---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold5
  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_task7_fold5

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: 0.4813
- Qwk: 0.8159
- Mse: 0.4813

## 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    | 1.7829          | 0.0226 | 1.7829 |
| No log        | 0.0656 | 4    | 1.0550          | 0.3246 | 1.0550 |
| No log        | 0.0984 | 6    | 1.2058          | 0.3390 | 1.2058 |
| No log        | 0.1311 | 8    | 1.2897          | 0.4716 | 1.2897 |
| No log        | 0.1639 | 10   | 0.7738          | 0.6671 | 0.7738 |
| No log        | 0.1967 | 12   | 0.4801          | 0.6113 | 0.4801 |
| No log        | 0.2295 | 14   | 0.4704          | 0.6859 | 0.4704 |
| No log        | 0.2623 | 16   | 0.6162          | 0.7884 | 0.6162 |
| No log        | 0.2951 | 18   | 0.8233          | 0.7575 | 0.8233 |
| No log        | 0.3279 | 20   | 0.8253          | 0.7631 | 0.8253 |
| No log        | 0.3607 | 22   | 0.6816          | 0.7772 | 0.6816 |
| No log        | 0.3934 | 24   | 0.6169          | 0.7875 | 0.6169 |
| No log        | 0.4262 | 26   | 0.6070          | 0.7969 | 0.6070 |
| No log        | 0.4590 | 28   | 0.5939          | 0.7990 | 0.5939 |
| No log        | 0.4918 | 30   | 0.5668          | 0.7902 | 0.5668 |
| No log        | 0.5246 | 32   | 0.5026          | 0.8069 | 0.5026 |
| No log        | 0.5574 | 34   | 0.5333          | 0.7935 | 0.5333 |
| No log        | 0.5902 | 36   | 0.6348          | 0.8099 | 0.6348 |
| No log        | 0.6230 | 38   | 0.7737          | 0.7826 | 0.7737 |
| No log        | 0.6557 | 40   | 0.7722          | 0.7861 | 0.7722 |
| No log        | 0.6885 | 42   | 0.6762          | 0.7874 | 0.6762 |
| No log        | 0.7213 | 44   | 0.5498          | 0.8024 | 0.5498 |
| No log        | 0.7541 | 46   | 0.4936          | 0.8014 | 0.4936 |
| No log        | 0.7869 | 48   | 0.4728          | 0.8025 | 0.4728 |
| No log        | 0.8197 | 50   | 0.4592          | 0.8048 | 0.4592 |
| No log        | 0.8525 | 52   | 0.4339          | 0.8081 | 0.4339 |
| No log        | 0.8852 | 54   | 0.4330          | 0.8048 | 0.4330 |
| No log        | 0.9180 | 56   | 0.4495          | 0.8048 | 0.4495 |
| No log        | 0.9508 | 58   | 0.4689          | 0.8114 | 0.4689 |
| No log        | 0.9836 | 60   | 0.4813          | 0.8159 | 0.4813 |


### Framework versions

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