---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task2_fold0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_baseline_grammar_task2_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: 1.2738
- Qwk: 0.0491
- Mse: 1.2508

## 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Qwk     | Mse    |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
| No log        | 0.3333 | 2    | 4.9005          | 0.0126  | 4.8502 |
| No log        | 0.6667 | 4    | 2.4699          | 0.0387  | 2.4471 |
| No log        | 1.0    | 6    | 1.4800          | -0.0982 | 1.4570 |
| No log        | 1.3333 | 8    | 1.0496          | 0.0541  | 1.0294 |
| No log        | 1.6667 | 10   | 1.2284          | 0.0     | 1.2139 |
| No log        | 2.0    | 12   | 1.4327          | 0.0     | 1.4198 |
| No log        | 2.3333 | 14   | 1.4042          | 0.0     | 1.3911 |
| No log        | 2.6667 | 16   | 1.1140          | -0.0161 | 1.0974 |
| No log        | 3.0    | 18   | 1.0138          | 0.1083  | 0.9870 |
| No log        | 3.3333 | 20   | 1.0084          | 0.2200  | 0.9831 |
| No log        | 3.6667 | 22   | 1.0806          | 0.0696  | 1.0592 |
| No log        | 4.0    | 24   | 1.2446          | -0.1170 | 1.2246 |
| No log        | 4.3333 | 26   | 1.4549          | -0.0960 | 1.4445 |
| No log        | 4.6667 | 28   | 1.3332          | 0.0585  | 1.3205 |
| No log        | 5.0    | 30   | 1.0953          | 0.0870  | 1.0641 |
| No log        | 5.3333 | 32   | 1.0705          | 0.0616  | 1.0381 |
| No log        | 5.6667 | 34   | 1.1503          | 0.1064  | 1.1300 |
| No log        | 6.0    | 36   | 1.2818          | 0.0585  | 1.2670 |
| No log        | 6.3333 | 38   | 1.3332          | -0.0161 | 1.3186 |
| No log        | 6.6667 | 40   | 1.2686          | 0.0491  | 1.2516 |
| No log        | 7.0    | 42   | 1.1870          | 0.0491  | 1.1658 |
| No log        | 7.3333 | 44   | 1.1491          | 0.0491  | 1.1243 |
| No log        | 7.6667 | 46   | 1.1946          | 0.0491  | 1.1709 |
| No log        | 8.0    | 48   | 1.3196          | 0.0491  | 1.3003 |
| No log        | 8.3333 | 50   | 1.3925          | 0.0541  | 1.3747 |
| No log        | 8.6667 | 52   | 1.3818          | 0.0541  | 1.3633 |
| No log        | 9.0    | 54   | 1.3491          | 0.0491  | 1.3293 |
| No log        | 9.3333 | 56   | 1.3127          | 0.0491  | 1.2916 |
| No log        | 9.6667 | 58   | 1.2864          | 0.0491  | 1.2640 |
| No log        | 10.0   | 60   | 1.2738          | 0.0491  | 1.2508 |


### Framework versions

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