---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task2_fold2
  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_relevance_task2_fold2

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: 0.2974
- Qwk: 0.0
- Mse: 0.2974

## 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    | 1.8592          | 0.0     | 1.8592 |
| No log        | 0.0615 | 4    | 0.5542          | 0.0521  | 0.5542 |
| No log        | 0.0923 | 6    | 0.2790          | -0.0315 | 0.2790 |
| No log        | 0.1231 | 8    | 0.3268          | 0.0812  | 0.3268 |
| No log        | 0.1538 | 10   | 0.2739          | 0.0068  | 0.2739 |
| No log        | 0.1846 | 12   | 0.2872          | 0.0     | 0.2872 |
| No log        | 0.2154 | 14   | 0.3469          | 0.0     | 0.3469 |
| No log        | 0.2462 | 16   | 0.3134          | 0.0     | 0.3134 |
| No log        | 0.2769 | 18   | 0.2680          | 0.0     | 0.2680 |
| No log        | 0.3077 | 20   | 0.2818          | -0.0034 | 0.2818 |
| No log        | 0.3385 | 22   | 0.3013          | -0.0461 | 0.3013 |
| No log        | 0.3692 | 24   | 0.3036          | -0.0714 | 0.3036 |
| No log        | 0.4    | 26   | 0.3135          | 0.0     | 0.3135 |
| No log        | 0.4308 | 28   | 0.3150          | 0.0     | 0.3150 |
| No log        | 0.4615 | 30   | 0.3118          | 0.0     | 0.3118 |
| No log        | 0.4923 | 32   | 0.3083          | -0.0096 | 0.3083 |
| No log        | 0.5231 | 34   | 0.3294          | 0.0432  | 0.3294 |
| No log        | 0.5538 | 36   | 0.3784          | 0.0432  | 0.3784 |
| No log        | 0.5846 | 38   | 0.4043          | 0.0432  | 0.4043 |
| No log        | 0.6154 | 40   | 0.3829          | 0.0432  | 0.3829 |
| No log        | 0.6462 | 42   | 0.3424          | 0.0     | 0.3424 |
| No log        | 0.6769 | 44   | 0.3208          | 0.0     | 0.3208 |
| No log        | 0.7077 | 46   | 0.3133          | 0.0     | 0.3133 |
| No log        | 0.7385 | 48   | 0.3084          | 0.0     | 0.3084 |
| No log        | 0.7692 | 50   | 0.3050          | 0.0     | 0.3050 |
| No log        | 0.8    | 52   | 0.3061          | 0.0     | 0.3061 |
| No log        | 0.8308 | 54   | 0.3000          | 0.0     | 0.3000 |
| No log        | 0.8615 | 56   | 0.2974          | 0.0     | 0.2974 |
| No log        | 0.8923 | 58   | 0.2961          | 0.0     | 0.2961 |
| No log        | 0.9231 | 60   | 0.2955          | 0.0     | 0.2955 |
| No log        | 0.9538 | 62   | 0.2966          | 0.0     | 0.2966 |
| No log        | 0.9846 | 64   | 0.2974          | 0.0     | 0.2974 |


### Framework versions

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