README.md

metadata

license: apache-2.0
library_name: transformers
tags:
  - trl
  - sft
base_model:
  - nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated
datasets:
  - HuggingFaceTB/smoltalk
model-index:
  - name: SmolNemo-12B-FFT-experimental
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 33.48
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 6.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 0.23
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 1.34
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 5.92
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 2.41
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/SmolNemo-12B-FFT-experimental
          name: Open LLM Leaderboard

🧪 Just Another Model Experiment

This is one of many experimental iterations I'm sharing publicly while I mess around with training parameters and ideas. It's not a "real" release - just me being transparent about my learning process. Feel free to look under the hood, but don't expect anything production-ready!

SmolNemo-12B-FFT-experimental

Mahou-1.5-mistral-nemo-12B-lorablated finetuned on HuggingFaceTB/smoltalk.

This model has erratic behavior and poor performance

Method

SFT with 8x A100 for 0.1 epochs.

This was a full finetune. I think the issues with the model can be chalked up to conflicts with Mistral Instruct and ChatML.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	8.32
IFEval (0-Shot)	33.48
BBH (3-Shot)	6.54
MATH Lvl 5 (4-Shot)	0.23
GPQA (0-shot)	1.34
MuSR (0-shot)	5.92
MMLU-PRO (5-shot)	2.41