---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ar-poem-classification
  results: []
---

<!-- 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. -->

# ar-poem-classification

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1427
- Macro F1: 0.6954
- Accuracy: 0.6944

## 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: 128
- seed: 25
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   | 250  | 1.0896          | 0.5319   | 0.5334   |
| 1.114         | 2.0   | 500  | 0.9989          | 0.5864   | 0.5826   |
| 1.114         | 3.0   | 750  | 0.9993          | 0.5942   | 0.5976   |
| 0.8219        | 4.0   | 1000 | 0.9949          | 0.6042   | 0.609    |
| 0.8219        | 5.0   | 1250 | 0.9813          | 0.6337   | 0.6366   |
| 0.563         | 6.0   | 1500 | 0.9666          | 0.6657   | 0.6654   |
| 0.563         | 7.0   | 1750 | 1.0253          | 0.6686   | 0.6668   |
| 0.3763        | 8.0   | 2000 | 1.0150          | 0.6951   | 0.6936   |
| 0.3763        | 9.0   | 2250 | 1.0619          | 0.6872   | 0.6872   |
| 0.2525        | 10.0  | 2500 | 1.1035          | 0.6929   | 0.6922   |
| 0.2525        | 11.0  | 2750 | 1.1352          | 0.6952   | 0.6944   |
| 0.184         | 12.0  | 3000 | 1.1427          | 0.6954   | 0.6944   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2