license: mit
datasets:
- meta-llama/Meta-Llama-3.1-405B-Instruct-evals
language:
- en
metrics:
- accuracy
- bleu
pipeline_tag: text-generation
tags:
- llama
- conversational
- text-generation
- emergency-response
- environmental-issues
This article provides a detailed overview of the TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model, which has been fine-tuned for specific use cases in emergencies and environmental issues. The model was developed as part of a hackathon and is designed to assist in generating responses related to these domains. Model Details Model Description
The TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model is a fine-tuned version of the TinyLlama-1.1B-Chat-v1.0, optimized for generating text in response to queries related to emergencies and environmental issues. This model was trained on synthetic data generated using the Meta-Llama-3.1-405B-Instruct-Turbo model, with the fine-tuning process conducted on Kaggle using T4 x2 GPUs in about 2 Hours Approx.
Developed by: Mixed Intelligence Team, led by Umar Majeed
Umar Majeed (Team Lead) www.linkedin.com/in/umarmajeedofficial
Mixed Intelligence Team Members:
Moazzan Hassan https://www.linkedin.com/in/moazzan-hassan/
Shahroz Butt https://www.linkedin.com/in/shahroz-butt-69a813211?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Sidra Hammed https://www.linkedin.com/in/sidra-hameed-8s122000?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Muskan Liaqat https://www.linkedin.com/in/muskan-liaquat-838880308?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Sana Qaisar https://www.linkedin.com/in/sana-qaisar-03b354316/
Model Sources
Repository: https://huggingface.co/umarmajeedofficial/TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence
Uses Direct Use
The TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model is intended to be used directly in applications requiring text generation related to emergencies and environmental issues. It is suitable for chatbot implementations, emergency response systems, and educational tools focusing on environmental awareness. Downstream Use
The model can be further fine-tuned or integrated into larger systems where specific domain knowledge or custom applications are required. Out-of-Scope Use
The model is not suitable for general-purpose text generation tasks unrelated to its fine-tuned domain. Misuse of generating harmful or misleading information is strongly discouraged. Bias, Risks, and Limitations
The TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model, while fine-tuned on specific data, may still exhibit biases present in the original TinyLlama model. Users should be aware of potential biases, especially in sensitive contexts such as emergency responses. Recommendations
Awareness: Users should be mindful of the model's limitations and biases.
Testing: It is recommended to test the model thoroughly in the intended environment before deployment.
How to Get Started with the Model
To get started with the MyFriend model, use the code snippet below
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="uumarmajeedofficial/TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence", torch_dtype=torch.bfloat16, device_map="auto")
messages = [
{
"role": "system",
"content": "You are an emergency response assistant with expertise in environmental issues.",
},
{"role": "user", "content": "What should I do during a heat wave?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Training Details Training Data
The model was fine-tuned using synthetic data generated from the Meta-Llama-3.1-405B-Instruct-Turbo model. This data was specifically designed to cover a wide range of scenarios related to emergencies and environmental issues which contain approx 2002 Questions Answers Pairs. Training Procedure
Preprocessing: The data was preprocessed to ensure relevance and quality for the fine-tuning task.
Training Hyperparameters: The model was trained using a mixed precision training regime on Kaggle with T4 x2 GPUs.
Evaluation Testing Data, Factors & Metrics Testing Data
Testing was conducted on a subset of the synthetic data generated, with evaluations focusing on the model's ability to provide accurate and contextually appropriate responses in emergency and environmental scenarios. Metrics
Accuracy: The model's ability to generate correct information.
Relevance: The relevance of the generated text to the input query.
Bias Analysis: Evaluation of potential biases in the responses.
Results
The TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model showed strong performance in generating accurate and relevant responses within its fine-tuned domain. Further details on evaluation metrics and results can be found in the repository. Environmental Impact
The environmental impact of training the MyFriend model was minimized by leveraging efficient hardware and cloud resources. The model was trained on Kaggle with T4 x2 GPUs, balancing performance and energy consumption.
Hardware Type: T4 x2 GPUs
Hours used: Approximately 2 hours
Cloud Provider: Kaggle
Technical Specifications Model Architecture and Objective
The TinyLlama-1.1B-Chat-v1.0-FineTuned-By-MixedIntelligence model is built on the TinyLlama architecture, with a focus on conversational text generation. Compute Infrastructure
Hardware: T4 x2 GPUs
Software: The model was fine-tuned using the Hugging Face Transformers library.
Model Card Authors
Umar Majeed (Team Lead) www.linkedin.com/in/umarmajeedofficial
Mixed Intelligence Team Members:
Moazzan Hassan https://www.linkedin.com/in/moazzan-hassan/
Shahroz Butt https://www.linkedin.com/in/shahroz-butt-69a813211?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Sidra Hammed https://www.linkedin.com/in/sidra-hameed-8s122000?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Muskan Liaqat https://www.linkedin.com/in/muskan-liaquat-838880308?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app
Sana Qaisar https://www.linkedin.com/in/sana-qaisar-03b354316/
Model Card Contact
For further information or inquiries, please contact Umar Majeed via Hugging Face.