---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task7_fold0
  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_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: 0.2152
- Qwk: 0.1252
- Mse: 0.2152

## 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    | 1.7444          | 0.0064 | 1.7443 |
| No log        | 0.0702 | 4    | 0.5072          | 0.0044 | 0.5075 |
| No log        | 0.1053 | 6    | 0.3202          | 0.1573 | 0.3202 |
| No log        | 0.1404 | 8    | 0.2932          | 0.1238 | 0.2931 |
| No log        | 0.1754 | 10   | 0.2459          | 0.0491 | 0.2459 |
| No log        | 0.2105 | 12   | 0.2721          | 0.0611 | 0.2721 |
| No log        | 0.2456 | 14   | 0.3258          | 0.1020 | 0.3257 |
| No log        | 0.2807 | 16   | 0.3460          | 0.1206 | 0.3459 |
| No log        | 0.3158 | 18   | 0.2997          | 0.1063 | 0.2996 |
| No log        | 0.3509 | 20   | 0.2574          | 0.1124 | 0.2574 |
| No log        | 0.3860 | 22   | 0.2457          | 0.1501 | 0.2457 |
| No log        | 0.4211 | 24   | 0.2347          | 0.1830 | 0.2348 |
| No log        | 0.4561 | 26   | 0.2255          | 0.1739 | 0.2255 |
| No log        | 0.4912 | 28   | 0.2268          | 0.1123 | 0.2267 |
| No log        | 0.5263 | 30   | 0.2372          | 0.1054 | 0.2370 |
| No log        | 0.5614 | 32   | 0.2505          | 0.1020 | 0.2503 |
| No log        | 0.5965 | 34   | 0.2609          | 0.1020 | 0.2606 |
| No log        | 0.6316 | 36   | 0.2711          | 0.0959 | 0.2709 |
| No log        | 0.6667 | 38   | 0.2674          | 0.0679 | 0.2672 |
| No log        | 0.7018 | 40   | 0.2605          | 0.0756 | 0.2602 |
| No log        | 0.7368 | 42   | 0.2455          | 0.0756 | 0.2453 |
| No log        | 0.7719 | 44   | 0.2290          | 0.0756 | 0.2289 |
| No log        | 0.8070 | 46   | 0.2191          | 0.0791 | 0.2190 |
| No log        | 0.8421 | 48   | 0.2160          | 0.0898 | 0.2159 |
| No log        | 0.8772 | 50   | 0.2154          | 0.1042 | 0.2153 |
| No log        | 0.9123 | 52   | 0.2153          | 0.1215 | 0.2152 |
| No log        | 0.9474 | 54   | 0.2154          | 0.1252 | 0.2153 |
| No log        | 0.9825 | 56   | 0.2152          | 0.1252 | 0.2152 |


### Framework versions

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