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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_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_mechanics_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: 0.9842
- Qwk: 0.1750
- Mse: 0.9841
## 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 | 4.1574 | 0.0205 | 4.1715 |
| No log | 0.6667 | 4 | 2.0929 | 0.0123 | 2.1054 |
| No log | 1.0 | 6 | 1.3194 | -0.1337 | 1.3202 |
| No log | 1.3333 | 8 | 0.9360 | 0.2588 | 0.9322 |
| No log | 1.6667 | 10 | 0.9386 | 0.0907 | 0.9344 |
| No log | 2.0 | 12 | 1.1338 | -0.0221 | 1.1277 |
| No log | 2.3333 | 14 | 1.0683 | 0.0907 | 1.0627 |
| No log | 2.6667 | 16 | 0.8193 | 0.2808 | 0.8154 |
| No log | 3.0 | 18 | 0.7951 | 0.2441 | 0.7912 |
| No log | 3.3333 | 20 | 0.8524 | 0.2853 | 0.8486 |
| No log | 3.6667 | 22 | 1.0382 | -0.1210 | 1.0361 |
| No log | 4.0 | 24 | 1.2097 | -0.1351 | 1.2090 |
| No log | 4.3333 | 26 | 1.3025 | -0.0355 | 1.3038 |
| No log | 4.6667 | 28 | 1.1375 | 0.2732 | 1.1373 |
| No log | 5.0 | 30 | 0.8628 | 0.2455 | 0.8539 |
| No log | 5.3333 | 32 | 0.8145 | 0.1649 | 0.8046 |
| No log | 5.6667 | 34 | 0.8765 | 0.2222 | 0.8718 |
| No log | 6.0 | 36 | 0.9949 | 0.1892 | 0.9951 |
| No log | 6.3333 | 38 | 1.0164 | 0.1892 | 1.0171 |
| No log | 6.6667 | 40 | 0.9913 | 0.1892 | 0.9919 |
| No log | 7.0 | 42 | 0.9485 | 0.1892 | 0.9484 |
| No log | 7.3333 | 44 | 0.9129 | 0.0667 | 0.9120 |
| No log | 7.6667 | 46 | 0.8943 | 0.0667 | 0.8925 |
| No log | 8.0 | 48 | 0.9394 | 0.0667 | 0.9387 |
| No log | 8.3333 | 50 | 0.9883 | 0.1892 | 0.9886 |
| No log | 8.6667 | 52 | 0.9904 | 0.1892 | 0.9907 |
| No log | 9.0 | 54 | 0.9905 | 0.1892 | 0.9908 |
| No log | 9.3333 | 56 | 0.9842 | 0.1892 | 0.9843 |
| No log | 9.6667 | 58 | 0.9876 | 0.1664 | 0.9876 |
| No log | 10.0 | 60 | 0.9842 | 0.1750 | 0.9841 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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