---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task3_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_task3_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: 1.2889
- Qwk: 0.1455
- Mse: 1.2889

## 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    | 8.9247          | 0.0     | 8.9247 |
| No log        | 0.0563 | 4    | 6.0585          | -0.0018 | 6.0585 |
| No log        | 0.0845 | 6    | 3.3683          | 0.0     | 3.3683 |
| No log        | 0.1127 | 8    | 1.9295          | 0.0353  | 1.9295 |
| No log        | 0.1408 | 10   | 1.1575          | 0.0     | 1.1575 |
| No log        | 0.1690 | 12   | 0.8179          | 0.0531  | 0.8179 |
| No log        | 0.1972 | 14   | 0.7602          | -0.0155 | 0.7602 |
| No log        | 0.2254 | 16   | 0.7582          | -0.0014 | 0.7582 |
| No log        | 0.2535 | 18   | 0.7660          | 0.0643  | 0.7660 |
| No log        | 0.2817 | 20   | 0.7464          | 0.0434  | 0.7464 |
| No log        | 0.3099 | 22   | 0.7568          | 0.0     | 0.7568 |
| No log        | 0.3380 | 24   | 0.7822          | 0.0     | 0.7822 |
| No log        | 0.3662 | 26   | 0.8311          | 0.0     | 0.8311 |
| No log        | 0.3944 | 28   | 0.8980          | 0.0     | 0.8980 |
| No log        | 0.4225 | 30   | 0.9093          | 0.0     | 0.9093 |
| No log        | 0.4507 | 32   | 0.8669          | 0.0     | 0.8669 |
| No log        | 0.4789 | 34   | 0.8507          | 0.0     | 0.8507 |
| No log        | 0.5070 | 36   | 0.8627          | 0.0     | 0.8627 |
| No log        | 0.5352 | 38   | 0.8443          | 0.0     | 0.8443 |
| No log        | 0.5634 | 40   | 0.8722          | 0.0     | 0.8722 |
| No log        | 0.5915 | 42   | 0.9229          | 0.0     | 0.9229 |
| No log        | 0.6197 | 44   | 0.9827          | 0.0     | 0.9827 |
| No log        | 0.6479 | 46   | 1.0396          | 0.0     | 1.0396 |
| No log        | 0.6761 | 48   | 1.1196          | 0.0     | 1.1196 |
| No log        | 0.7042 | 50   | 1.1654          | 0.0     | 1.1654 |
| No log        | 0.7324 | 52   | 1.1934          | 0.0086  | 1.1934 |
| No log        | 0.7606 | 54   | 1.2497          | 0.0603  | 1.2497 |
| No log        | 0.7887 | 56   | 1.2723          | 0.0272  | 1.2723 |
| No log        | 0.8169 | 58   | 1.2595          | 0.1040  | 1.2595 |
| No log        | 0.8451 | 60   | 1.2516          | 0.1696  | 1.2516 |
| No log        | 0.8732 | 62   | 1.2442          | 0.1807  | 1.2442 |
| No log        | 0.9014 | 64   | 1.2514          | 0.1696  | 1.2514 |
| No log        | 0.9296 | 66   | 1.2627          | 0.1524  | 1.2627 |
| No log        | 0.9577 | 68   | 1.2780          | 0.1455  | 1.2780 |
| No log        | 0.9859 | 70   | 1.2889          | 0.1455  | 1.2889 |


### Framework versions

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