---
base_model: aubmindlab/bert-large-arabertv02
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: arabert-emotions-classification
  results: []
---

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

This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02](https://huggingface.co/aubmindlab/bert-large-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2817
- F1: 0.7006
- Roc Auc: 0.7931
- Accuracy: 0.2769

## 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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 190  | 0.3665          | 0.5604 | 0.7049  | 0.1761   |
| No log        | 2.0   | 380  | 0.3086          | 0.6755 | 0.7775  | 0.2564   |
| 0.3831        | 3.0   | 570  | 0.2953          | 0.6848 | 0.7812  | 0.2496   |
| 0.3831        | 4.0   | 760  | 0.2849          | 0.6933 | 0.7866  | 0.2615   |
| 0.3831        | 5.0   | 950  | 0.2817          | 0.7006 | 0.7931  | 0.2769   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1