🚀Mixture of Expert (MoE) TEST
Collection
MoE done using mergekit
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4 items
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Updated
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2
This is a merge of pre-trained language models created using mergekit.
This model was merged using the DARE TIES merge method using mlabonne/ChimeraLlama-3-8B-v3 as a base.
The following models were included in the merge:
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 |
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