Update README.md

README.md

@@ -1,194 +1,71 @@
 ---
 library_name: peft
 base_model: mistralai/Mistral-7B-Instruct-v0.2
+license: apache-2.0
+language:
+- en
 ---
 
-# Model Card for Model ID
+# Suri-I-ORPO
+Suri-I-ORPO is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 using instructional odds ratio preference optimization (I-ORPO). Please check [our paper](TODO) for more details on the method. 
 
-## Model Details
+## 📒 Model Details
 
 ### Model Description
 
-- **Developed by:**
-- **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]
+- **Language(s) (NLP):** English
+- **License:** Apache-2.0
+- **Finetuned from model:** [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
 
-### Model Sources [optional]
+### Model Sources
 
-<!-- Provide the basic links for the model. -->
+- **Repository:** [Github repository](https://github.com/chtmp223/suri) -- contains code to reconstruct books3 subset. 
+- **Paper:** TODO
+- **Demo:** [Website](https://chtmp223.github.io/suri)
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+## ⚠️ Getting Started
 
-## Uses
+Use the code in [this repository](https://github.com/chtmp223/suri) for training and inference. 
 
-<!-- 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 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]
+[chtmp223/suri](https://huggingface.co/datasets/chtmp223/suri)
 
 ### 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
+| **Configurations**               | **Values**   |
+|----------------------------------|--------------|
+| Hardware (Training and Inference)| 4xA100s      |
+| Tracking                         | wandb        |
+| lora_r                           | 16           |
+| lora_alpha                       | 16           |
+| lora_dropout                     | 0.05         |
+| beta                             | 0.4          |
+| gradient_accumulation_steps      | 1            |
+| gradient_checkpointing           | True         |
+| learning_rate                    | 5.0e-5       |
+| lr_scheduler_type                | cosine       |
+| max_length                       | 15024        |
+| max_completion_length            | 15000        |
+| max_prompt_length                | 5000         |
+| num_train_epochs                 | 2            |
+| optim                            | adamw_torch  |
+| per_device_train_batch_size      | 1            |
+
+
+#### 🤗 Software
+
+Training code is adapted from [Alignment Handbook](https://github.com/huggingface/alignment-handbook) and [Trl](https://github.com/huggingface/trl).
+
+## 📜 Citation 
+
+```
+TODO
+```
+
+### ⚙️ Framework versions
 
 - PEFT 0.11.1