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roberta-scam-classifier-v1
BothBosu/roberta-scam-classifier-v1
roberta-scam-classifier-v1 is a text classification model from BothBosu. 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
- May 3, 2024
- Updated
- May 3, 2024
- SHA
- 94361823
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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. -->
roberta-scam-classifier-v1
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0264
- Accuracy: {'accuracy': 1.0}
- Precision: {'precision': 1.0}
- Recall: {'recall': 1.0}
- F1: {'f1': 1.0}
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 40 | 0.1392 | {'accuracy': 0.9875} | {'precision': 0.9878048780487806} | {'recall': 0.9875} | {'f1': 0.9874980465697764} |
| No log | 2.0 | 80 | 0.0264 | {'accuracy': 1.0} | {'precision': 1.0} | {'recall': 1.0} | {'f1': 1.0} |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 3, 2024
- Updated
- May 3, 2024