---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task2_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_task2_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: 0.7896
- Qwk: -0.0578
- Mse: 0.7896

## 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        | 0.0308 | 2    | 8.5786          | 0.0     | 8.5786 |
| No log        | 0.0615 | 4    | 4.7361          | 0.0027  | 4.7361 |
| No log        | 0.0923 | 6    | 2.4849          | -0.0164 | 2.4849 |
| No log        | 0.1231 | 8    | 1.0682          | 0.0     | 1.0682 |
| No log        | 0.1538 | 10   | 1.0484          | -0.2071 | 1.0484 |
| No log        | 0.1846 | 12   | 1.1580          | -0.1541 | 1.1580 |
| No log        | 0.2154 | 14   | 0.7197          | 0.0071  | 0.7197 |
| No log        | 0.2462 | 16   | 0.7275          | 0.1341  | 0.7275 |
| No log        | 0.2769 | 18   | 0.8223          | 0.0676  | 0.8223 |
| No log        | 0.3077 | 20   | 0.8068          | 0.0447  | 0.8068 |
| No log        | 0.3385 | 22   | 0.7532          | -0.0157 | 0.7532 |
| No log        | 0.3692 | 24   | 0.7525          | -0.0155 | 0.7525 |
| No log        | 0.4    | 26   | 0.7808          | -0.0217 | 0.7808 |
| No log        | 0.4308 | 28   | 0.7874          | -0.0658 | 0.7874 |
| No log        | 0.4615 | 30   | 0.7780          | 0.0     | 0.7780 |
| No log        | 0.4923 | 32   | 0.8462          | 0.0     | 0.8462 |
| No log        | 0.5231 | 34   | 0.9212          | 0.0     | 0.9212 |
| No log        | 0.5538 | 36   | 0.9624          | 0.0     | 0.9624 |
| No log        | 0.5846 | 38   | 0.9977          | 0.0     | 0.9977 |
| No log        | 0.6154 | 40   | 0.9965          | 0.0     | 0.9965 |
| No log        | 0.6462 | 42   | 0.9605          | 0.0     | 0.9605 |
| No log        | 0.6769 | 44   | 0.8767          | 0.0     | 0.8767 |
| No log        | 0.7077 | 46   | 0.8153          | 0.0     | 0.8153 |
| No log        | 0.7385 | 48   | 0.7919          | 0.0     | 0.7919 |
| No log        | 0.7692 | 50   | 0.7850          | -0.0371 | 0.7850 |
| No log        | 0.8    | 52   | 0.7871          | -0.0777 | 0.7871 |
| No log        | 0.8308 | 54   | 0.7856          | -0.0777 | 0.7856 |
| No log        | 0.8615 | 56   | 0.7873          | -0.0777 | 0.7873 |
| No log        | 0.8923 | 58   | 0.7877          | -0.0578 | 0.7877 |
| No log        | 0.9231 | 60   | 0.7921          | -0.0777 | 0.7921 |
| No log        | 0.9538 | 62   | 0.7919          | -0.0777 | 0.7919 |
| No log        | 0.9846 | 64   | 0.7896          | -0.0578 | 0.7896 |


### Framework versions

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