---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold1
  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_fold1

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: 0.5474
- Qwk: 0.4497
- Mse: 0.5474

## 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    | 8.1440          | -0.0005 | 8.1440 |
| No log        | 0.0615 | 4    | 4.7743          | 0.0021  | 4.7743 |
| No log        | 0.0923 | 6    | 2.7118          | 0.0416  | 2.7118 |
| No log        | 0.1231 | 8    | 1.7150          | 0.0799  | 1.7150 |
| No log        | 0.1538 | 10   | 0.8541          | 0.1088  | 0.8541 |
| No log        | 0.1846 | 12   | 0.8601          | 0.1094  | 0.8601 |
| No log        | 0.2154 | 14   | 0.8470          | 0.1589  | 0.8470 |
| No log        | 0.2462 | 16   | 1.0145          | 0.1789  | 1.0145 |
| No log        | 0.2769 | 18   | 1.4913          | 0.1666  | 1.4913 |
| No log        | 0.3077 | 20   | 1.4930          | 0.2073  | 1.4930 |
| No log        | 0.3385 | 22   | 0.8055          | 0.3243  | 0.8055 |
| No log        | 0.3692 | 24   | 0.5508          | 0.4354  | 0.5508 |
| No log        | 0.4    | 26   | 0.6031          | 0.3790  | 0.6031 |
| No log        | 0.4308 | 28   | 0.5860          | 0.4121  | 0.5860 |
| No log        | 0.4615 | 30   | 0.6336          | 0.4190  | 0.6336 |
| No log        | 0.4923 | 32   | 0.9905          | 0.3071  | 0.9905 |
| No log        | 0.5231 | 34   | 1.0889          | 0.2932  | 1.0889 |
| No log        | 0.5538 | 36   | 0.8745          | 0.3389  | 0.8745 |
| No log        | 0.5846 | 38   | 0.7332          | 0.3681  | 0.7332 |
| No log        | 0.6154 | 40   | 0.6486          | 0.3927  | 0.6486 |
| No log        | 0.6462 | 42   | 0.6347          | 0.3914  | 0.6347 |
| No log        | 0.6769 | 44   | 0.6439          | 0.3923  | 0.6439 |
| No log        | 0.7077 | 46   | 0.6224          | 0.4042  | 0.6224 |
| No log        | 0.7385 | 48   | 0.6224          | 0.4075  | 0.6224 |
| No log        | 0.7692 | 50   | 0.5740          | 0.4350  | 0.5740 |
| No log        | 0.8    | 52   | 0.5606          | 0.4443  | 0.5606 |
| No log        | 0.8308 | 54   | 0.5580          | 0.4473  | 0.5580 |
| No log        | 0.8615 | 56   | 0.5443          | 0.4451  | 0.5443 |
| No log        | 0.8923 | 58   | 0.5430          | 0.4451  | 0.5430 |
| No log        | 0.9231 | 60   | 0.5370          | 0.4575  | 0.5370 |
| No log        | 0.9538 | 62   | 0.5412          | 0.4517  | 0.5412 |
| No log        | 0.9846 | 64   | 0.5474          | 0.4497  | 0.5474 |


### Framework versions

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