---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_fold5
  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_task6_fold5

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: 0.3785
- Qwk: 0.8516
- Mse: 0.3785

## 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    | 3.9811          | 0.0    | 3.9811 |
| No log        | 0.0656 | 4    | 2.1407          | 0.1479 | 2.1407 |
| No log        | 0.0984 | 6    | 1.1264          | 0.1813 | 1.1264 |
| No log        | 0.1311 | 8    | 0.8366          | 0.5074 | 0.8366 |
| No log        | 0.1639 | 10   | 0.8195          | 0.5441 | 0.8195 |
| No log        | 0.1967 | 12   | 1.0058          | 0.5881 | 1.0058 |
| No log        | 0.2295 | 14   | 1.0622          | 0.6346 | 1.0622 |
| No log        | 0.2623 | 16   | 0.9868          | 0.6510 | 0.9868 |
| No log        | 0.2951 | 18   | 0.6515          | 0.7729 | 0.6515 |
| No log        | 0.3279 | 20   | 0.3945          | 0.6974 | 0.3945 |
| No log        | 0.3607 | 22   | 0.5838          | 0.5376 | 0.5838 |
| No log        | 0.3934 | 24   | 0.3960          | 0.6758 | 0.3960 |
| No log        | 0.4262 | 26   | 0.3530          | 0.8548 | 0.3530 |
| No log        | 0.4590 | 28   | 0.6972          | 0.8507 | 0.6972 |
| No log        | 0.4918 | 30   | 0.8848          | 0.8086 | 0.8848 |
| No log        | 0.5246 | 32   | 0.8411          | 0.8211 | 0.8411 |
| No log        | 0.5574 | 34   | 0.7868          | 0.8137 | 0.7868 |
| No log        | 0.5902 | 36   | 0.6804          | 0.8522 | 0.6804 |
| No log        | 0.6230 | 38   | 0.5836          | 0.8642 | 0.5836 |
| No log        | 0.6557 | 40   | 0.4481          | 0.8666 | 0.4481 |
| No log        | 0.6885 | 42   | 0.3439          | 0.8485 | 0.3439 |
| No log        | 0.7213 | 44   | 0.3168          | 0.8084 | 0.3168 |
| No log        | 0.7541 | 46   | 0.3134          | 0.7968 | 0.3134 |
| No log        | 0.7869 | 48   | 0.3070          | 0.7933 | 0.3070 |
| No log        | 0.8197 | 50   | 0.3050          | 0.8144 | 0.3050 |
| No log        | 0.8525 | 52   | 0.3093          | 0.8265 | 0.3093 |
| No log        | 0.8852 | 54   | 0.3243          | 0.8430 | 0.3243 |
| No log        | 0.9180 | 56   | 0.3471          | 0.8435 | 0.3471 |
| No log        | 0.9508 | 58   | 0.3676          | 0.8531 | 0.3676 |
| No log        | 0.9836 | 60   | 0.3785          | 0.8516 | 0.3785 |


### Framework versions

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