---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task7_fold4
  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_task7_fold4

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: 0.4178
- Qwk: 0.3096
- Mse: 0.4178

## 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        | 0.0351 | 2    | 1.2442          | 0.0023 | 1.2442 |
| No log        | 0.0702 | 4    | 0.5486          | 0.1737 | 0.5486 |
| No log        | 0.1053 | 6    | 0.4401          | 0.2092 | 0.4401 |
| No log        | 0.1404 | 8    | 0.6085          | 0.3448 | 0.6085 |
| No log        | 0.1754 | 10   | 0.5312          | 0.2261 | 0.5312 |
| No log        | 0.2105 | 12   | 0.4802          | 0.1025 | 0.4802 |
| No log        | 0.2456 | 14   | 0.4993          | 0.0823 | 0.4993 |
| No log        | 0.2807 | 16   | 0.5735          | 0.2037 | 0.5735 |
| No log        | 0.3158 | 18   | 0.5919          | 0.1336 | 0.5919 |
| No log        | 0.3509 | 20   | 0.5961          | 0.1778 | 0.5961 |
| No log        | 0.3860 | 22   | 0.5618          | 0.1936 | 0.5618 |
| No log        | 0.4211 | 24   | 0.4983          | 0.1014 | 0.4983 |
| No log        | 0.4561 | 26   | 0.4610          | 0.0823 | 0.4610 |
| No log        | 0.4912 | 28   | 0.4379          | 0.0823 | 0.4379 |
| No log        | 0.5263 | 30   | 0.4243          | 0.0823 | 0.4243 |
| No log        | 0.5614 | 32   | 0.4112          | 0.0823 | 0.4112 |
| No log        | 0.5965 | 34   | 0.4065          | 0.0986 | 0.4065 |
| No log        | 0.6316 | 36   | 0.4065          | 0.1147 | 0.4065 |
| No log        | 0.6667 | 38   | 0.4002          | 0.1147 | 0.4002 |
| No log        | 0.7018 | 40   | 0.3916          | 0.1147 | 0.3916 |
| No log        | 0.7368 | 42   | 0.3875          | 0.1718 | 0.3875 |
| No log        | 0.7719 | 44   | 0.3871          | 0.1718 | 0.3871 |
| No log        | 0.8070 | 46   | 0.3961          | 0.1945 | 0.3961 |
| No log        | 0.8421 | 48   | 0.4011          | 0.2573 | 0.4011 |
| No log        | 0.8772 | 50   | 0.4079          | 0.2869 | 0.4079 |
| No log        | 0.9123 | 52   | 0.4165          | 0.3089 | 0.4165 |
| No log        | 0.9474 | 54   | 0.4186          | 0.3096 | 0.4186 |
| No log        | 0.9825 | 56   | 0.4178          | 0.3096 | 0.4178 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1