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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.6156
- Qwk: 0.7263
- Mse: 0.5866
## 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 | 4.0016 | -0.0094 | 4.0420 |
| No log | 0.6667 | 4 | 1.5678 | 0.0597 | 1.6106 |
| No log | 1.0 | 6 | 1.1107 | 0.125 | 1.1443 |
| No log | 1.3333 | 8 | 0.6987 | 0.2286 | 0.7156 |
| No log | 1.6667 | 10 | 0.6381 | 0.4661 | 0.6469 |
| No log | 2.0 | 12 | 0.5798 | 0.3984 | 0.5877 |
| No log | 2.3333 | 14 | 0.4646 | 0.552 | 0.4642 |
| No log | 2.6667 | 16 | 0.4683 | 0.6379 | 0.4526 |
| No log | 3.0 | 18 | 0.4347 | 0.7154 | 0.4182 |
| No log | 3.3333 | 20 | 0.4464 | 0.5977 | 0.4400 |
| No log | 3.6667 | 22 | 0.4523 | 0.6957 | 0.4373 |
| No log | 4.0 | 24 | 0.6917 | 0.7616 | 0.6664 |
| No log | 4.3333 | 26 | 0.8197 | 0.7485 | 0.7888 |
| No log | 4.6667 | 28 | 0.7131 | 0.7701 | 0.6829 |
| No log | 5.0 | 30 | 0.7249 | 0.7154 | 0.6941 |
| No log | 5.3333 | 32 | 0.8136 | 0.7572 | 0.7780 |
| No log | 5.6667 | 34 | 0.9048 | 0.7347 | 0.8646 |
| No log | 6.0 | 36 | 0.8073 | 0.7347 | 0.7664 |
| No log | 6.3333 | 38 | 0.7257 | 0.7840 | 0.6853 |
| No log | 6.6667 | 40 | 0.7345 | 0.7840 | 0.6936 |
| No log | 7.0 | 42 | 0.7184 | 0.7263 | 0.6797 |
| No log | 7.3333 | 44 | 0.6757 | 0.7263 | 0.6409 |
| No log | 7.6667 | 46 | 0.7056 | 0.7042 | 0.6701 |
| No log | 8.0 | 48 | 0.7177 | 0.7515 | 0.6822 |
| No log | 8.3333 | 50 | 0.7076 | 0.7515 | 0.6730 |
| No log | 8.6667 | 52 | 0.7003 | 0.7515 | 0.6663 |
| No log | 9.0 | 54 | 0.6732 | 0.7515 | 0.6407 |
| No log | 9.3333 | 56 | 0.6412 | 0.7042 | 0.6104 |
| No log | 9.6667 | 58 | 0.6207 | 0.7263 | 0.5913 |
| No log | 10.0 | 60 | 0.6156 | 0.7263 | 0.5866 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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