metadata
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: arabert-fully-supervised-arabic-propaganda
results: []
arabert-fully-supervised-arabic-propaganda
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02-twitter on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9417
- Accuracy: 0.9452
- Precision: 0.7812
- Recall: 0.6098
- F1: 0.6849
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2106 | 1.0 | 40 | 0.3648 | 0.8881 | 0.4559 | 0.7561 | 0.5688 |
| 0.5647 | 2.0 | 80 | 0.5461 | 0.9286 | 0.6341 | 0.6341 | 0.6341 |
| 0.1487 | 3.0 | 120 | 0.5744 | 0.9286 | 0.6222 | 0.6829 | 0.6512 |
| 0.0015 | 4.0 | 160 | 0.7544 | 0.9429 | 0.7179 | 0.6829 | 0.7000 |
| 0.0013 | 5.0 | 200 | 0.9417 | 0.9452 | 0.7812 | 0.6098 | 0.6849 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1