---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_task1_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: 0.2814
- Qwk: 0.1577
- Mse: 0.2814

## 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    | 0.5567          | -0.0320 | 0.5567 |
| No log        | 0.0656 | 4    | 0.5564          | -0.0102 | 0.5564 |
| No log        | 0.0984 | 6    | 0.5081          | 0.0304  | 0.5081 |
| No log        | 0.1311 | 8    | 0.4677          | 0.0304  | 0.4677 |
| No log        | 0.1639 | 10   | 0.4282          | 0.0400  | 0.4282 |
| No log        | 0.1967 | 12   | 0.4239          | 0.0496  | 0.4239 |
| No log        | 0.2295 | 14   | 0.4171          | 0.0384  | 0.4171 |
| No log        | 0.2623 | 16   | 0.3868          | 0.0496  | 0.3868 |
| No log        | 0.2951 | 18   | 0.3678          | 0.0690  | 0.3678 |
| No log        | 0.3279 | 20   | 0.3448          | 0.0596  | 0.3448 |
| No log        | 0.3607 | 22   | 0.3295          | 0.0877  | 0.3295 |
| No log        | 0.3934 | 24   | 0.3190          | 0.0877  | 0.3190 |
| No log        | 0.4262 | 26   | 0.3166          | 0.0969  | 0.3166 |
| No log        | 0.4590 | 28   | 0.3135          | 0.0969  | 0.3135 |
| No log        | 0.4918 | 30   | 0.3075          | 0.0969  | 0.3075 |
| No log        | 0.5246 | 32   | 0.3014          | 0.1139  | 0.3014 |
| No log        | 0.5574 | 34   | 0.2971          | 0.1139  | 0.2971 |
| No log        | 0.5902 | 36   | 0.2957          | 0.1048  | 0.2957 |
| No log        | 0.6230 | 38   | 0.2937          | 0.1048  | 0.2937 |
| No log        | 0.6557 | 40   | 0.2888          | 0.1139  | 0.2888 |
| No log        | 0.6885 | 42   | 0.2867          | 0.1139  | 0.2867 |
| No log        | 0.7213 | 44   | 0.2857          | 0.1139  | 0.2857 |
| No log        | 0.7541 | 46   | 0.2847          | 0.1321  | 0.2847 |
| No log        | 0.7869 | 48   | 0.2833          | 0.1577  | 0.2833 |
| No log        | 0.8197 | 50   | 0.2826          | 0.1577  | 0.2826 |
| No log        | 0.8525 | 52   | 0.2822          | 0.1577  | 0.2822 |
| No log        | 0.8852 | 54   | 0.2805          | 0.1577  | 0.2805 |
| No log        | 0.9180 | 56   | 0.2810          | 0.1667  | 0.2810 |
| No log        | 0.9508 | 58   | 0.2816          | 0.1667  | 0.2816 |
| No log        | 0.9836 | 60   | 0.2814          | 0.1577  | 0.2814 |


### Framework versions

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