---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task4_fold1
  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_task4_fold1

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: 0.1659
- Qwk: 0.0402
- Mse: 0.1659

## 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    | 2.0522          | -0.0055 | 2.0522 |
| No log        | 0.0615 | 4    | 0.6665          | -0.0084 | 0.6665 |
| No log        | 0.0923 | 6    | 0.2290          | 0.0207  | 0.2290 |
| No log        | 0.1231 | 8    | 0.1690          | 0.0796  | 0.1690 |
| No log        | 0.1538 | 10   | 0.2100          | 0.0199  | 0.2100 |
| No log        | 0.1846 | 12   | 0.4380          | 0.0228  | 0.4380 |
| No log        | 0.2154 | 14   | 0.4146          | 0.0114  | 0.4146 |
| No log        | 0.2462 | 16   | 0.4672          | 0.0164  | 0.4672 |
| No log        | 0.2769 | 18   | 0.4548          | 0.0082  | 0.4548 |
| No log        | 0.3077 | 20   | 0.3092          | 0.0166  | 0.3092 |
| No log        | 0.3385 | 22   | 0.1656          | 0.0373  | 0.1656 |
| No log        | 0.3692 | 24   | 0.1443          | 0.0155  | 0.1443 |
| No log        | 0.4    | 26   | 0.1375          | 0.0344  | 0.1375 |
| No log        | 0.4308 | 28   | 0.1319          | 0.0250  | 0.1319 |
| No log        | 0.4615 | 30   | 0.1415          | 0.0270  | 0.1415 |
| No log        | 0.4923 | 32   | 0.1730          | 0.0185  | 0.1730 |
| No log        | 0.5231 | 34   | 0.2033          | 0.0185  | 0.2033 |
| No log        | 0.5538 | 36   | 0.2320          | 0.0166  | 0.2320 |
| No log        | 0.5846 | 38   | 0.2349          | 0.0149  | 0.2349 |
| No log        | 0.6154 | 40   | 0.2136          | 0.0165  | 0.2136 |
| No log        | 0.6462 | 42   | 0.1798          | 0.0165  | 0.1798 |
| No log        | 0.6769 | 44   | 0.1596          | 0.0175  | 0.1596 |
| No log        | 0.7077 | 46   | 0.1554          | 0.0243  | 0.1554 |
| No log        | 0.7385 | 48   | 0.1612          | 0.0316  | 0.1612 |
| No log        | 0.7692 | 50   | 0.1628          | 0.0261  | 0.1628 |
| No log        | 0.8    | 52   | 0.1699          | 0.0317  | 0.1699 |
| No log        | 0.8308 | 54   | 0.1702          | 0.0284  | 0.1702 |
| No log        | 0.8615 | 56   | 0.1679          | 0.0334  | 0.1679 |
| No log        | 0.8923 | 58   | 0.1678          | 0.0334  | 0.1678 |
| No log        | 0.9231 | 60   | 0.1646          | 0.0436  | 0.1646 |
| No log        | 0.9538 | 62   | 0.1648          | 0.0402  | 0.1648 |
| No log        | 0.9846 | 64   | 0.1659          | 0.0402  | 0.1659 |


### Framework versions

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