---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold2
  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_vocabulary_task4_fold2

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: 1.4786
- Qwk: 0.0414
- Mse: 1.4653

## 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        | 0.0282 | 2    | 7.1347          | 0.0039  | 7.1562 |
| No log        | 0.0563 | 4    | 3.4551          | 0.0095  | 3.4688 |
| No log        | 0.0845 | 6    | 1.4618          | 0.0540  | 1.4670 |
| No log        | 0.1127 | 8    | 0.7258          | -0.0161 | 0.7252 |
| No log        | 0.1408 | 10   | 0.7701          | -0.0572 | 0.7709 |
| No log        | 0.1690 | 12   | 1.0250          | -0.0732 | 1.0315 |
| No log        | 0.1972 | 14   | 0.7175          | -0.0348 | 0.7181 |
| No log        | 0.2254 | 16   | 0.6112          | 0.0365  | 0.6099 |
| No log        | 0.2535 | 18   | 0.5589          | 0.0853  | 0.5572 |
| No log        | 0.2817 | 20   | 0.5273          | 0.0940  | 0.5251 |
| No log        | 0.3099 | 22   | 0.5480          | 0.0098  | 0.5432 |
| No log        | 0.3380 | 24   | 0.7106          | 0.0098  | 0.7034 |
| No log        | 0.3662 | 26   | 0.9344          | 0.0202  | 0.9253 |
| No log        | 0.3944 | 28   | 1.1676          | 0.1456  | 1.1562 |
| No log        | 0.4225 | 30   | 1.2628          | 0.1249  | 1.2507 |
| No log        | 0.4507 | 32   | 1.0404          | 0.1021  | 1.0296 |
| No log        | 0.4789 | 34   | 1.0395          | 0.1112  | 1.0292 |
| No log        | 0.5070 | 36   | 1.1961          | 0.1187  | 1.1868 |
| No log        | 0.5352 | 38   | 1.1022          | 0.1439  | 1.0951 |
| No log        | 0.5634 | 40   | 0.8840          | -0.0190 | 0.8791 |
| No log        | 0.5915 | 42   | 0.7380          | -0.0094 | 0.7349 |
| No log        | 0.6197 | 44   | 0.7231          | -0.0336 | 0.7198 |
| No log        | 0.6479 | 46   | 0.7578          | -0.0424 | 0.7530 |
| No log        | 0.6761 | 48   | 0.9652          | -0.0262 | 0.9566 |
| No log        | 0.7042 | 50   | 1.1114          | -0.1252 | 1.1008 |
| No log        | 0.7324 | 52   | 1.2059          | 0.0116  | 1.1948 |
| No log        | 0.7606 | 54   | 1.3383          | -0.0009 | 1.3265 |
| No log        | 0.7887 | 56   | 1.4278          | 0.0369  | 1.4156 |
| No log        | 0.8169 | 58   | 1.4154          | 0.0855  | 1.4032 |
| No log        | 0.8451 | 60   | 1.3691          | 0.1138  | 1.3571 |
| No log        | 0.8732 | 62   | 1.3963          | 0.0789  | 1.3841 |
| No log        | 0.9014 | 64   | 1.4466          | 0.0640  | 1.4340 |
| No log        | 0.9296 | 66   | 1.4766          | 0.0358  | 1.4637 |
| No log        | 0.9577 | 68   | 1.4844          | 0.0203  | 1.4712 |
| No log        | 0.9859 | 70   | 1.4786          | 0.0414  | 1.4653 |


### Framework versions

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