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library_name: transformers
license: mit
base_model: adity12345/RoBerta_covi19_rumor
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Roberta_feverous
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. -->
# Roberta_feverous
This model is a fine-tuned version of [adity12345/RoBerta_covi19_rumor](https://huggingface.co/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
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