---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_relevance_task1_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: 0.2406
- Qwk: 0.0225
- Mse: 0.2406

## 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    | 0.5970          | 0.0065 | 0.5970 |
| No log        | 0.0702 | 4    | 0.1673          | 0.0060 | 0.1673 |
| No log        | 0.1053 | 6    | 0.3299          | 0.0278 | 0.3299 |
| No log        | 0.1404 | 8    | 0.7352          | 0.0065 | 0.7352 |
| No log        | 0.1754 | 10   | 0.6501          | 0.0208 | 0.6501 |
| No log        | 0.2105 | 12   | 0.4790          | 0.0347 | 0.4790 |
| No log        | 0.2456 | 14   | 0.3876          | 0.0363 | 0.3876 |
| No log        | 0.2807 | 16   | 0.4097          | 0.0294 | 0.4097 |
| No log        | 0.3158 | 18   | 0.3925          | 0.0277 | 0.3925 |
| No log        | 0.3509 | 20   | 0.3541          | 0.0310 | 0.3541 |
| No log        | 0.3860 | 22   | 0.3565          | 0.0461 | 0.3565 |
| No log        | 0.4211 | 24   | 0.3341          | 0.0410 | 0.3341 |
| No log        | 0.4561 | 26   | 0.3266          | 0.0480 | 0.3266 |
| No log        | 0.4912 | 28   | 0.3191          | 0.0381 | 0.3191 |
| No log        | 0.5263 | 30   | 0.3104          | 0.0271 | 0.3104 |
| No log        | 0.5614 | 32   | 0.3215          | 0.0271 | 0.3215 |
| No log        | 0.5965 | 34   | 0.3010          | 0.0194 | 0.3010 |
| No log        | 0.6316 | 36   | 0.3055          | 0.0194 | 0.3055 |
| No log        | 0.6667 | 38   | 0.3447          | 0.0254 | 0.3447 |
| No log        | 0.7018 | 40   | 0.3547          | 0.0399 | 0.3547 |
| No log        | 0.7368 | 42   | 0.3642          | 0.0399 | 0.3642 |
| No log        | 0.7719 | 44   | 0.3510          | 0.0327 | 0.3510 |
| No log        | 0.8070 | 46   | 0.3201          | 0.0178 | 0.3201 |
| No log        | 0.8421 | 48   | 0.2882          | 0.0194 | 0.2882 |
| No log        | 0.8772 | 50   | 0.2672          | 0.0209 | 0.2672 |
| No log        | 0.9123 | 52   | 0.2539          | 0.0209 | 0.2539 |
| No log        | 0.9474 | 54   | 0.2455          | 0.0225 | 0.2455 |
| No log        | 0.9825 | 56   | 0.2406          | 0.0225 | 0.2406 |


### Framework versions

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