---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task2_fold3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_relevance_task2_fold3

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: 0.2961
- Qwk: 0.3277
- Mse: 0.2961

## 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    | 1.1621          | 0.0229 | 1.1621 |
| No log        | 0.0702 | 4    | 0.5340          | 0.1841 | 0.5340 |
| No log        | 0.1053 | 6    | 0.5506          | 0.1500 | 0.5506 |
| No log        | 0.1404 | 8    | 0.5057          | 0.1888 | 0.5057 |
| No log        | 0.1754 | 10   | 0.4434          | 0.1993 | 0.4434 |
| No log        | 0.2105 | 12   | 0.4171          | 0.2214 | 0.4171 |
| No log        | 0.2456 | 14   | 0.3762          | 0.2316 | 0.3762 |
| No log        | 0.2807 | 16   | 0.3295          | 0.2935 | 0.3295 |
| No log        | 0.3158 | 18   | 0.3210          | 0.2948 | 0.3210 |
| No log        | 0.3509 | 20   | 0.3093          | 0.2948 | 0.3093 |
| No log        | 0.3860 | 22   | 0.3105          | 0.3062 | 0.3105 |
| No log        | 0.4211 | 24   | 0.3464          | 0.3679 | 0.3464 |
| No log        | 0.4561 | 26   | 0.3981          | 0.6151 | 0.3981 |
| No log        | 0.4912 | 28   | 0.3851          | 0.6021 | 0.3851 |
| No log        | 0.5263 | 30   | 0.3431          | 0.4831 | 0.3431 |
| No log        | 0.5614 | 32   | 0.3017          | 0.3166 | 0.3017 |
| No log        | 0.5965 | 34   | 0.2863          | 0.3277 | 0.2863 |
| No log        | 0.6316 | 36   | 0.2906          | 0.3407 | 0.2906 |
| No log        | 0.6667 | 38   | 0.2981          | 0.3509 | 0.2981 |
| No log        | 0.7018 | 40   | 0.2999          | 0.3509 | 0.2999 |
| No log        | 0.7368 | 42   | 0.2988          | 0.3391 | 0.2988 |
| No log        | 0.7719 | 44   | 0.2970          | 0.3148 | 0.2970 |
| No log        | 0.8070 | 46   | 0.2972          | 0.3126 | 0.2972 |
| No log        | 0.8421 | 48   | 0.2982          | 0.3126 | 0.2982 |
| No log        | 0.8772 | 50   | 0.2966          | 0.3158 | 0.2966 |
| No log        | 0.9123 | 52   | 0.2961          | 0.3277 | 0.2961 |
| No log        | 0.9474 | 54   | 0.2957          | 0.3286 | 0.2957 |
| No log        | 0.9825 | 56   | 0.2961          | 0.3277 | 0.2961 |


### Framework versions

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