---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task7_fold6
  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_task7_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: 0.2712
- Qwk: 0.1915
- Mse: 0.2729

## 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        | 0.0328 | 2    | 0.5105          | 0.0254 | 0.5110 |
| No log        | 0.0656 | 4    | 0.3468          | 0.1105 | 0.3473 |
| No log        | 0.0984 | 6    | 0.3739          | 0.0623 | 0.3733 |
| No log        | 0.1311 | 8    | 0.4061          | 0.0623 | 0.4056 |
| No log        | 0.1639 | 10   | 0.3781          | 0.0714 | 0.3780 |
| No log        | 0.1967 | 12   | 0.3204          | 0.0732 | 0.3208 |
| No log        | 0.2295 | 14   | 0.2912          | 0.0732 | 0.2917 |
| No log        | 0.2623 | 16   | 0.2824          | 0.0732 | 0.2828 |
| No log        | 0.2951 | 18   | 0.2830          | 0.0924 | 0.2833 |
| No log        | 0.3279 | 20   | 0.2833          | 0.1116 | 0.2835 |
| No log        | 0.3607 | 22   | 0.2895          | 0.1022 | 0.2894 |
| No log        | 0.3934 | 24   | 0.3016          | 0.1520 | 0.3014 |
| No log        | 0.4262 | 26   | 0.3147          | 0.1588 | 0.3148 |
| No log        | 0.4590 | 28   | 0.3134          | 0.1666 | 0.3141 |
| No log        | 0.4918 | 30   | 0.3075          | 0.1679 | 0.3086 |
| No log        | 0.5246 | 32   | 0.3003          | 0.1679 | 0.3014 |
| No log        | 0.5574 | 34   | 0.2952          | 0.1891 | 0.2962 |
| No log        | 0.5902 | 36   | 0.2815          | 0.1835 | 0.2826 |
| No log        | 0.6230 | 38   | 0.2722          | 0.1890 | 0.2731 |
| No log        | 0.6557 | 40   | 0.2672          | 0.1973 | 0.2681 |
| No log        | 0.6885 | 42   | 0.2631          | 0.2056 | 0.2644 |
| No log        | 0.7213 | 44   | 0.2625          | 0.2056 | 0.2639 |
| No log        | 0.7541 | 46   | 0.2628          | 0.1939 | 0.2643 |
| No log        | 0.7869 | 48   | 0.2640          | 0.1746 | 0.2657 |
| No log        | 0.8197 | 50   | 0.2654          | 0.1804 | 0.2671 |
| No log        | 0.8525 | 52   | 0.2657          | 0.2023 | 0.2674 |
| No log        | 0.8852 | 54   | 0.2677          | 0.1915 | 0.2694 |
| No log        | 0.9180 | 56   | 0.2701          | 0.1915 | 0.2718 |
| No log        | 0.9508 | 58   | 0.2708          | 0.1915 | 0.2725 |
| No log        | 0.9836 | 60   | 0.2712          | 0.1915 | 0.2729 |


### Framework versions

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