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Adding Evaluation Results
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metadata
license: apache-2.0
tags:
  - finetuned
pipeline_tag: text-generation
model-index:
  - name: deepseek-coder-1.3b-chat-and-function-calling
    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: 26.28
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          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: 39.27
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          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: 26.92
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          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: 43.37
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          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: 51.7
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          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: 3.41
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-1.3b-chat-and-function-calling
          name: Open LLM Leaderboard

deepseek-coder-1.3b-chat-and-function-calling

It was created by starting with the deepseek-coder-1.3b and training it on the open assistant dataset then training yhat on function calling. We have attached the wandb report in pdf form to view the training run at a glance.

Reson

This model was fine tuned to allow it to work with the openai syntask and will return function when apperate.

Templete

Us the following templete when interacting with the fine tuned model.

Referrals

Run Pod - This is who I use to train th emodels on huggingface. If you use it we both get free crdits. - Visit Runpod's Website!

Paypal - If you want to leave a tip, it is appecaheted. - Visit My Paypal!

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 31.82
AI2 Reasoning Challenge (25-Shot) 26.28
HellaSwag (10-Shot) 39.27
MMLU (5-Shot) 26.92
TruthfulQA (0-shot) 43.37
Winogrande (5-shot) 51.70
GSM8k (5-shot) 3.41