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README.md

@@ -1,79 +1,207 @@
 ---
-license: mit
-datasets:
-- SohamGhadge/casual-conversation
-language:
-- en
-base_model:
-- openai-community/gpt2-medium
-pipeline_tag: question-answering
+base_model: openai-community/gpt2-medium
+library_name: peft
+pipeline_tag: text-generation
 tags:
+- base_model:adapter:openai-community/gpt2-medium
+- lora
 - transformers
-- peft
-- gpt2
 ---
 
-## 🧠 Fine-Tuned GPT-2 Medium for Conversational AI
-This project fine-tunes the `gpt2-medium` language model to support natural, casual **conversational dialogue** using **PEFT + LoRA**.
----
-### 🚀 Model Summary
-* **Base model**: `gpt2-medium`
-* **Objective**: Enable natural question-answering and dialogue
-* **Training method**: Supervised Fine-Tuning (SFT) using PEFT with LoRA adapters
-* **Tokenizer**: `gpt2` (same as base model)
----
-### 📈 Training Metrics
-| Metric              | Value          |
-| ------------------- | -------------- |
-| Global Steps        | 2611           |
-| Final Training Loss | 2.185          |
-| Training Runtime    | 430.61 seconds |
-| Samples/sec         | 138.41         |
-| Steps/sec           | 17.32          |
-| Total FLOPs         | 1.12 × 10¹⁵    |
-| Epochs              | 7.0            |
-> These metrics reflect final performance after complete training.
----
-### 💬 Inference Script
-Chat with the model using the `talk()` function below:
-```python
-def talk(model=peft_model, tokenizer=tokenizer, device=device):
-    print("Start chatting with the bot! Type 'exit' to stop.\n")
-    while True:
-        question = input("You: ")
-        if question.lower() == "exit":
-            print("Goodbye!")
-            break
-
-        prompt = f"User: {question}\nBot:"
-        inputs = tokenizer(prompt, return_tensors="pt").to(device)
-
-        with torch.no_grad():
-            outputs = model.generate(
-                **inputs,
-                max_new_tokens=20,
-                do_sample=True,
-                temperature=0.7,
-                top_p=0.9,
-                pad_token_id=tokenizer.eos_token_id
-            )
-
-        response = tokenizer.decode(
-            outputs[0][inputs["input_ids"].shape[-1]:],
-            skip_special_tokens=True
-        )
-
-        # Clean response
-        response = response.split(".")
-        response = ".".join(response[:-1]) + "."
-        print("Bot:", response.strip())
-```
-
-* 🤖 **Stateless**: No memory across turns (yet).
-* 🌱 **Future idea**: Add memory/context for multi-turn dialogue.
----
-### ⚙️ Quick Setup
-To use this model locally:
-```bash
-pip install transformers peft accelerate
-```
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.0

adapter_config.json

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special_tokens_map.json

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tokenizer_config.json

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