Update README.md

README.md

@@ -6,197 +6,70 @@ library_name: peft
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
+Fine Tuned meta-llama/Llama-3.2-1B-Instruct using a small sample (3000 examples) of https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k:
 
+hf (pretrained=meta-llama/Llama-3.2-1B-Instruct,dtype=float), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto:4 (64,64,64,64,64)
 
+| Tasks  |Version|Filter|n-shot|     Metric      |   | Value |   |Stderr|
+|--------|------:|------|-----:|-----------------|---|------:|---|-----:|
+|eq_bench|    2.1|none  |     0|eqbench          |↑  |22.8199|±  |3.3087|
+|        |       |none  |     0|percent_parseable|↑  |97.6608|±  |1.1592|
+Model Description
+Developed by: Meta AI (assuming the model is related to Meta’s Llama series)
 
-## Model Details
+Funded by [optional]: Meta Platforms, Inc. (or similar organization if applicable)
 
-### Model Description
+Shared by [optional]: Hugging Face (if the model is hosted there)
 
-<!-- Provide a longer summary of what this model is. -->
+Model type: Language Model (LM), specifically an Instruction-tuned transformer model
 
+Language(s) (NLP): Primarily English (confirm the language capabilities as needed)
 
+License: Apache 2.0 License (check if the original model has a specific license)
 
-- **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]
+Finetuned from model [optional]: Llama-3.2-1B-Instruct (ensure the base model details are accurate)
 
-### Model Sources [optional]
+Model Sources [optional]:
 
-<!-- Provide the basic links for the model. -->
+Repository: [Hugging Face model repository link if available]
+Dataset: https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k
+Paper [optional]: [Link to any relevant papers or documentation about the model or its base architecture]
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+Demo [optional]: [Link to any demos if available, e.g., Hugging Face Spaces]
 
-## Uses
+Uses
+Direct Use:
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+Intended for natural language understanding and generation tasks, including but not limited to question answering, text summarization, and conversational AI applications.
+Downstream Use [optional]:
 
-### Direct Use
+Can be applied in various applications such as chatbots, virtual assistants, educational tools, content generation, and other NLP tasks.
+Out-of-Scope Use:
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+May not be suitable for applications requiring high-stakes decision-making, sensitive data processing, or contexts where ethical considerations are paramount.
+Bias, Risks, and Limitations
+Bias:
 
-[More Information Needed]
+As with many language models, the model may inherit biases present in the training data, potentially reflecting cultural, social, or gender biases.
+Risks:
 
-### Downstream Use [optional]
+There is a risk of generating inappropriate or harmful content if not carefully monitored. Users should implement safety checks when deploying this model in applications.
+Limitations:
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+The model’s performance may vary based on the input complexity and domain. It may also struggle with understanding nuanced or context-heavy queries. Performance metrics from evaluation tasks should be considered when assessing its utility.
+Performance Metrics (from your data)
+Task: eq_bench
 
-[More Information Needed]
+Version: 2.1
+n-shot: 0
+Metric: eqbench
+Value: 22.8199
+Stderr: ± 3.3087
+Task: none
 
-### 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 0.13.2
+n-shot: 0
+Metric: percent_parseable
+Value: 97.6608
+Stderr: ± 1.1592
+Additional Notes
+Ensure that you validate all the placeholders with accurate and specific details about the model, its developers, and its applications as needed.