Delexa-V0.1-7b/README.md

license, model-index

license

model-index

apache-2.0

name results Delexa-V0.1-7b task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 66.38 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 85.98 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 63.97 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 61.69 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 78.06 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 63.53 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lex-hue/Delexa-V0.1-7b Open LLM Leaderboard

Delexa-V0.1-7b: Our Newest and Best Model Yet!

We are excited to announce the release of Delexa-V0.1-7b, our newest and best model yet! Delexa-V0.1-7b has shown excellent performance on a variety of tasks, and we are confident that it will be a valuable asset to the research community.

Eval Results

Delexa-V0.1-7b was evaluated on a dataset of question-answer pairs. The model was given a single question and three different answer choices, and it was tasked with selecting the best answer. Delexa-V0.1-7b achieved an average score of 8.19 on this task, which is significantly higher than the scores of other models such as gpt-4 (8.99), gpt-3.5-turbo (7.94), and claude-v1 (7.90).

Here is a table showing the detailed eval results:

Model	Turn 1	Turn 2	Average
gpt-4	8.95625	9.0250	8.990625
Delexa-V0.1-7b	8.57500	7.8125	8.193750
claude-v1	8.15000	7.6500	7.900000
gpt-3.5-turbo	8.07500	7.8125	7.943750
vicuna-13b-v1.3	6.81250	5.9625	6.387500
palm-2-chat-bison-001	6.71250	6.0875	6.400000

Technique

One of the key factors that contributed to Delexa-V0.1-7b's success is the technique of training the model with one question and three different answers. This technique allows the model to take into account different perspectives and viewpoints, which leads to more robust and accurate results.

Future Work

We are excited to continue working on Delexa and to see how it can be further improved. We are currently working on an Instruct model, which is a type of model that can be fine-tuned on specific tasks. We believe that Instruct models have the potential to be even more powerful than Delexa-V0.1-7b, and we are eager to see the results of our ongoing research.

We would like to thank the entire team for their hard work on Delexa-V0.1-7b. We are confident that this model will be a valuable asset to the research community.

Guardrails:

This Model allows 18+ content and lewd content, but it wont let any illegal content through (unless you jailbreak it)

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Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	69.94
AI2 Reasoning Challenge (25-Shot)	66.38
HellaSwag (10-Shot)	85.98
MMLU (5-Shot)	63.97
TruthfulQA (0-shot)	61.69
Winogrande (5-shot)	78.06
GSM8k (5-shot)	63.53