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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task5_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_mechanics_task5_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: 0.6569
- Qwk: 0.7179
- Mse: 0.6569
## 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 | 1.9122 | 0.0290 | 1.9122 |
| No log | 0.6667 | 4 | 0.8359 | 0.0 | 0.8359 |
| No log | 1.0 | 6 | 0.5865 | 0.3478 | 0.5865 |
| No log | 1.3333 | 8 | 0.5525 | 0.1739 | 0.5525 |
| No log | 1.6667 | 10 | 0.5082 | 0.25 | 0.5082 |
| No log | 2.0 | 12 | 0.5342 | 0.3636 | 0.5342 |
| No log | 2.3333 | 14 | 0.5194 | 0.3478 | 0.5194 |
| No log | 2.6667 | 16 | 0.5004 | 0.5714 | 0.5004 |
| No log | 3.0 | 18 | 0.5279 | 0.4848 | 0.5279 |
| No log | 3.3333 | 20 | 0.5491 | 0.4848 | 0.5491 |
| No log | 3.6667 | 22 | 0.6345 | 0.6154 | 0.6345 |
| No log | 4.0 | 24 | 0.7154 | 0.6111 | 0.7154 |
| No log | 4.3333 | 26 | 0.8157 | 0.5882 | 0.8157 |
| No log | 4.6667 | 28 | 0.8595 | 0.6667 | 0.8595 |
| No log | 5.0 | 30 | 0.7144 | 0.6842 | 0.7144 |
| No log | 5.3333 | 32 | 0.6153 | 0.6 | 0.6153 |
| No log | 5.6667 | 34 | 0.6974 | 0.6154 | 0.6974 |
| No log | 6.0 | 36 | 0.7895 | 0.7 | 0.7895 |
| No log | 6.3333 | 38 | 0.8393 | 0.6667 | 0.8393 |
| No log | 6.6667 | 40 | 0.8578 | 0.6667 | 0.8578 |
| No log | 7.0 | 42 | 0.8027 | 0.6667 | 0.8027 |
| No log | 7.3333 | 44 | 0.7182 | 0.6667 | 0.7182 |
| No log | 7.6667 | 46 | 0.6647 | 0.6842 | 0.6647 |
| No log | 8.0 | 48 | 0.6573 | 0.6 | 0.6573 |
| No log | 8.3333 | 50 | 0.6541 | 0.6842 | 0.6541 |
| No log | 8.6667 | 52 | 0.6499 | 0.6842 | 0.6499 |
| No log | 9.0 | 54 | 0.6477 | 0.7179 | 0.6477 |
| No log | 9.3333 | 56 | 0.6501 | 0.7179 | 0.6501 |
| No log | 9.6667 | 58 | 0.6545 | 0.7179 | 0.6545 |
| No log | 10.0 | 60 | 0.6569 | 0.7179 | 0.6569 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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