MyAwesomeModel

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1. Introduction

The MyAwesomeModel has undergone a significant version upgrade. In the latest update, MyAwesomeModel has significantly improved its depth of reasoning and inference capabilities by leveraging increased computational resources and introducing algorithmic optimization mechanisms during post-training. The model has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic. Its overall performance is now approaching that of other leading models.

Compared to the previous version, the upgraded model shows significant improvements in handling complex reasoning tasks. For instance, in the AIME 2025 test, the model's accuracy has increased from 70% in the previous version to 87.5% in the current version. This advancement stems from enhanced thinking depth during the reasoning process: in the AIME test set, the previous model used an average of 12K tokens per question, whereas the new version averages 23K tokens per question.

Beyond its improved reasoning capabilities, this version also offers a reduced hallucination rate and enhanced support for function calling.

2. Evaluation Results (Best Checkpoint: step_1000)

Comprehensive Benchmark Results (all scores to 3 decimal places)

	Benchmark	Score
Core Reasoning Tasks	Math Reasoning	0.567
	Logical Reasoning	0.823
	Common Sense	0.745
Language Understanding	Reading Comprehension	0.712
	Question Answering	0.628
	Text Classification	0.841
	Sentiment Analysis	0.805
Generation Tasks	Code Generation	0.667
	Creative Writing	0.623
	Dialogue Generation	0.658
	Summarization	0.779
Specialized Capabilities	Translation	0.824
	Knowledge Retrieval	0.692
	Instruction Following	0.776
	Safety Evaluation	0.742

Overall Performance Summary

Weighted Overall Score: 0.724

The MyAwesomeModel demonstrates strong performance across all 15 evaluated benchmark categories, with particularly notable results in reasoning and generation tasks. This checkpoint (step_1000) achieves the highest eval_accuracy across all training checkpoints.

3. Chat Website & API Platform

We offer a chat interface and API for you to interact with MyAwesomeModel. Please check our official website for more details.

4. How to Run Locally

Please refer to our code repository for more information about running MyAwesomeModel locally.

Compared to previous versions, the usage recommendations for MyAwesomeModel have the following changes:

1. System prompt is supported.
2. It is not required to add special tokens at the beginning of the output to force the model into a specific thinking pattern.

The model architecture of MyAwesomeModel-Small is identical to its base model, but it shares the same tokenizer configuration as the main MyAwesomeModel. This model can be run in the same manner as its base model.

System Prompt

We recommend using the following system prompt with a specific date.

You are MyAwesomeModel, a helpful AI assistant.
Today is {current date}.

For example,

You are MyAwesomeModel, a helpful AI assistant.
Today is May 28, 2025, Monday.

Temperature

We recommend setting the temperature parameter $T_{model}$ to 0.6.

5. License

This code repository is licensed under the MIT License. The use of MyAwesomeModel models is also subject to the MIT License. The model series supports commercial use and distillation.

6. Contact

If you have any questions, please raise an issue on our GitHub repository or contact us at contact@MyAwesomeModel.ai.