---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_fold6
  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_fold6

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: 0.2541
- Qwk: 0.2373
- Mse: 0.2539

## 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        | 0.0333 | 2    | 0.3369          | 0.1172 | 0.3369 |
| No log        | 0.0667 | 4    | 0.4978          | 0.3977 | 0.4978 |
| No log        | 0.1    | 6    | 0.4733          | 0.3519 | 0.4733 |
| No log        | 0.1333 | 8    | 0.3071          | 0.0964 | 0.3071 |
| No log        | 0.1667 | 10   | 0.2732          | 0.1475 | 0.2733 |
| No log        | 0.2    | 12   | 0.2941          | 0.2325 | 0.2943 |
| No log        | 0.2333 | 14   | 0.2888          | 0.2076 | 0.2890 |
| No log        | 0.2667 | 16   | 0.2781          | 0.2076 | 0.2782 |
| No log        | 0.3    | 18   | 0.3038          | 0.2583 | 0.3038 |
| No log        | 0.3333 | 20   | 0.3106          | 0.2515 | 0.3105 |
| No log        | 0.3667 | 22   | 0.2932          | 0.2691 | 0.2930 |
| No log        | 0.4    | 24   | 0.2674          | 0.2167 | 0.2669 |
| No log        | 0.4333 | 26   | 0.2571          | 0.2325 | 0.2564 |
| No log        | 0.4667 | 28   | 0.2516          | 0.2282 | 0.2509 |
| No log        | 0.5    | 30   | 0.2513          | 0.2352 | 0.2506 |
| No log        | 0.5333 | 32   | 0.2536          | 0.2414 | 0.2531 |
| No log        | 0.5667 | 34   | 0.2678          | 0.2304 | 0.2674 |
| No log        | 0.6    | 36   | 0.2837          | 0.2448 | 0.2832 |
| No log        | 0.6333 | 38   | 0.3006          | 0.2257 | 0.3000 |
| No log        | 0.6667 | 40   | 0.3090          | 0.2226 | 0.3084 |
| No log        | 0.7    | 42   | 0.2975          | 0.2250 | 0.2971 |
| No log        | 0.7333 | 44   | 0.2897          | 0.2572 | 0.2894 |
| No log        | 0.7667 | 46   | 0.2878          | 0.2779 | 0.2875 |
| No log        | 0.8    | 48   | 0.2796          | 0.2786 | 0.2794 |
| No log        | 0.8333 | 50   | 0.2697          | 0.2649 | 0.2695 |
| No log        | 0.8667 | 52   | 0.2639          | 0.2578 | 0.2637 |
| No log        | 0.9    | 54   | 0.2596          | 0.2436 | 0.2594 |
| No log        | 0.9333 | 56   | 0.2564          | 0.2443 | 0.2562 |
| No log        | 0.9667 | 58   | 0.2544          | 0.2373 | 0.2543 |
| No log        | 1.0    | 60   | 0.2541          | 0.2373 | 0.2539 |


### Framework versions

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