---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_task1_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: 0.1955
- Qwk: 0.3846
- Mse: 0.1955

## 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    | 0.3613          | 0.2826 | 0.3613 |
| No log        | 0.0702 | 4    | 0.4116          | 0.5484 | 0.4116 |
| No log        | 0.1053 | 6    | 0.2771          | 0.4880 | 0.2771 |
| No log        | 0.1404 | 8    | 0.2157          | 0.3346 | 0.2157 |
| No log        | 0.1754 | 10   | 0.2149          | 0.3324 | 0.2149 |
| No log        | 0.2105 | 12   | 0.2119          | 0.3302 | 0.2119 |
| No log        | 0.2456 | 14   | 0.2146          | 0.3336 | 0.2146 |
| No log        | 0.2807 | 16   | 0.2085          | 0.3319 | 0.2085 |
| No log        | 0.3158 | 18   | 0.2118          | 0.3641 | 0.2118 |
| No log        | 0.3509 | 20   | 0.2261          | 0.4439 | 0.2261 |
| No log        | 0.3860 | 22   | 0.2392          | 0.4713 | 0.2392 |
| No log        | 0.4211 | 24   | 0.2344          | 0.4095 | 0.2344 |
| No log        | 0.4561 | 26   | 0.2151          | 0.3602 | 0.2151 |
| No log        | 0.4912 | 28   | 0.2029          | 0.3304 | 0.2029 |
| No log        | 0.5263 | 30   | 0.2041          | 0.3227 | 0.2041 |
| No log        | 0.5614 | 32   | 0.2085          | 0.3015 | 0.2085 |
| No log        | 0.5965 | 34   | 0.2114          | 0.2998 | 0.2114 |
| No log        | 0.6316 | 36   | 0.2114          | 0.2998 | 0.2114 |
| No log        | 0.6667 | 38   | 0.2041          | 0.3156 | 0.2041 |
| No log        | 0.7018 | 40   | 0.1985          | 0.3186 | 0.1985 |
| No log        | 0.7368 | 42   | 0.1948          | 0.3490 | 0.1948 |
| No log        | 0.7719 | 44   | 0.1925          | 0.3543 | 0.1925 |
| No log        | 0.8070 | 46   | 0.1939          | 0.3667 | 0.1939 |
| No log        | 0.8421 | 48   | 0.1928          | 0.3684 | 0.1928 |
| No log        | 0.8772 | 50   | 0.1932          | 0.3736 | 0.1932 |
| No log        | 0.9123 | 52   | 0.1942          | 0.3795 | 0.1942 |
| No log        | 0.9474 | 54   | 0.1952          | 0.3846 | 0.1952 |
| No log        | 0.9825 | 56   | 0.1955          | 0.3846 | 0.1955 |


### Framework versions

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