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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task7_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_task7_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: 0.3972
- Qwk: 0.6491
- Mse: 0.3972
## 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 | 1.3247 | 0.0816 | 1.3247 |
| No log | 0.6667 | 4 | 0.6683 | 0.4335 | 0.6683 |
| No log | 1.0 | 6 | 0.5559 | 0.4980 | 0.5559 |
| No log | 1.3333 | 8 | 0.6243 | 0.4454 | 0.6243 |
| No log | 1.6667 | 10 | 0.4715 | 0.6195 | 0.4715 |
| No log | 2.0 | 12 | 0.5116 | 0.6491 | 0.5116 |
| No log | 2.3333 | 14 | 0.6116 | 0.5702 | 0.6116 |
| No log | 2.6667 | 16 | 0.6154 | 0.5631 | 0.6154 |
| No log | 3.0 | 18 | 0.6351 | 0.4762 | 0.6351 |
| No log | 3.3333 | 20 | 0.4519 | 0.5248 | 0.4519 |
| No log | 3.6667 | 22 | 0.2987 | 0.6600 | 0.2987 |
| No log | 4.0 | 24 | 0.2664 | 0.6715 | 0.2664 |
| No log | 4.3333 | 26 | 0.3049 | 0.6491 | 0.3049 |
| No log | 4.6667 | 28 | 0.5042 | 0.5601 | 0.5042 |
| No log | 5.0 | 30 | 0.7298 | 0.4401 | 0.7298 |
| No log | 5.3333 | 32 | 0.7112 | 0.4401 | 0.7112 |
| No log | 5.6667 | 34 | 0.4277 | 0.6780 | 0.4277 |
| No log | 6.0 | 36 | 0.2880 | 0.7239 | 0.2880 |
| No log | 6.3333 | 38 | 0.2886 | 0.7239 | 0.2886 |
| No log | 6.6667 | 40 | 0.3219 | 0.7239 | 0.3219 |
| No log | 7.0 | 42 | 0.4290 | 0.6329 | 0.4290 |
| No log | 7.3333 | 44 | 0.5828 | 0.5497 | 0.5828 |
| No log | 7.6667 | 46 | 0.6367 | 0.5129 | 0.6367 |
| No log | 8.0 | 48 | 0.5900 | 0.5497 | 0.5900 |
| No log | 8.3333 | 50 | 0.4796 | 0.5955 | 0.4796 |
| No log | 8.6667 | 52 | 0.4272 | 0.6491 | 0.4272 |
| No log | 9.0 | 54 | 0.4126 | 0.6491 | 0.4126 |
| No log | 9.3333 | 56 | 0.4004 | 0.6491 | 0.4004 |
| No log | 9.6667 | 58 | 0.3997 | 0.6491 | 0.3997 |
| No log | 10.0 | 60 | 0.3972 | 0.6491 | 0.3972 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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