---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task5_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_task5_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: 0.6937
- Qwk: 0.0
- Mse: 0.6827

## 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    | 4.6009          | 0.0009  | 4.6270 |
| No log        | 0.0635 | 4    | 1.4046          | -0.0070 | 1.4154 |
| No log        | 0.0952 | 6    | 0.7366          | -0.0031 | 0.7371 |
| No log        | 0.1270 | 8    | 0.6366          | -0.0370 | 0.6297 |
| No log        | 0.1587 | 10   | 0.7085          | -0.0259 | 0.6993 |
| No log        | 0.1905 | 12   | 0.7820          | -0.0140 | 0.7757 |
| No log        | 0.2222 | 14   | 0.7393          | -0.0458 | 0.7348 |
| No log        | 0.2540 | 16   | 0.5809          | 0.0613  | 0.5748 |
| No log        | 0.2857 | 18   | 0.5907          | 0.0     | 0.5826 |
| No log        | 0.3175 | 20   | 0.5968          | 0.0     | 0.5879 |
| No log        | 0.3492 | 22   | 0.5997          | 0.0     | 0.5907 |
| No log        | 0.3810 | 24   | 0.6179          | 0.0     | 0.6081 |
| No log        | 0.4127 | 26   | 0.6180          | 0.0     | 0.6082 |
| No log        | 0.4444 | 28   | 0.6050          | 0.0     | 0.5957 |
| No log        | 0.4762 | 30   | 0.6052          | 0.0     | 0.5959 |
| No log        | 0.5079 | 32   | 0.5967          | 0.0     | 0.5878 |
| No log        | 0.5397 | 34   | 0.6247          | 0.0     | 0.6152 |
| No log        | 0.5714 | 36   | 0.6697          | 0.0     | 0.6594 |
| No log        | 0.6032 | 38   | 0.7455          | 0.0     | 0.7341 |
| No log        | 0.6349 | 40   | 0.7874          | 0.0     | 0.7757 |
| No log        | 0.6667 | 42   | 0.7649          | 0.0     | 0.7537 |
| No log        | 0.6984 | 44   | 0.7194          | 0.0     | 0.7089 |
| No log        | 0.7302 | 46   | 0.6683          | 0.0     | 0.6584 |
| No log        | 0.7619 | 48   | 0.6472          | 0.0     | 0.6374 |
| No log        | 0.7937 | 50   | 0.6425          | 0.0     | 0.6324 |
| No log        | 0.8254 | 52   | 0.6567          | 0.0     | 0.6463 |
| No log        | 0.8571 | 54   | 0.6712          | 0.0     | 0.6605 |
| No log        | 0.8889 | 56   | 0.6746          | 0.0     | 0.6639 |
| No log        | 0.9206 | 58   | 0.6773          | 0.0     | 0.6666 |
| No log        | 0.9524 | 60   | 0.6866          | 0.0     | 0.6758 |
| No log        | 0.9841 | 62   | 0.6937          | 0.0     | 0.6827 |


### Framework versions

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