---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_vocabulary_task7_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: 0.7372
- Qwk: 0.0
- Mse: 0.7250

## 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        | 0.0317 | 2    | 3.4222          | 0.0005  | 3.4448 |
| No log        | 0.0635 | 4    | 0.8344          | -0.0075 | 0.8385 |
| No log        | 0.0952 | 6    | 0.6004          | 0.0456  | 0.5963 |
| No log        | 0.1270 | 8    | 0.5812          | -0.0227 | 0.5744 |
| No log        | 0.1587 | 10   | 0.6585          | 0.0     | 0.6498 |
| No log        | 0.1905 | 12   | 0.6873          | 0.0     | 0.6781 |
| No log        | 0.2222 | 14   | 0.6603          | 0.0     | 0.6514 |
| No log        | 0.2540 | 16   | 0.5985          | -0.0496 | 0.5919 |
| No log        | 0.2857 | 18   | 0.5749          | -0.0344 | 0.5697 |
| No log        | 0.3175 | 20   | 0.5691          | -0.0546 | 0.5649 |
| No log        | 0.3492 | 22   | 0.5753          | -0.0344 | 0.5700 |
| No log        | 0.3810 | 24   | 0.6027          | -0.0886 | 0.5953 |
| No log        | 0.4127 | 26   | 0.6013          | -0.0886 | 0.5936 |
| No log        | 0.4444 | 28   | 0.6360          | -0.0252 | 0.6265 |
| No log        | 0.4762 | 30   | 0.6499          | -0.0252 | 0.6399 |
| No log        | 0.5079 | 32   | 0.7649          | 0.0     | 0.7525 |
| No log        | 0.5397 | 34   | 0.8350          | 0.0     | 0.8221 |
| No log        | 0.5714 | 36   | 0.8330          | 0.0     | 0.8214 |
| No log        | 0.6032 | 38   | 0.7620          | 0.0     | 0.7524 |
| No log        | 0.6349 | 40   | 0.7292          | 0.0     | 0.7198 |
| No log        | 0.6667 | 42   | 0.6967          | 0.0     | 0.6875 |
| No log        | 0.6984 | 44   | 0.7020          | 0.0     | 0.6922 |
| No log        | 0.7302 | 46   | 0.7157          | 0.0     | 0.7048 |
| No log        | 0.7619 | 48   | 0.7198          | 0.0     | 0.7083 |
| No log        | 0.7937 | 50   | 0.6970          | 0.0     | 0.6856 |
| No log        | 0.8254 | 52   | 0.6743          | 0.0     | 0.6632 |
| No log        | 0.8571 | 54   | 0.6647          | 0.0     | 0.6537 |
| No log        | 0.8889 | 56   | 0.6819          | 0.0     | 0.6706 |
| No log        | 0.9206 | 58   | 0.7064          | 0.0     | 0.6946 |
| No log        | 0.9524 | 60   | 0.7251          | 0.0     | 0.7130 |
| No log        | 0.9841 | 62   | 0.7372          | 0.0     | 0.7250 |


### Framework versions

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