README.md

metadata

license: mit
widget:
  - text: |-
      <|user|>
      Can you tell me a space adventure story?</s>
      <|assistant|>
model-index:
  - name: 160M-TinyLLama-Mini-Cinder
    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: 24.66
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          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: 28.16
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          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: 25.09
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          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: 44.08
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          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: 52.57
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          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: 0
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/160M-TinyLLama-Mini-Cinder
          name: Open LLM Leaderboard

Model trained on Tiny Stories. Followed up with conversations datasets, followed up with trimmed Cinder Dataset. Mini Cinder is ok at conversation and story telling for kids stories.

Overview Cinder is an AI chatbot tailored for engaging users in scientific and educational conversations, offering companionship, and sparking imaginative exploration. This Cinder still has a lot to learn but is very friendly and enjoys telling stories.

Main Character Cinder: AI companion and quirky robot. Cozmo: The silly one. Vector: The serious one. Computer Voice: The narrator. User: Ship member.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.09
AI2 Reasoning Challenge (25-Shot)	24.66
HellaSwag (10-Shot)	28.16
MMLU (5-Shot)	25.09
TruthfulQA (0-shot)	44.08
Winogrande (5-shot)	52.57
GSM8k (5-shot)	0.00