• Model creator: https://huggingface.co/fblgit/
• Original model: https://huggingface.co/fblgit/UNA-SimpleSmaug-34b-v1beta/

Original model description:

• UNA
• simple-math
• juanako base_model: abacusai/Smaug-34B-v0.1 datasets:
• fblgit/simple-math
• jondurbin/bagel-v0.3 model-index:
• name: UNA-SimpleSmaug-34b-v1beta results:
  • task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
    • type: acc_norm value: 74.57 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
    • type: acc_norm value: 86.74 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
    • type: acc value: 76.68 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
    • type: mc2 value: 70.17 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
    • type: acc value: 83.82 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
    • type: acc value: 72.48 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-SimpleSmaug-34b-v1beta name: Open LLM Leaderboard

UNA-SimpleSmaug-34b-v1beta

==== And people wonders.. why there is no UNA of Hermes or Smaug 70B? << i dont think is worth the time to spend on a model that is widely known for not being too useful, likely UNA can fix some of the internal mess.. for Hermes, we spoke chitchat quick a couple times but nothing solid, but we would like to make a reborn of excellent models using UNA, just liek we did with UNA-Dolphin where we saw relevant performance is short time.

Applied UNA only on the Attention, not on the MLP's

• Is based on Smaug
• SimpleMath dataset
• It was trained on Axolotl

Experiment

Evals

|    Task     |Version| Metric |Value            |
|-------------|------:|--------|----------------:|
|arc_challenge|     HF|acc_norm| 0.7457337883959 |
|gsm8k        |     HF|acc     | 0.7247915087187 |
|mmlu         |     HF|acc     | 0.7649553475572 |
|mmlu         |     HF|acc_norm| 0.7681713551647 |
|hellaswag    |     HF|acc_norm| 0.8673571001792 | 
|truthfulqa   |     HF|mc2     | 0.7016557407771 |
|winogrande   |     HF|acc     | 0.8382004735595 |
|------------------------------------------------|

Citations

Open LLM Leaderboard Evaluation Results