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arabertv2-weakly-supervised-arabic-propaganda
Bmalmotairy/arabertv2-weakly-supervised-arabic-propaganda
arabertv2-weakly-supervised-arabic-propaganda is a text classification model from Bmalmotairy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Nov 16, 2023
- Updated
- Nov 16, 2023
- SHA
- 5d8381b0
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
arabertv2-weakly-supervised-arabic-propaganda
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2702
- Accuracy: 0.8651
- Precision: 0.7667
- Recall: 0.6656
- F1: 0.7126
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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2746 | 1.0 | 1648 | 0.2702 | 0.8651 | 0.7667 | 0.6656 | 0.7126 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 16, 2023
- Updated
- Nov 16, 2023