---
tags:
- generated_from_trainer
datasets:
- emotone_ar
metrics:
- accuracy
- f1
model-index:
- name: bert-base-arabic-finetuned-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotone_ar
      type: emotone_ar
      config: default
      split: train[:90%]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7266401590457257
    - name: F1
      type: f1
      value: 0.7258317874418239
---

<!-- 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. -->

# bert-base-arabic-finetuned-emotion

This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9079
- Accuracy: 0.7266
- F1: 0.7258

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.2471        | 1.0   | 142  | 0.8635          | 0.7078   | 0.6951 |
| 0.7906        | 2.0   | 284  | 0.8124          | 0.7266   | 0.7202 |
| 0.5983        | 3.0   | 426  | 0.8331          | 0.7336   | 0.7262 |
| 0.4615        | 4.0   | 568  | 0.8542          | 0.7266   | 0.7240 |
| 0.3573        | 5.0   | 710  | 0.8924          | 0.7286   | 0.7274 |
| 0.2969        | 6.0   | 852  | 0.9079          | 0.7266   | 0.7258 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2