README.md

---
license: apache-2.0
base_model: roberta-base
tags:
- text-classification
- question-answering
- roberta
- pytorch
- transformers
language:
- en
pipeline_tag: text-classification
---

# Cyber_Bot

This is a fine-tuned RoBERTa model for question-answering classification tasks.

## Model Details

- **Base Model**: roberta-base
- **Model Type**: Sequence Classification
- **Language**: English
- **License**: Apache 2.0

## Model Information


- **Number of Classes**: 5
- **Classification Type**: grouped_classification
- **Class Names**: Empty, Word, Short, Medium, Long

## Usage

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained('whitedevil0089devil/Cyber_Bot')
model = AutoModelForSequenceClassification.from_pretrained('whitedevil0089devil/Cyber_Bot')

# Example usage
question = "Your question here"
inputs = tokenizer(question, return_tensors="pt", truncation=True, padding=True, max_length=384)

with torch.no_grad():
    outputs = model(**inputs)
    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
    predicted_class = torch.argmax(outputs.logits, dim=-1).item()
    confidence = predictions[0][predicted_class].item()

print(f"Predicted class: {predicted_class}")
print(f"Confidence: {confidence:.4f}")
```

## Training Details

This model was fine-tuned using:
- **Framework**: PyTorch + Transformers
- **Optimization**: AdamW with learning rate scheduling
- **Training Strategy**: Early stopping with validation monitoring
- **Hardware**: Trained on Google Colab (T4 GPU)

## Intended Use

This model is designed for question-answering classification tasks. It can be used to:
- Classify questions into predefined categories
- Provide automated responses based on question classification
- Support Q&A systems and chatbots

## Limitations

- Model performance depends on the similarity between training data and inference data
- May not generalize well to domains significantly different from training data
- Classification accuracy may vary based on question complexity and length

## Citation

If you use this model, please cite:
```
@misc{roberta-qa-model,
  title={Fine-tuned RoBERTa for Question-Answer Classification},
  author={Your Name},
  year={2024},
  url={https://huggingface.co/whitedevil0089devil/Cyber_Bot}
}
```