update lfs wrap final

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,176 @@
+---
+license: llama3
+datasets: Microsoft/ChatBench
+language: en
+base_model: meta-llama/Meta-Llama-3-8B
+library_name: peft
+tags:
+- Microsoft
+- ChatBench
+- Interactive Benchmark
+- User Simulator
+- Benchmarking
+---
+
+# chatbench-llama3-8b
+
+## Overview
+
+ChatBench Simulators are fine-tuned user simulators designed to enable automated, realistic evaluation of large language models (LLMs) through simulated user–AI conversations.
+
+Instead of recruiting human participants for every evaluation, you can use this simulator (`chatbench-llama3-8b`) to act as a proxy user. By providing a multiple-choice question (full stem plus answer options) via a CLI or Python API, the simulator generates natural user turns—asking clarifications, signaling understanding, or indicating errors—until the simulated user “accepts” an answer.
+
+These conversations can be used to compute task success rate, coherence, user satisfaction, error recovery, and latency metrics, enabling researchers and practitioners to move beyond static benchmarks and evaluate models under interactive, user-in-the-loop conditions.
+
+<p align="center">
+        <a href="https://github.com/microsoft/ChatBench">GitHub</a>&nbsp&nbsp | &nbsp&nbsp <a href="https://arxiv.org/pdf/2504.07114">Paper</a> 
+</p>
+
+
+## Model Details
+
+### Model Description
+
+- **Model type**: Causal LM (user simulator, LoRA adapter on Llama-3-8B)
+- **Base model**: meta-llama/Meta-Llama-3-8B
+- **Fine-tuned on**: microsoft/ChatBench (≈12K multi-turn QA dialogs)
+- **Languages**: English
+- **License**: Inherits from Meta-Llama-3 (llama3)
+- **Developed by**: Microsoft
+- **Contacts**: [email protected], [email protected], [email protected]
+
+### Training Setup:
+
+The model was fine-tuned end-to-end on ChatBench data using the same simulator recipe described in Section 5 of the paper. Each example is formatted as:
+
+```text
+[SYSTEM] <instruction>
+
+<previous turns>
+
+[USER] 
+→ model generates: <assistant reply> [END]
+```
+
+- **Optimizer:** AdamW
+- **Adapter**: LoRA (r=8, α=32, dropout=0.05)
+- **Quantization**: 8-bit weights with CPU offload
+- **Precision:** bf16 (trained on 4× RTX A6000 GPUs)
+- **Quantization:** 8-bit CPU offload for inference
+- **Batch size:** 1 per GPU
+- **Epochs:** 2
+- **LR:** 5e−5
+
+## Intended Uses
+
+#### Direct Use
+
+- Automated user simulation for interactive benchmarking of LLMs.
+
+- Research reproduction of the ACL’25 paper results.
+
+- Prototyping multi-turn evaluation pipelines with a mid-size simulator model.
+
+#### Out-of-Scope
+
+- Deployment in sensitive domains (healthcare, legal, financial) without expert oversight.
+
+- Open-ended creative generation (storytelling, brainstorming).
+
+- Very long-context tasks beyond the Llama-3-8B context window.
+
+## Bias, Risks, and Limitations
+
+- **Bias**: Inherits biases from Llama-3-8B pretraining and ChatBench data.
+
+- **Factual reliability**: May hallucinate or produce unrealistic user behaviors outside the training domain.
+
+- **Coverage**: Optimized for structured, multiple-choice QA; not suitable for unconstrained dialogue.
+
+- **Adapter trade-offs**: LoRA adapters may underfit compared to full fine-tunes.
+
+## How to Get Started
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# Load base Llama-3-8B in 8-bit
+base = AutoModelForCausalLM.from_pretrained(
+    "meta-llama/Meta-Llama-3-8B",
+    load_in_8bit=True,
+    device_map="auto"
+)
+
+# Load ChatBench LoRA adapter
+model = PeftModel.from_pretrained(base, "microsoft/chatbench-llama3-8b")
+
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B")
+tokenizer.pad_token = tokenizer.eos_token
+
+inputs = tokenizer(
+    "[SYSTEM] You are a user.\n\n[USER] What is 2+2?\n\n[USER] ",
+    return_tensors="pt"
+).to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens=64)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Evaluation
+
+### Perplexity
+
+We report perplexity (PPL) on held-out ChatBench data, comparing baseline `Llama3-8B` vs. fine-tuned `chatbench-llama3-8b`. 
+
+_A lower PPL means the fine-tuned model is closer (more confident) in the human-like reply it was trained on._
+
+| **Model** | **Perplexity** 
+| :----------------------- | :------------ | 
+| Llama-3-8B (baseline) | 4.14
+| **chatbench-llama3-8b** | **1.89** |
+
+### Interactive Evaluation (ACL’25 Study)
+
+- **Correlation with Human User–AI Accuracy**: +20 point improvement over unfine-tuned baselines.
+
+- **Task Success Accuracy**: Within ±5 points of real user–AI results across five MMLU subsets.
+
+- **Ablations**: Removing persona-conditioning or chain-of-thought prompts reduced coherence scores by ~10 points.
+
+Full details are available in Section 6 of the [paper](https://arxiv.org/pdf/2504.07114).
+
+## Technical Specifications
+
+### Compute Infrastructure
+
+- **Hardware**: 4× NVIDIA RTX A6000 GPUs (48GB VRAM each), 128-core x86_64 CPU
+- **Software**: Ubuntu 22.04, CUDA 12.4, PyTorch + Hugging Face Transformers + PEFT
+
+## Citation
+
+https://arxiv.org/abs/2504.07114
+
+
+#### Subjects:	Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Human-Computer Interaction (cs.HC)
+#### Cite as:	
+- arXiv:2504.07114 [cs.CL] (or arXiv:2504.07114v1 [cs.CL] for this version)
+- https://doi.org/10.48550/arXiv.2504.07114
+
+
+**BibTeX:**
+
+@misc{chang2025chatbenchstaticbenchmarkshumanai,
+      title={ChatBench: From Static Benchmarks to Human-AI Evaluation}, 
+      author={Serina Chang and Ashton Anderson and Jake M. Hofman},
+      year={2025},
+      eprint={2504.07114},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2504.07114}, 
+}
+
+**APA:**
+
+Chang, S., Anderson, A., & Hofman, J. M. (2025). ChatBench: From Static Benchmarks to Human-AI Evaluation. arXiv [Cs.CL]. Retrieved from http://arxiv.org/abs/2504.07114 
+

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checkpoint-6000/README.md

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+---
+base_model: meta-llama/Meta-Llama-3-8B
+library_name: peft
+---
+
+# 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 0.15.2.dev0

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checkpoint-6244/README.md

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+---
+base_model: meta-llama/Meta-Llama-3-8B
+library_name: peft
+---
+
+# 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 0.15.2.dev0

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