metadata

language:
  - en
license: mit
library_name: adapter-transformers
datasets:
  - argilla/distilabel-intel-orca-dpo-pairs
  - jondurbin/truthy-dpo-v0.1
  - argilla/distilabel-math-preference-dpo
  - argilla/distilabel-capybara-dpo-7k-binarized
base_model: Technoculture/MT7Bi-sft
model-index:
  - name: MedMerge-6-7b-alpha-dpo
    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: 54.27
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          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: 75.6
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          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: 52.65
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          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: 43.94
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          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: 71.03
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          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: 26.16
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
          name: Open LLM Leaderboard

Technoculture/MedMerge-6-7b-alpha-dpo

Open LLM Leaderboard

Model Name	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
Orca-2-7b	78.4	76.1	53.7	52.4	74.2	47.2
LLAMA-2-7b	43.2	77.1	44.4	38.7	69.5	16
MT7Bi-sft	54.1	75.11	-	43.08	72.14	15.54
MedMerge-6-7b	29.52	41.04	-	37.53	59.35	0.91
MedMerge-6-7b-alpha-dpo	54.27	75.6	52.65	43.94	71.03	26.16

Training Details

GPU: Nvidia A100 Tensor Core GPU
Total Batches: 4266
Epochs: 3
Duration: 3 hours, 57 minutes, and 00 seconds

DPO Training Dataset Mixture

Dataset Name	Original Size(Rows)	Ratio	Size After Ratio(Rows)
argilla/distilabel-math-preference-dpo	2.4k	1.0	2.4k
argilla/distilabel-intel-orca-dpo-pairs	12.9k	0.5	6.45k
jondurbin/truthy-dpo-v0.1	1.04k	1.0	1.04k
argilla/distilabel-capybara-dpo-7k-binarized	7.5k	0.2	1.5k
Total Size: 11.38k

Training Loss Plot

Training Loss Smoothed Plot

For full details of this dpo-training please read our notebook.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MedMerge-6-7b-alpha-dpo)

Metric	Value
Avg.	53.94
AI2 Reasoning Challenge (25-Shot)	54.27
HellaSwag (10-Shot)	75.60
MMLU (5-Shot)	52.65
TruthfulQA (0-shot)	43.94
Winogrande (5-shot)	71.03
GSM8k (5-shot)	26.16