Microsoft's Phi 1.5: A New Language Model

Introduction

Microsoft has recently introduced a new language model called Phi 1.5. Despite having fewer parameters compared to larger models in the industry, Phi 1.5 performs exceptionally well. It offers unique features that make it ideal for tasks such as question answering, chat, and code generation. In this blog, we will explore what Phi 1.5 is, how it works, what it can do, and why it is considered an awesome language model.

Understanding Transformer Models

Before diving into Phi 1.5, let's first understand what a Transformer model is. Essentially, a Transformer model is a type of neural network that excels at understanding context and data, whether it be words or pixels. It achieves this through a mechanism called attention, which allows it to focus on important parts of the input and process long sequences more efficiently compared to older models such as recurrent neural networks (RNNs) or convolutional neural networks (CNNs).

The concept of Transformers was introduced by Google in 2017 through their groundbreaking paper titled "Attention Is All You Need". Since then, Transformers have gained widespread usage in various language-related tasks such as translation, text summarization, and sentiment analysis. They have also found applications in fields like computer vision and speech recognition.

What Makes Phi 1.5 Stand Out?

Phi 1.5, developed by Microsoft Research, builds upon the foundation of the gpt2 architecture but incorporates unique features and enhancements. Unlike many language models, Phi 1.5 doesn't rely solely on web data for training. Instead, it leverages diverse sources of knowledge, including pieces of Python code from stack Overflow, coding competition samples, synthetic Python textbooks, and exercises generated by GPT 3.5 Turbo 0.0301, which is a smaller version of gpt3.

This multi-source training approach equips Phi 1.5 with a strong understanding of programming languages and logic, making it particularly useful for tasks like code generation and error fixing. Additionally, Phi 1.5 benefits from various NLP synthetic texts. These texts are generated by other language models or computer algorithms and follow specific rules. They help Phi 1.5 develop a deeper understanding of language intricacies, enhancing its ability to comprehend and generate text.

Phi 1.5 also utilizes cutting-edge software tools to improve its training process. One notable tool is deep speed, which optimizes deep learning on PyTorch. Thanks to deep speed, Phi 1.5 can learn faster using multiple GPUs while consuming less memory and reducing data exchange time. Another crucial tool incorporated is Flash attention, an algorithm that rearranges attention computations using established methods like tiling and recomputation. This leads to faster attention processing and reduces memory usage, resulting in more efficient training.

Impressive Performance on Benchmark Tests

Phi 1.5 has demonstrated remarkable performance on various benchmark tests designed to evaluate its common sense understanding of language and logical thinking. In the AGI eval Benchmark, which assesses foundational models using exams like SAT, LSAT, and math competitions, Phi 1.5 outperforms the average person and even surpasses meta's llama27b, a set of text models with billions of parameters. Specifically, Phi 1.5 scores 95% on the SAT math test and achieves a 92.5% score on the English section of the Chinese college entrance exam.

In the gpt4 all's Benchmark Suite with lme Val harness, which tests language models on over 200 tasks, Phi 1.5 performs on par with llama27b and outperforms other models like gpt3 chat GPT and text DaVinci 003 in most tasks. These results highlight Phi 1.5 as a top performer among models with fewer than 10 billion parameters. It showcases not only its text generation capabilities but also its exceptional comprehension and sense-making abilities.

Limitations and Safety Concerns

While Phi 1.5 is a powerful language model, it does have its limitations. One potential issue is that it may provide more information than requested. For example, if you ask who the U.S. president is, Phi 1.5 might not only provide the answer (Joe Biden) but also offer additional details about his election and age, which may not always be desired.

Additionally, when dealing with complex topics, particularly in fields like mathematics or engineering, Phi 1.5 may not deliver optimal answers. This is because certain topics require more than just language understanding; they necessitate specialized skills and domain-specific knowledge.

Another crucial consideration is the safety of Phi 1.5 and similar models. AI models can sometimes produce biased or offensive content due to the biases present in the training data. Although Microsoft has taken precautions to make Phi 1.5 safer, it is important to acknowledge that it is not perfect in this regard. Users must exercise responsibility while utilizing this model and be mindful of potential biases that may arise.

Open Source Model for Research

Microsoft has generously released Phi 1.5 as an open-source model under a research license. This means that researchers can freely download and utilize it for research purposes. This contribution to the research community provides an unrestricted, smaller model that enables exploration of essential safety challenges and furthers our understanding of large language models.

Conclusion

Microsoft's Phi 1.5 language model introduces exciting advancements in the field of natural language processing. With its unique features, multi-source knowledge, and state-of-the-art software tools, Phi 1.5 delivers impressive performance on benchmark tests, showcasing its common sense understanding of language and logical thinking.

While Phi 1.5 has its limitations and safety concerns, it represents a significant step forward in language modeling. By making Phi 1.5 open source for research purposes, Microsoft encourages further exploration into safety challenges and the improvement of large language models.

We hope you found this blog informative and enjoyed learning about Microsoft's Phi 1.5 language model. If you have any questions or comments, please feel free to leave them down below.

Thank you for reading!