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roberta-tweet-virality-classification-full
siddharthgowda/roberta-tweet-virality-classification-full
roberta-tweet-virality-classification-full is a text classification model from siddharthgowda. 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
- roberta
- Access
- Public
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025
- SHA
- 21e7874b
Try a prompt
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. -->
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
COMS4705-roberta-tweet-virality-full-vfinal-last-minuete
This model is a fine-tuned version of siddharthgowda/COMS4705-roberta-tweet-virality-head-only-vfinal on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3471
- Accuracy: 0.8363
- F1: 0.9019
- Precision: 0.9875
- Recall: 0.8363
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: 1e-07
- train_batch_size: 256
- eval_batch_size: 8
- seed: 42
- 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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4624 | 1.0 | 365 | 0.3623 | 0.8374 | 0.9025 | 0.9874 | 0.8374 |
| 0.4773 | 2.0 | 730 | 0.3470 | 0.8394 | 0.9037 | 0.9875 | 0.8394 |
| 0.4639 | 3.0 | 1095 | 0.3471 | 0.8363 | 0.9019 | 0.9875 | 0.8363 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025