---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_token_classification_AraEval24_aug800
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RoBERTa_token_classification_AraEval24_aug800

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5882
- Precision: 0.0607
- Recall: 0.0717
- F1: 0.0658
- Accuracy: 0.6965

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7043        | 1.0   | 1839  | 1.0921          | 0.0244    | 0.0115 | 0.0156 | 0.7401   |
| 0.4043        | 2.0   | 3678  | 1.1721          | 0.0428    | 0.0339 | 0.0378 | 0.7080   |
| 0.3146        | 3.0   | 5517  | 1.2162          | 0.0565    | 0.0583 | 0.0574 | 0.7032   |
| 0.2459        | 4.0   | 7356  | 1.3033          | 0.0641    | 0.0697 | 0.0668 | 0.7021   |
| 0.2155        | 5.0   | 9195  | 1.2839          | 0.0619    | 0.0523 | 0.0567 | 0.7322   |
| 0.1775        | 6.0   | 11034 | 1.3535          | 0.0653    | 0.0627 | 0.0640 | 0.7184   |
| 0.1598        | 7.0   | 12873 | 1.4153          | 0.0654    | 0.0702 | 0.0677 | 0.7092   |
| 0.1442        | 8.0   | 14712 | 1.5081          | 0.0636    | 0.0712 | 0.0672 | 0.6949   |
| 0.1287        | 9.0   | 16551 | 1.5040          | 0.0646    | 0.0687 | 0.0666 | 0.7068   |
| 0.108         | 10.0  | 18390 | 1.5882          | 0.0607    | 0.0717 | 0.0658 | 0.6965   |


### Framework versions

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