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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_task2_fold0
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_fold0
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: 0.4765
- Qwk: 0.5051
- Mse: 0.4812
## 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 | 3.4785 | 0.0139 | 3.4271 |
| No log | 0.6667 | 4 | 1.3527 | 0.0988 | 1.3438 |
| No log | 1.0 | 6 | 0.9762 | 0.0466 | 0.9710 |
| No log | 1.3333 | 8 | 0.5845 | 0.3068 | 0.5906 |
| No log | 1.6667 | 10 | 0.6355 | 0.4901 | 0.6479 |
| No log | 2.0 | 12 | 0.6002 | 0.4901 | 0.6080 |
| No log | 2.3333 | 14 | 0.5521 | 0.3591 | 0.5519 |
| No log | 2.6667 | 16 | 0.5671 | 0.5312 | 0.5733 |
| No log | 3.0 | 18 | 0.5298 | 0.5351 | 0.5340 |
| No log | 3.3333 | 20 | 0.5071 | 0.3871 | 0.4996 |
| No log | 3.6667 | 22 | 0.4892 | 0.3871 | 0.4817 |
| No log | 4.0 | 24 | 0.4557 | 0.5051 | 0.4597 |
| No log | 4.3333 | 26 | 0.5421 | 0.5205 | 0.5533 |
| No log | 4.6667 | 28 | 0.5017 | 0.5263 | 0.5115 |
| No log | 5.0 | 30 | 0.4329 | 0.5365 | 0.4364 |
| No log | 5.3333 | 32 | 0.4203 | 0.4431 | 0.4190 |
| No log | 5.6667 | 34 | 0.4083 | 0.4848 | 0.4015 |
| No log | 6.0 | 36 | 0.4520 | 0.4167 | 0.4366 |
| No log | 6.3333 | 38 | 0.4291 | 0.4396 | 0.4158 |
| No log | 6.6667 | 40 | 0.4230 | 0.4324 | 0.4110 |
| No log | 7.0 | 42 | 0.4029 | 0.4848 | 0.3965 |
| No log | 7.3333 | 44 | 0.4095 | 0.4848 | 0.4043 |
| No log | 7.6667 | 46 | 0.4194 | 0.4149 | 0.4149 |
| No log | 8.0 | 48 | 0.4324 | 0.5051 | 0.4317 |
| No log | 8.3333 | 50 | 0.4591 | 0.5051 | 0.4628 |
| No log | 8.6667 | 52 | 0.4758 | 0.4652 | 0.4811 |
| No log | 9.0 | 54 | 0.4791 | 0.4652 | 0.4844 |
| No log | 9.3333 | 56 | 0.4781 | 0.4652 | 0.4831 |
| No log | 9.6667 | 58 | 0.4760 | 0.5051 | 0.4806 |
| No log | 10.0 | 60 | 0.4765 | 0.5051 | 0.4812 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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