---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_task1_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: 0.1907
- Qwk: 0.0246
- Mse: 0.1907

## 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    | 1.1829          | -0.0050 | 1.1829 |
| No log        | 0.0702 | 4    | 0.2409          | 0.0099  | 0.2409 |
| No log        | 0.1053 | 6    | 0.1676          | -0.0484 | 0.1676 |
| No log        | 0.1404 | 8    | 0.1570          | 0.0130  | 0.1570 |
| No log        | 0.1754 | 10   | 0.3161          | 0.0173  | 0.3161 |
| No log        | 0.2105 | 12   | 0.6111          | 0.0144  | 0.6111 |
| No log        | 0.2456 | 14   | 0.4643          | 0.0505  | 0.4643 |
| No log        | 0.2807 | 16   | 0.3698          | 0.0345  | 0.3698 |
| No log        | 0.3158 | 18   | 0.2920          | 0.0181  | 0.2920 |
| No log        | 0.3509 | 20   | 0.2091          | 0.0235  | 0.2091 |
| No log        | 0.3860 | 22   | 0.1792          | 0.0092  | 0.1792 |
| No log        | 0.4211 | 24   | 0.1670          | 0.0386  | 0.1670 |
| No log        | 0.4561 | 26   | 0.1654          | 0.0258  | 0.1654 |
| No log        | 0.4912 | 28   | 0.1730          | 0.0081  | 0.1730 |
| No log        | 0.5263 | 30   | 0.1851          | 0.0141  | 0.1851 |
| No log        | 0.5614 | 32   | 0.2064          | 0.0092  | 0.2064 |
| No log        | 0.5965 | 34   | 0.2253          | 0.0270  | 0.2253 |
| No log        | 0.6316 | 36   | 0.2300          | 0.0355  | 0.2300 |
| No log        | 0.6667 | 38   | 0.2391          | 0.0339  | 0.2391 |
| No log        | 0.7018 | 40   | 0.2358          | 0.0339  | 0.2358 |
| No log        | 0.7368 | 42   | 0.2370          | 0.0300  | 0.2370 |
| No log        | 0.7719 | 44   | 0.2370          | 0.0361  | 0.2370 |
| No log        | 0.8070 | 46   | 0.2312          | 0.0323  | 0.2312 |
| No log        | 0.8421 | 48   | 0.2215          | 0.0323  | 0.2215 |
| No log        | 0.8772 | 50   | 0.2101          | 0.0358  | 0.2101 |
| No log        | 0.9123 | 52   | 0.2006          | 0.0212  | 0.2006 |
| No log        | 0.9474 | 54   | 0.1943          | 0.0246  | 0.1943 |
| No log        | 0.9825 | 56   | 0.1907          | 0.0246  | 0.1907 |


### Framework versions

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