---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold0
  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_fold0

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: 0.8406
- Qwk: 0.4869
- Mse: 0.8406

## 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    | 5.8006          | 0.0028 | 5.7935 |
| No log        | 0.0615 | 4    | 3.2764          | 0.0156 | 3.2707 |
| No log        | 0.0923 | 6    | 1.6565          | 0.1556 | 1.6520 |
| No log        | 0.1231 | 8    | 0.9711          | 0.1893 | 0.9685 |
| No log        | 0.1538 | 10   | 0.8861          | 0.2860 | 0.8838 |
| No log        | 0.1846 | 12   | 1.4789          | 0.1911 | 1.4759 |
| No log        | 0.2154 | 14   | 2.1319          | 0.1487 | 2.1287 |
| No log        | 0.2462 | 16   | 1.7196          | 0.2185 | 1.7170 |
| No log        | 0.2769 | 18   | 1.0076          | 0.3413 | 1.0063 |
| No log        | 0.3077 | 20   | 0.8904          | 0.3996 | 0.8897 |
| No log        | 0.3385 | 22   | 1.1149          | 0.3433 | 1.1142 |
| No log        | 0.3692 | 24   | 1.1193          | 0.3481 | 1.1188 |
| No log        | 0.4    | 26   | 0.9820          | 0.3962 | 0.9818 |
| No log        | 0.4308 | 28   | 0.8143          | 0.4684 | 0.8141 |
| No log        | 0.4615 | 30   | 0.8216          | 0.4725 | 0.8215 |
| No log        | 0.4923 | 32   | 1.0728          | 0.3944 | 1.0729 |
| No log        | 0.5231 | 34   | 1.2902          | 0.3621 | 1.2903 |
| No log        | 0.5538 | 36   | 1.1504          | 0.3826 | 1.1506 |
| No log        | 0.5846 | 38   | 0.9402          | 0.4417 | 0.9403 |
| No log        | 0.6154 | 40   | 0.8442          | 0.4861 | 0.8442 |
| No log        | 0.6462 | 42   | 0.8157          | 0.5097 | 0.8157 |
| No log        | 0.6769 | 44   | 0.7981          | 0.5175 | 0.7980 |
| No log        | 0.7077 | 46   | 0.8171          | 0.5105 | 0.8170 |
| No log        | 0.7385 | 48   | 0.9036          | 0.4947 | 0.9036 |
| No log        | 0.7692 | 50   | 0.9337          | 0.4808 | 0.9338 |
| No log        | 0.8    | 52   | 0.9430          | 0.4687 | 0.9432 |
| No log        | 0.8308 | 54   | 0.9279          | 0.4743 | 0.9280 |
| No log        | 0.8615 | 56   | 0.8904          | 0.4850 | 0.8905 |
| No log        | 0.8923 | 58   | 0.8610          | 0.4939 | 0.8610 |
| No log        | 0.9231 | 60   | 0.8424          | 0.4894 | 0.8424 |
| No log        | 0.9538 | 62   | 0.8388          | 0.4905 | 0.8388 |
| No log        | 0.9846 | 64   | 0.8406          | 0.4869 | 0.8406 |


### Framework versions

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