---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task2_fold0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_relevance_task2_fold0

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: 0.2433
- Qwk: 0.0809
- Mse: 0.2430

## 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    | 0.5429          | 0.0139  | 0.5422 |
| No log        | 0.0702 | 4    | 0.2881          | -0.0033 | 0.2878 |
| No log        | 0.1053 | 6    | 0.2552          | 0.0037  | 0.2550 |
| No log        | 0.1404 | 8    | 0.2756          | 0.0363  | 0.2756 |
| No log        | 0.1754 | 10   | 0.2731          | 0.0358  | 0.2730 |
| No log        | 0.2105 | 12   | 0.2492          | 0.0319  | 0.2491 |
| No log        | 0.2456 | 14   | 0.2366          | 0.0426  | 0.2365 |
| No log        | 0.2807 | 16   | 0.2435          | 0.0674  | 0.2435 |
| No log        | 0.3158 | 18   | 0.2530          | 0.0698  | 0.2530 |
| No log        | 0.3509 | 20   | 0.2490          | 0.0774  | 0.2489 |
| No log        | 0.3860 | 22   | 0.2454          | 0.0743  | 0.2454 |
| No log        | 0.4211 | 24   | 0.2447          | 0.0740  | 0.2446 |
| No log        | 0.4561 | 26   | 0.2496          | 0.0713  | 0.2494 |
| No log        | 0.4912 | 28   | 0.2557          | 0.0679  | 0.2553 |
| No log        | 0.5263 | 30   | 0.2693          | 0.0721  | 0.2689 |
| No log        | 0.5614 | 32   | 0.2903          | 0.0721  | 0.2898 |
| No log        | 0.5965 | 34   | 0.2872          | 0.0721  | 0.2868 |
| No log        | 0.6316 | 36   | 0.2801          | 0.0787  | 0.2797 |
| No log        | 0.6667 | 38   | 0.2824          | 0.0809  | 0.2819 |
| No log        | 0.7018 | 40   | 0.2708          | 0.0809  | 0.2704 |
| No log        | 0.7368 | 42   | 0.2675          | 0.0809  | 0.2672 |
| No log        | 0.7719 | 44   | 0.2680          | 0.0809  | 0.2677 |
| No log        | 0.8070 | 46   | 0.2603          | 0.0809  | 0.2600 |
| No log        | 0.8421 | 48   | 0.2536          | 0.0809  | 0.2534 |
| No log        | 0.8772 | 50   | 0.2489          | 0.0809  | 0.2487 |
| No log        | 0.9123 | 52   | 0.2470          | 0.0809  | 0.2467 |
| No log        | 0.9474 | 54   | 0.2448          | 0.0809  | 0.2446 |
| No log        | 0.9825 | 56   | 0.2433          | 0.0809  | 0.2430 |


### Framework versions

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