---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold4
  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_fold4

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: 0.6439
- Qwk: 0.8180
- Mse: 0.6439

## 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        | 0.0290 | 2    | 3.9935          | 0.0078 | 3.9935 |
| No log        | 0.0580 | 4    | 2.2937          | 0.0536 | 2.2937 |
| No log        | 0.0870 | 6    | 1.2377          | 0.1729 | 1.2377 |
| No log        | 0.1159 | 8    | 1.3353          | 0.1826 | 1.3353 |
| No log        | 0.1449 | 10   | 1.1216          | 0.4773 | 1.1216 |
| No log        | 0.1739 | 12   | 0.8392          | 0.5499 | 0.8392 |
| No log        | 0.2029 | 14   | 0.6966          | 0.6127 | 0.6966 |
| No log        | 0.2319 | 16   | 0.6473          | 0.6969 | 0.6473 |
| No log        | 0.2609 | 18   | 0.6961          | 0.7720 | 0.6961 |
| No log        | 0.2899 | 20   | 0.5180          | 0.8112 | 0.5180 |
| No log        | 0.3188 | 22   | 0.4069          | 0.7973 | 0.4069 |
| No log        | 0.3478 | 24   | 0.3749          | 0.7620 | 0.3749 |
| No log        | 0.3768 | 26   | 0.3945          | 0.7235 | 0.3945 |
| No log        | 0.4058 | 28   | 0.3796          | 0.7580 | 0.3796 |
| No log        | 0.4348 | 30   | 0.4995          | 0.8231 | 0.4995 |
| No log        | 0.4638 | 32   | 0.6489          | 0.7303 | 0.6489 |
| No log        | 0.4928 | 34   | 0.6807          | 0.6611 | 0.6807 |
| No log        | 0.5217 | 36   | 0.5950          | 0.7894 | 0.5950 |
| No log        | 0.5507 | 38   | 0.4549          | 0.8319 | 0.4549 |
| No log        | 0.5797 | 40   | 0.3601          | 0.7833 | 0.3601 |
| No log        | 0.6087 | 42   | 0.3472          | 0.7513 | 0.3472 |
| No log        | 0.6377 | 44   | 0.3541          | 0.716  | 0.3541 |
| No log        | 0.6667 | 46   | 0.3486          | 0.7411 | 0.3486 |
| No log        | 0.6957 | 48   | 0.3480          | 0.7678 | 0.3480 |
| No log        | 0.7246 | 50   | 0.3984          | 0.8135 | 0.3984 |
| No log        | 0.7536 | 52   | 0.5146          | 0.8349 | 0.5146 |
| No log        | 0.7826 | 54   | 0.6619          | 0.8250 | 0.6619 |
| No log        | 0.8116 | 56   | 0.7304          | 0.7951 | 0.7304 |
| No log        | 0.8406 | 58   | 0.7284          | 0.7985 | 0.7284 |
| No log        | 0.8696 | 60   | 0.7335          | 0.8019 | 0.7335 |
| No log        | 0.8986 | 62   | 0.7134          | 0.8053 | 0.7134 |
| No log        | 0.9275 | 64   | 0.6805          | 0.8133 | 0.6805 |
| No log        | 0.9565 | 66   | 0.6611          | 0.8180 | 0.6611 |
| No log        | 0.9855 | 68   | 0.6439          | 0.8180 | 0.6439 |


### Framework versions

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