---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold0
  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_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: 0.6468
- Qwk: 0.5330
- Mse: 0.6465

## 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    | 7.0706          | 0.0013 | 7.0661 |
| No log        | 0.0702 | 4    | 3.7734          | 0.0327 | 3.7717 |
| No log        | 0.1053 | 6    | 1.8592          | 0.0683 | 1.8601 |
| No log        | 0.1404 | 8    | 1.0155          | 0.2390 | 1.0154 |
| No log        | 0.1754 | 10   | 1.1406          | 0.1653 | 1.1393 |
| No log        | 0.2105 | 12   | 1.3051          | 0.1603 | 1.3037 |
| No log        | 0.2456 | 14   | 1.6813          | 0.1353 | 1.6795 |
| No log        | 0.2807 | 16   | 1.9830          | 0.1290 | 1.9812 |
| No log        | 0.3158 | 18   | 1.4915          | 0.2062 | 1.4903 |
| No log        | 0.3509 | 20   | 0.8770          | 0.3141 | 0.8766 |
| No log        | 0.3860 | 22   | 0.7757          | 0.3596 | 0.7754 |
| No log        | 0.4211 | 24   | 0.7897          | 0.3469 | 0.7894 |
| No log        | 0.4561 | 26   | 0.7860          | 0.3869 | 0.7857 |
| No log        | 0.4912 | 28   | 1.0219          | 0.3741 | 1.0213 |
| No log        | 0.5263 | 30   | 1.4552          | 0.3028 | 1.4543 |
| No log        | 0.5614 | 32   | 1.7633          | 0.2481 | 1.7624 |
| No log        | 0.5965 | 34   | 1.7356          | 0.2503 | 1.7348 |
| No log        | 0.6316 | 36   | 1.3222          | 0.3331 | 1.3216 |
| No log        | 0.6667 | 38   | 0.9190          | 0.3911 | 0.9185 |
| No log        | 0.7018 | 40   | 0.7186          | 0.4702 | 0.7182 |
| No log        | 0.7368 | 42   | 0.6343          | 0.5308 | 0.6340 |
| No log        | 0.7719 | 44   | 0.6126          | 0.5621 | 0.6123 |
| No log        | 0.8070 | 46   | 0.6041          | 0.5797 | 0.6039 |
| No log        | 0.8421 | 48   | 0.6057          | 0.5797 | 0.6055 |
| No log        | 0.8772 | 50   | 0.6117          | 0.5643 | 0.6115 |
| No log        | 0.9123 | 52   | 0.6235          | 0.5650 | 0.6232 |
| No log        | 0.9474 | 54   | 0.6369          | 0.5445 | 0.6367 |
| No log        | 0.9825 | 56   | 0.6468          | 0.5330 | 0.6465 |


### Framework versions

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