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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_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_relevance_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: 0.1845
- Qwk: 0.3789
- Mse: 0.1845
## 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 | 0.7186 | -0.0682 | 0.7186 |
| No log | 0.6667 | 4 | 0.2563 | 0.0 | 0.2563 |
| No log | 1.0 | 6 | 0.1977 | 0.0551 | 0.1977 |
| No log | 1.3333 | 8 | 0.1845 | 0.2373 | 0.1845 |
| No log | 1.6667 | 10 | 0.1961 | 0.2361 | 0.1961 |
| No log | 2.0 | 12 | 0.2108 | 0.1960 | 0.2108 |
| No log | 2.3333 | 14 | 0.2096 | 0.2347 | 0.2096 |
| No log | 2.6667 | 16 | 0.2117 | 0.2814 | 0.2117 |
| No log | 3.0 | 18 | 0.2125 | 0.2814 | 0.2125 |
| No log | 3.3333 | 20 | 0.2086 | 0.3789 | 0.2086 |
| No log | 3.6667 | 22 | 0.2136 | 0.2547 | 0.2136 |
| No log | 4.0 | 24 | 0.2106 | 0.3293 | 0.2106 |
| No log | 4.3333 | 26 | 0.1994 | 0.3293 | 0.1994 |
| No log | 4.6667 | 28 | 0.1978 | 0.1477 | 0.1978 |
| No log | 5.0 | 30 | 0.2011 | 0.2353 | 0.2011 |
| No log | 5.3333 | 32 | 0.2091 | 0.2258 | 0.2091 |
| No log | 5.6667 | 34 | 0.2215 | 0.2763 | 0.2215 |
| No log | 6.0 | 36 | 0.2177 | 0.2763 | 0.2177 |
| No log | 6.3333 | 38 | 0.2103 | 0.2763 | 0.2103 |
| No log | 6.6667 | 40 | 0.1968 | 0.4304 | 0.1968 |
| No log | 7.0 | 42 | 0.1868 | 0.3789 | 0.1868 |
| No log | 7.3333 | 44 | 0.1820 | 0.3789 | 0.1820 |
| No log | 7.6667 | 46 | 0.1813 | 0.3789 | 0.1813 |
| No log | 8.0 | 48 | 0.1828 | 0.3789 | 0.1828 |
| No log | 8.3333 | 50 | 0.1865 | 0.3789 | 0.1865 |
| No log | 8.6667 | 52 | 0.1900 | 0.4304 | 0.1900 |
| No log | 9.0 | 54 | 0.1886 | 0.4304 | 0.1886 |
| No log | 9.3333 | 56 | 0.1873 | 0.3789 | 0.1873 |
| No log | 9.6667 | 58 | 0.1853 | 0.3789 | 0.1853 |
| No log | 10.0 | 60 | 0.1845 | 0.3789 | 0.1845 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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