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medLlama-3-8B_DARE

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mlabonne/ChimeraLlama-3-8B-v3 as a base.

Models Merged

The following models were included in the merge:

Evaluation

  • multimedq (0 shot)
Tasks Version Filter n-shot Metric Value Stderr
- medmcqa Yaml none 0 acc 0.5728 ± 0.0076
none 0 acc_norm 0.5728 ± 0.0076
- medqa_4options Yaml none 0 acc 0.5923 ± 0.0138
none 0 acc_norm 0.5923 ± 0.0138
- anatomy (mmlu) 0 none 0 acc 0.7111 ± 0.0392
- clinical_knowledge (mmlu) 0 none 0 acc 0.7547 ± 0.0265
- college_biology (mmlu) 0 none 0 acc 0.7917 ± 0.0340
- college_medicine (mmlu) 0 none 0 acc 0.6647 ± 0.0360
- medical_genetics (mmlu) 0 none 0 acc 0.8200 ± 0.0386
- professional_medicine (mmlu) 0 none 0 acc 0.7426 ± 0.0266
stem N/A none 0 acc_norm 0.5773 ± 0.0067
none 0 acc 0.6145 ± 0.0057
- pubmedqa 1 none 0 acc 0.7400 ± 0.0196
Groups Version Filter n-shot Metric Value Stderr
stem N/A none 0 acc_norm 0.5773 ± 0.0067
none 0 acc 0.6145 ± 0.0057

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: mlabonne/ChimeraLlama-3-8B-v3
    # No parameters necessary for base model

  - model: sethuiyer/Medichat-Llama3-8B
    parameters:
      density: 0.53
      weight: 0.5
  - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
    parameters:
      density: 0.53
      weight: 0.5
      
merge_method: dare_ties
base_model: mlabonne/ChimeraLlama-3-8B-v3
parameters:
  int8_mask: true
dtype: float16
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