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Roberta_feverous
adity12345/Roberta_feverous
Roberta_feverous is a text classification model from adity12345. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Aug 24, 2025
- Updated
- Aug 24, 2025
- SHA
- 2b006c8e
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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. -->
Roberta_feverous
This model is a fine-tuned version of adity12345/RoBerta_covi19_rumor on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6168
- Accuracy: 0.674
- Auc: 0.67
- Precision: 0.677
- Recall: 0.897
- F1: 0.771
- F1-macro: 0.6
- F1-micro: 0.674
- F1-weighted: 0.639
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | Recall | F1 | F1-macro | F1-micro | F1-weighted |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6385 | 0.2896 | 500 | 0.6240 | 0.666 | 0.646 | 0.656 | 0.96 | 0.779 | 0.546 | 0.666 | 0.599 |
| 0.6294 | 0.5793 | 1000 | 0.6270 | 0.665 | 0.652 | 0.673 | 0.885 | 0.764 | 0.593 | 0.665 | 0.632 |
| 0.627 | 0.8689 | 1500 | 0.6192 | 0.669 | 0.658 | 0.674 | 0.891 | 0.768 | 0.595 | 0.669 | 0.634 |
| 0.6126 | 1.1581 | 2000 | 0.6185 | 0.674 | 0.662 | 0.665 | 0.945 | 0.781 | 0.573 | 0.674 | 0.621 |
| 0.6044 | 1.4478 | 2500 | 0.6155 | 0.673 | 0.665 | 0.669 | 0.927 | 0.777 | 0.582 | 0.673 | 0.627 |
| 0.5942 | 1.7374 | 3000 | 0.6168 | 0.674 | 0.67 | 0.677 | 0.897 | 0.771 | 0.6 | 0.674 | 0.639 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Aug 24, 2025
- Updated
- Aug 24, 2025