Upload README.md

README.md

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+---
+license: apache-2.0
+tags:
+- bert
+- deberta
+- text-classification
+- fine-tuned
+- databricks-dolly
+- prompt-category
+language: en
+---
+
+# 🧠 DeBERTa-v3 Base - Prompt Category Classifier (Fine-tuned)
+
+This model is a fine-tuned version of [`microsoft/deberta-v3-base`](https://huggingface.co/microsoft/deberta-v3-base) on a modified version of the [databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) dataset.  
+It has been trained to classify the **prompt category** based solely on the **response** text.
+
+## 🗂️ Task
+
+**Text Classification**  
+**Input**: Response text from a human-annotated prompt  
+**Output**: One of the predefined categories such as:
+- `brainstorming`
+- `classification`
+- `closed_qa`
+- `creative_writing`
+- `general_qa`
+- `information_extraction`
+- `open_qa`
+- `summarization`
+
+## 📊 Evaluation
+
+The model was evaluated on a balanced version of the dataset. Here are the results:
+
+- **Validation Accuracy**: ~85.5%
+- **F1 Score**: ~85.0%
+- Best performance on: `creative_writing`, `classification`, `summarization`
+- Room for improvement on: `open_qa`
+
+## 🧪 How to Use
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model = AutoModelForSequenceClassification.from_pretrained("mariadg/deberta-v3-category-classifier")
+tokenizer = AutoTokenizer.from_pretrained("mariadg/deberta-v3-category-classifier")
+
+text = "The mitochondria is known as the powerhouse of the cell."
+inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+outputs = model(**inputs)
+pred = torch.argmax(outputs.logits, dim=1).item()
+
+print(pred)  # Map this index back to label if needed
+```
+
+## 🛠️ Training Details
+
+- **Base model**: `microsoft/deberta-v3-base`
+- **Framework**: PyTorch
+- **Max length**: 256
+- **Batch size**: 16
+- **Epochs**: 4
+- **Loss function**: `CrossEntropyLoss`
+
+## 🔐 License
+
+Apache 2.0
+
+---
+
+📝 Fine-tuned by [mariadg](https://huggingface.co/mariadg) – for research purposes.