Update README.md

README.md

@@ -1,208 +1,146 @@
 ---
-base_model: unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit
+base_model: unsloth/Qwen3-4B-Instruct-2507
+datasets:
+- u-10bei/structured_data_with_cot_dataset_512_v2
+- u-10bei/structured_data_with_cot_dataset_512_v4
+- u-10bei/structured_data_with_cot_dataset_512_v5
+language:
+- en
+license: apache-2.0
 library_name: peft
 pipeline_tag: text-generation
 tags:
-- base_model:adapter:unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit
+- qlora
 - lora
-- transformers
-- unsloth
+- structured-output
+- phase1
 ---
 
-# Model Card for Model ID
+# Qwen3-4B Structured Output LoRA (Phase 1)
 
-<!-- Provide a quick summary of what the model is/does. -->
+This repository provides a **LoRA adapter** fine-tuned from  
+**unsloth/Qwen3-4B-Instruct-2507** using **QLoRA with Unsloth**.
 
+It is designed to improve the model’s ability to generate **structured outputs** such as:
 
+- JSON  
+- YAML  
+- XML  
+- CSV  
+- other machine-readable formats  
 
-## 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
+## What This Repository Contains
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+⚠ **Important**
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+This repository contains **LoRA adapter weights only**.  
+It does **not** include the base model.
 
-## How to Get Started with the Model
+To use this adapter, you must load it on top of the original base model:
 
-Use the code below to get started with the model.
+```
+unsloth/Qwen3-4B-Instruct-2507
+```
 
-[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 Phase
 
+This adapter was trained as **Phase 1** using the following datasets:
 
-#### Training Hyperparameters
+- `u-10bei/structured_data_with_cot_dataset_512_v2`
+- `u-10bei/structured_data_with_cot_dataset_512_v4`
+- `u-10bei/structured_data_with_cot_dataset_512_v5`
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+Further training (Phase 2) may be performed later using additional datasets.
 
-#### 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
+### Training Method
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+- Method: **QLoRA (4-bit)**
+- Framework: **Unsloth + PEFT**
+- Base model: `unsloth/Qwen3-4B-Instruct-2507`
+- Maximum sequence length: 1024
+- Loss applied only to final assistant output  
+- Intermediate Chain-of-Thought reasoning is masked
 
-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]
+### Hyperparameters (Phase 1)
 
-## Technical Specifications [optional]
+- LoRA rank (r): 64  
+- LoRA alpha: 128  
+- Learning rate: 1e-4  
+- Epochs: 1  
+- Batch size: 2  
+- Gradient accumulation: 8  
 
-### Model Architecture and Objective
+---
 
-[More Information Needed]
+## How to Use
 
-### Compute Infrastructure
+Example Python code to load and use this adapter:
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+import torch
 
-#### Hardware
+base_model = "unsloth/Qwen3-4B-Instruct-2507"
+adapter = "cinnamonrooo/qwen3-structeval-phase1"
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained(base_model)
 
-#### Software
+model = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
 
-[More Information Needed]
+model = PeftModel.from_pretrained(model, adapter)
 
-## Citation [optional]
+prompt = "Convert the following text into JSON format:\nName: John\nAge: 25"
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=200)
 
-**BibTeX:**
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
 
-[More Information Needed]
+---
 
-**APA:**
+## License and Terms
 
-[More Information Needed]
+- Training datasets: MIT License  
+- Base model: subject to original model license  
+- This adapter follows **Apache 2.0 License**
 
-## Glossary [optional]
+Users must comply with both:
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+1. The dataset license  
+2. The original base model terms  
 
-[More Information Needed]
+---
 
-## More Information [optional]
+## Notes
 
-[More Information Needed]
+- This adapter is optimized for **structured generation tasks**  
+- It may not improve general conversational performance  
+- Designed primarily for format-following and machine-readable output accuracy  
 
-## Model Card Authors [optional]
+---
 
-[More Information Needed]
+### Future Plans
 
-## Model Card Contact
+- Additional training with more datasets (Phase 2)
+- Evaluation on structured output benchmarks
+- Possible quantized release versions
 
-[More Information Needed]
-### Framework versions
+---
 
-- PEFT 0.18.1
+If you have any questions or feedback, feel free to open an issue.