---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification__AraEval24_merged_rassd_fixed
  results: []
---

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# AraBERT_token_classification__AraEval24_merged_rassd_fixed

This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8835
- Precision: 0.0974
- Recall: 0.0209
- F1: 0.0344
- Accuracy: 0.8600

## 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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6721        | 1.0   | 2878  | 0.7894          | 0.05      | 0.0002 | 0.0005 | 0.8632   |
| 0.6093        | 2.0   | 5756  | 0.7914          | 0.0841    | 0.0033 | 0.0064 | 0.8636   |
| 0.5514        | 3.0   | 8634  | 0.7789          | 0.1141    | 0.0042 | 0.0081 | 0.8633   |
| 0.5117        | 4.0   | 11512 | 0.7879          | 0.1026    | 0.0129 | 0.0229 | 0.8623   |
| 0.4447        | 5.0   | 14390 | 0.8013          | 0.0881    | 0.0053 | 0.0100 | 0.8628   |
| 0.4371        | 6.0   | 17268 | 0.8165          | 0.1255    | 0.0151 | 0.0270 | 0.8630   |
| 0.415         | 7.0   | 20146 | 0.8406          | 0.0984    | 0.0116 | 0.0208 | 0.8623   |
| 0.3919        | 8.0   | 23024 | 0.8537          | 0.0999    | 0.0173 | 0.0295 | 0.8616   |
| 0.3611        | 9.0   | 25902 | 0.8645          | 0.1039    | 0.0183 | 0.0311 | 0.8614   |
| 0.3518        | 10.0  | 28780 | 0.8835          | 0.0974    | 0.0209 | 0.0344 | 0.8600   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.2
- Tokenizers 0.13.3