---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold1
  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_task7_fold1

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: 0.8627
- Qwk: 0.3143
- Mse: 0.8627

## 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        | 0.0351 | 2    | 3.8189          | 0.0193 | 3.8189 |
| No log        | 0.0702 | 4    | 1.7985          | 0.0716 | 1.7985 |
| No log        | 0.1053 | 6    | 1.6094          | 0.1126 | 1.6094 |
| No log        | 0.1404 | 8    | 1.2553          | 0.1291 | 1.2553 |
| No log        | 0.1754 | 10   | 0.8065          | 0.1674 | 0.8065 |
| No log        | 0.2105 | 12   | 0.7741          | 0.2489 | 0.7741 |
| No log        | 0.2456 | 14   | 1.1045          | 0.2614 | 1.1045 |
| No log        | 0.2807 | 16   | 1.1978          | 0.2692 | 1.1978 |
| No log        | 0.3158 | 18   | 1.0983          | 0.2938 | 1.0983 |
| No log        | 0.3509 | 20   | 1.0710          | 0.3026 | 1.0710 |
| No log        | 0.3860 | 22   | 0.6682          | 0.3670 | 0.6682 |
| No log        | 0.4211 | 24   | 0.5966          | 0.4097 | 0.5966 |
| No log        | 0.4561 | 26   | 0.6833          | 0.3683 | 0.6833 |
| No log        | 0.4912 | 28   | 0.9987          | 0.2985 | 0.9987 |
| No log        | 0.5263 | 30   | 1.2852          | 0.2523 | 1.2852 |
| No log        | 0.5614 | 32   | 1.0778          | 0.2737 | 1.0778 |
| No log        | 0.5965 | 34   | 0.7230          | 0.3317 | 0.7230 |
| No log        | 0.6316 | 36   | 0.6062          | 0.4082 | 0.6062 |
| No log        | 0.6667 | 38   | 0.5822          | 0.4172 | 0.5822 |
| No log        | 0.7018 | 40   | 0.6112          | 0.4001 | 0.6112 |
| No log        | 0.7368 | 42   | 0.6913          | 0.3542 | 0.6913 |
| No log        | 0.7719 | 44   | 0.8003          | 0.3063 | 0.8003 |
| No log        | 0.8070 | 46   | 0.8430          | 0.3051 | 0.8430 |
| No log        | 0.8421 | 48   | 0.8930          | 0.3029 | 0.8930 |
| No log        | 0.8772 | 50   | 0.8887          | 0.3031 | 0.8887 |
| No log        | 0.9123 | 52   | 0.8824          | 0.2971 | 0.8824 |
| No log        | 0.9474 | 54   | 0.8755          | 0.2971 | 0.8755 |
| No log        | 0.9825 | 56   | 0.8627          | 0.3143 | 0.8627 |


### Framework versions

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