---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task2_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_task2_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: 0.4047
- Qwk: 0.8288
- Mse: 0.4047

## 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        | 0.0328 | 2    | 1.7452          | 0.0006 | 1.7452 |
| No log        | 0.0656 | 4    | 1.2370          | 0.1274 | 1.2370 |
| No log        | 0.0984 | 6    | 0.8329          | 0.4478 | 0.8329 |
| No log        | 0.1311 | 8    | 0.6416          | 0.5311 | 0.6416 |
| No log        | 0.1639 | 10   | 0.5045          | 0.6702 | 0.5045 |
| No log        | 0.1967 | 12   | 0.7393          | 0.7456 | 0.7393 |
| No log        | 0.2295 | 14   | 0.6764          | 0.7611 | 0.6764 |
| No log        | 0.2623 | 16   | 0.4405          | 0.7742 | 0.4405 |
| No log        | 0.2951 | 18   | 0.4529          | 0.6406 | 0.4529 |
| No log        | 0.3279 | 20   | 0.4250          | 0.6970 | 0.4250 |
| No log        | 0.3607 | 22   | 0.4454          | 0.8071 | 0.4454 |
| No log        | 0.3934 | 24   | 0.6139          | 0.7900 | 0.6139 |
| No log        | 0.4262 | 26   | 0.5738          | 0.7676 | 0.5738 |
| No log        | 0.4590 | 28   | 0.4153          | 0.7533 | 0.4153 |
| No log        | 0.4918 | 30   | 0.3615          | 0.7288 | 0.3615 |
| No log        | 0.5246 | 32   | 0.3546          | 0.7617 | 0.3546 |
| No log        | 0.5574 | 34   | 0.3710          | 0.7951 | 0.3710 |
| No log        | 0.5902 | 36   | 0.4183          | 0.8076 | 0.4183 |
| No log        | 0.6230 | 38   | 0.4794          | 0.8180 | 0.4794 |
| No log        | 0.6557 | 40   | 0.4977          | 0.8093 | 0.4977 |
| No log        | 0.6885 | 42   | 0.4901          | 0.8202 | 0.4901 |
| No log        | 0.7213 | 44   | 0.4251          | 0.8233 | 0.4251 |
| No log        | 0.7541 | 46   | 0.3869          | 0.8256 | 0.3869 |
| No log        | 0.7869 | 48   | 0.3765          | 0.8231 | 0.3765 |
| No log        | 0.8197 | 50   | 0.3956          | 0.8234 | 0.3956 |
| No log        | 0.8525 | 52   | 0.4092          | 0.8176 | 0.4092 |
| No log        | 0.8852 | 54   | 0.4118          | 0.8198 | 0.4118 |
| No log        | 0.9180 | 56   | 0.4170          | 0.8220 | 0.4170 |
| No log        | 0.9508 | 58   | 0.4094          | 0.8265 | 0.4094 |
| No log        | 0.9836 | 60   | 0.4047          | 0.8288 | 0.4047 |


### Framework versions

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