This a TinyLlama mix merge, experimental, using a custom merge method. Should be better at RP.
merge_method: task_swapping
base_model: Doctor-Shotgun/TinyLlama-1.1B-32k
models:
- model: cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
parameters:
weight: 0.75
diagonal_offset: 5
- model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
parameters:
weight: 0.85
diagonal_offset: 17
invert_offset: True
dtype: bfloat16
name: bye
---
merge_method: task_swapping
base_model: Doctor-Shotgun/TinyLlama-1.1B-32k-Instruct
models:
- model: vihangd/DopeyTinyLlama-1.1B-v1
parameters:
weight: 0.8
diagonal_offset: 3
invert_offset: False
dtype: bfloat16
name: hello
---
merge_method: task_arithmetic
base_model: Doctor-Shotgun/TinyLlama-1.1B-32k
models:
- model: hello
parameters:
weight: 0.66
- model: bye+Anarchist/PIPPA_LORA_TinyLlama
parameters:
weight: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 32.99 |
AI2 Reasoning Challenge (25-Shot) | 31.48 |
HellaSwag (10-Shot) | 48.39 |
MMLU (5-Shot) | 25.05 |
TruthfulQA (0-shot) | 33.45 |
Winogrande (5-shot) | 58.48 |
GSM8k (5-shot) | 1.06 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard31.480
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard48.390
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard25.050
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard33.450
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard58.480
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard1.060