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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_task7_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_task7_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: 0.6217
- Qwk: 0.4969
- Mse: 0.6213
## 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 | 1.0245 | 0.3758 | 1.0297 |
| No log | 0.6667 | 4 | 0.7919 | 0.5312 | 0.8059 |
| No log | 1.0 | 6 | 0.8469 | 0.6400 | 0.8626 |
| No log | 1.3333 | 8 | 0.7621 | 0.3793 | 0.7785 |
| No log | 1.6667 | 10 | 0.8831 | 0.2326 | 0.8970 |
| No log | 2.0 | 12 | 0.7493 | 0.4 | 0.7628 |
| No log | 2.3333 | 14 | 0.4924 | 0.6165 | 0.5052 |
| No log | 2.6667 | 16 | 0.4499 | 0.6571 | 0.4612 |
| No log | 3.0 | 18 | 0.4936 | 0.6203 | 0.5029 |
| No log | 3.3333 | 20 | 0.7252 | 0.4224 | 0.7311 |
| No log | 3.6667 | 22 | 0.9227 | 0.3657 | 0.9263 |
| No log | 4.0 | 24 | 0.8957 | 0.3657 | 0.8980 |
| No log | 4.3333 | 26 | 0.7242 | 0.4211 | 0.7260 |
| No log | 4.6667 | 28 | 0.5595 | 0.6203 | 0.5620 |
| No log | 5.0 | 30 | 0.4521 | 0.6024 | 0.4559 |
| No log | 5.3333 | 32 | 0.4402 | 0.6786 | 0.4437 |
| No log | 5.6667 | 34 | 0.4703 | 0.6909 | 0.4728 |
| No log | 6.0 | 36 | 0.6144 | 0.5 | 0.6153 |
| No log | 6.3333 | 38 | 0.7150 | 0.4969 | 0.7150 |
| No log | 6.6667 | 40 | 0.7022 | 0.4969 | 0.7024 |
| No log | 7.0 | 42 | 0.6409 | 0.5 | 0.6418 |
| No log | 7.3333 | 44 | 0.5912 | 0.5 | 0.5923 |
| No log | 7.6667 | 46 | 0.5457 | 0.6341 | 0.5469 |
| No log | 8.0 | 48 | 0.5073 | 0.6909 | 0.5089 |
| No log | 8.3333 | 50 | 0.5143 | 0.6909 | 0.5157 |
| No log | 8.6667 | 52 | 0.5540 | 0.6341 | 0.5549 |
| No log | 9.0 | 54 | 0.5883 | 0.6272 | 0.5886 |
| No log | 9.3333 | 56 | 0.6103 | 0.4969 | 0.6102 |
| No log | 9.6667 | 58 | 0.6204 | 0.4969 | 0.6200 |
| No log | 10.0 | 60 | 0.6217 | 0.4969 | 0.6213 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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