ptkag1712
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gpt2-based-on-paraSCI_dataset

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+tags:
+- text-generation
+- paraphrase
+- gpt2
+- causal-lm
+- transformers
+- pytorch
+license: mit
+datasets:
+- HHousen/ParaSCI
+language:
+- en
+base_model:
+- openai-community/gpt2
+pipeline_tag: text-generation
 ---
+# Model Card for `gpt2-parasciparaphrase`
+## 🧠 Model Summary
+This model is a fine-tuned version of [GPT-2](https://huggingface.co/gpt2) on the [ParaSCI dataset](https://huggingface.co/datasets/HHousen/ParaSCI) for paraphrase generation. It takes a sentence as input and generates a paraphrased version of that sentence.
+---
+## 📋 Model Details
+- **Base model:** GPT-2 (`gpt2`)
+- **Task:** Paraphrase generation (Causal Language Modeling)
+- **Language:** English
+- **Training data:** [HHousen/ParaSCI](https://huggingface.co/datasets/HHousen/ParaSCI)
+- **Training steps:** 1 epoch on ~270k examples
+- **Precision:** `fp16` mixed precision
+- **Hardware used:** Tesla T4 (Kaggle Notebook GPU)
+- **Framework:** 🤗 Transformers, PyTorch
+- **Trained by:** [Your Name or HF Username]
+- **License:** MIT
+---
+## 💡 Intended Use
+### ✅ Direct Use
+- Generate paraphrased versions of input English sentences in a general academic/technical writing context.
+### 🚫 Out-of-Scope Use
+- Not suitable for paraphrasing code, informal language, or other languages (non-English).
+- Not tested for fairness, bias, or ethical use in downstream applications.
+---
+## 📊 Evaluation
+- **Qualitative Evaluation:** Manual checks indicate coherent paraphrased outputs.
+- **Automatic Metrics:** Not yet reported.
+---
+## 🛠 Training Details
+- **Dataset:** ParaSCI (`sentence1` → `sentence2`)
+- **Preprocessing:** Concatenated prompt `paraphrase this sentence: {sentence1}\n{sentence2}`
+- **Tokenizer:** GPT-2 tokenizer with `pad_token = eos_token`
+- **Batch size:** 8
+- **Epochs:** 1
+- **Learning rate:** 5e-5
+- **Logging and checkpointing:** Every 500 steps, using Weights & Biases (`wandb`)
+- **Max sequence length:** 256 tokens
+---
+## 🏁 How to Use
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model = AutoModelForCausalLM.from_pretrained("your-username/gpt2-parasciparaphrase")
+tokenizer = AutoTokenizer.from_pretrained("your-username/gpt2-parasciparaphrase")
+input_text = "paraphrase this sentence: AI models can help in automating tasks.\n"
+input_ids = tokenizer.encode(input_text, return_tensors="pt")
+output = model.generate(input_ids, max_new_tokens=50, do_sample=True, top_k=50, top_p=0.95)
+print(tokenizer.decode(output[0], skip_special_tokens=True))