---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task2_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_task2_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: 0.3095
- Qwk: 0.0122
- Mse: 0.3095

## 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        | 0.0317 | 2    | 0.4149          | -0.0147 | 0.4158 |
| No log        | 0.0635 | 4    | 0.5335          | 0.1106  | 0.5335 |
| No log        | 0.0952 | 6    | 0.5725          | 0.1645  | 0.5725 |
| No log        | 0.1270 | 8    | 0.3171          | -0.0585 | 0.3169 |
| No log        | 0.1587 | 10   | 0.2926          | 0.0     | 0.2912 |
| No log        | 0.1905 | 12   | 0.2846          | 0.0     | 0.2833 |
| No log        | 0.2222 | 14   | 0.3130          | 0.0     | 0.3124 |
| No log        | 0.2540 | 16   | 0.4146          | -0.0932 | 0.4145 |
| No log        | 0.2857 | 18   | 0.5126          | -0.0604 | 0.5126 |
| No log        | 0.3175 | 20   | 0.5293          | 0.0071  | 0.5293 |
| No log        | 0.3492 | 22   | 0.5096          | -0.0065 | 0.5096 |
| No log        | 0.3810 | 24   | 0.4663          | -0.0607 | 0.4663 |
| No log        | 0.4127 | 26   | 0.3891          | 0.0072  | 0.3890 |
| No log        | 0.4444 | 28   | 0.3106          | 0.0     | 0.3105 |
| No log        | 0.4762 | 30   | 0.2879          | 0.0     | 0.2877 |
| No log        | 0.5079 | 32   | 0.2833          | 0.0     | 0.2833 |
| No log        | 0.5397 | 34   | 0.2867          | 0.0     | 0.2867 |
| No log        | 0.5714 | 36   | 0.2981          | 0.0     | 0.2981 |
| No log        | 0.6032 | 38   | 0.3163          | 0.0122  | 0.3163 |
| No log        | 0.6349 | 40   | 0.3375          | -0.0208 | 0.3375 |
| No log        | 0.6667 | 42   | 0.3404          | -0.0128 | 0.3404 |
| No log        | 0.6984 | 44   | 0.3376          | -0.0128 | 0.3376 |
| No log        | 0.7302 | 46   | 0.3381          | -0.0128 | 0.3381 |
| No log        | 0.7619 | 48   | 0.3257          | -0.0042 | 0.3257 |
| No log        | 0.7937 | 50   | 0.3134          | 0.0122  | 0.3134 |
| No log        | 0.8254 | 52   | 0.3075          | 0.0     | 0.3075 |
| No log        | 0.8571 | 54   | 0.3042          | 0.0     | 0.3042 |
| No log        | 0.8889 | 56   | 0.3043          | 0.0     | 0.3043 |
| No log        | 0.9206 | 58   | 0.3064          | 0.0     | 0.3064 |
| No log        | 0.9524 | 60   | 0.3082          | 0.0122  | 0.3082 |
| No log        | 0.9841 | 62   | 0.3095          | 0.0122  | 0.3095 |


### Framework versions

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