log | 5.0 | 30 | 0.3971 | 0.2623 | 0.4100 |
| No log | 5.3333 | 32 | 0.5018 | 0.5263 | 0.5120 |
| No log | 5.6667 | 34 | 0.5357 | 0.3390 | 0.5481 |
| No log | 6.0 | 36 | 0.4854 | 0.3000 | 0.5002 |
| No log | 6.3333 | 38 | 0.4022 | 0.2623 | 0.4219 |
| No log | 6.6667 | 40 | 0.4018 | 0.2597 | 0.4313 |
| No log | 7.0 | 42 | 0.4157 | 0.2597 | 0.4485 |
| No log | 7.3333 | 44 | 0.3858 | 0.2895 | 0.4130 |
| No log | 7.6667 | 46 | 0.3839 | 0.3200 | 0.4045 |
| No log | 8.0 | 48 | 0.4237 | 0.5263 | 0.4396 |
| No log | 8.3333 | 50 | 0.4462 | 0.5263 | 0.4608 |
| No log | 8.6667 | 52 | 0.4536 | 0.5263 | 0.4681 |
| No log | 9.0 | 54 | 0.4620 | 0.5263 | 0.4764 |
| No log | 9.3333 | 56 | 0.4700 | 0.5263 | 0.4842 |
| No log | 9.6667 | 58 | 0.4698 | 0.5263 | 0.4842 |
| No log | 10.0 | 60 | 0.4740 | 0.5263 | 0.4884 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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