Chimera_MedLlama-3-8B

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

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Evaluation

  • multimedqa (0 shot)
Tasks Version Filter n-shot Metric Value Stderr
- medmcqa Yaml none 0 acc 0.6087 ± 0.0075
none 0 acc_norm 0.6087 ± 0.0075
- medqa_4options Yaml none 0 acc 0.6269 ± 0.0136
none 0 acc_norm 0.6269 ± 0.0136
- anatomy (mmlu) 0 none 0 acc 0.6963 ± 0.0397
- clinical_knowledge (mmlu) 0 none 0 acc 0.7585 ± 0.0263
- college_biology (mmlu) 0 none 0 acc 0.7847 ± 0.0344
- college_medicine (mmlu) 0 none 0 acc 0.6936 ± 0.0351
- medical_genetics (mmlu) 0 none 0 acc 0.8200 ± 0.0386
- professional_medicine (mmlu) 0 none 0 acc 0.7684 ± 0.0256
stem N/A none 0 acc_norm 0.6129 ± 0.0066
none 0 acc 0.6440 ± 0.0057
- pubmedqa 1 none 0 acc 0.7480 ± 0.0194
Groups Version Filter n-shot Metric Value Stderr
stem N/A none 0 acc_norm 0.6129 ± 0.0066
none 0 acc 0.6440 ± 0.0057

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: mlabonne/ChimeraLlama-3-8B-v3
        layer_range: [0, 32]
      - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
        layer_range: [0, 32]
merge_method: slerp
base_model:  mlabonne/ChimeraLlama-3-8B-v3
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16


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