---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task4_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_task4_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: 0.2131
- Qwk: 0.2800
- Mse: 0.2131

## 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        | 0.0290 | 2    | 1.5877          | 0.0071 | 1.5877 |
| No log        | 0.0580 | 4    | 0.7523          | 0.0797 | 0.7523 |
| No log        | 0.0870 | 6    | 0.4972          | 0.2325 | 0.4972 |
| No log        | 0.1159 | 8    | 0.4973          | 0.2818 | 0.4973 |
| No log        | 0.1449 | 10   | 0.3782          | 0.2548 | 0.3782 |
| No log        | 0.1739 | 12   | 0.3328          | 0.2641 | 0.3328 |
| No log        | 0.2029 | 14   | 0.2810          | 0.2677 | 0.2810 |
| No log        | 0.2319 | 16   | 0.2749          | 0.2717 | 0.2749 |
| No log        | 0.2609 | 18   | 0.2745          | 0.2169 | 0.2745 |
| No log        | 0.2899 | 20   | 0.2605          | 0.2602 | 0.2605 |
| No log        | 0.3188 | 22   | 0.2453          | 0.2528 | 0.2453 |
| No log        | 0.3478 | 24   | 0.2442          | 0.2459 | 0.2442 |
| No log        | 0.3768 | 26   | 0.2468          | 0.2763 | 0.2468 |
| No log        | 0.4058 | 28   | 0.2595          | 0.2864 | 0.2595 |
| No log        | 0.4348 | 30   | 0.2694          | 0.2852 | 0.2694 |
| No log        | 0.4638 | 32   | 0.2515          | 0.2790 | 0.2515 |
| No log        | 0.4928 | 34   | 0.2280          | 0.3189 | 0.2280 |
| No log        | 0.5217 | 36   | 0.2522          | 0.4255 | 0.2522 |
| No log        | 0.5507 | 38   | 0.2616          | 0.3794 | 0.2616 |
| No log        | 0.5797 | 40   | 0.2487          | 0.2990 | 0.2487 |
| No log        | 0.6087 | 42   | 0.2345          | 0.2490 | 0.2345 |
| No log        | 0.6377 | 44   | 0.2296          | 0.2615 | 0.2296 |
| No log        | 0.6667 | 46   | 0.2262          | 0.2654 | 0.2262 |
| No log        | 0.6957 | 48   | 0.2230          | 0.2654 | 0.2230 |
| No log        | 0.7246 | 50   | 0.2198          | 0.2691 | 0.2198 |
| No log        | 0.7536 | 52   | 0.2182          | 0.2728 | 0.2182 |
| No log        | 0.7826 | 54   | 0.2166          | 0.2763 | 0.2166 |
| No log        | 0.8116 | 56   | 0.2162          | 0.2763 | 0.2162 |
| No log        | 0.8406 | 58   | 0.2158          | 0.2798 | 0.2158 |
| No log        | 0.8696 | 60   | 0.2144          | 0.2798 | 0.2144 |
| No log        | 0.8986 | 62   | 0.2129          | 0.2798 | 0.2129 |
| No log        | 0.9275 | 64   | 0.2125          | 0.2763 | 0.2125 |
| No log        | 0.9565 | 66   | 0.2128          | 0.2728 | 0.2128 |
| No log        | 0.9855 | 68   | 0.2131          | 0.2800 | 0.2131 |


### Framework versions

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