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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task6_fold5
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_cross_relevance_task6_fold5
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: 0.1873
- Qwk: 0.3574
- Mse: 0.1873
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log | 0.0328 | 2 | 1.7597 | 0.0 | 1.7597 |
| No log | 0.0656 | 4 | 0.5562 | 0.1908 | 0.5562 |
| No log | 0.0984 | 6 | 0.1992 | 0.3305 | 0.1992 |
| No log | 0.1311 | 8 | 0.2333 | 0.4006 | 0.2333 |
| No log | 0.1639 | 10 | 0.2174 | 0.2998 | 0.2174 |
| No log | 0.1967 | 12 | 0.2464 | 0.2998 | 0.2464 |
| No log | 0.2295 | 14 | 0.2503 | 0.3279 | 0.2503 |
| No log | 0.2623 | 16 | 0.2466 | 0.3305 | 0.2466 |
| No log | 0.2951 | 18 | 0.2107 | 0.3279 | 0.2107 |
| No log | 0.3279 | 20 | 0.1965 | 0.3251 | 0.1965 |
| No log | 0.3607 | 22 | 0.1973 | 0.3292 | 0.1973 |
| No log | 0.3934 | 24 | 0.1930 | 0.3318 | 0.1930 |
| No log | 0.4262 | 26 | 0.1955 | 0.3379 | 0.1955 |
| No log | 0.4590 | 28 | 0.1901 | 0.3379 | 0.1901 |
| No log | 0.4918 | 30 | 0.1893 | 0.3343 | 0.1893 |
| No log | 0.5246 | 32 | 0.1861 | 0.3279 | 0.1861 |
| No log | 0.5574 | 34 | 0.1931 | 0.3453 | 0.1931 |
| No log | 0.5902 | 36 | 0.2045 | 0.5036 | 0.2045 |
| No log | 0.6230 | 38 | 0.2065 | 0.5858 | 0.2065 |
| No log | 0.6557 | 40 | 0.1891 | 0.4899 | 0.1891 |
| No log | 0.6885 | 42 | 0.1813 | 0.3696 | 0.1813 |
| No log | 0.7213 | 44 | 0.2125 | 0.3665 | 0.2125 |
| No log | 0.7541 | 46 | 0.2717 | 0.3526 | 0.2717 |
| No log | 0.7869 | 48 | 0.3306 | 0.3344 | 0.3306 |
| No log | 0.8197 | 50 | 0.3275 | 0.3475 | 0.3275 |
| No log | 0.8525 | 52 | 0.2862 | 0.3587 | 0.2862 |
| No log | 0.8852 | 54 | 0.2419 | 0.3643 | 0.2419 |
| No log | 0.9180 | 56 | 0.2102 | 0.3614 | 0.2102 |
| No log | 0.9508 | 58 | 0.1933 | 0.3590 | 0.1933 |
| No log | 0.9836 | 60 | 0.1873 | 0.3574 | 0.1873 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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