Psyfighter2-Orca2-ties
Psyfighter2-Orca2-ties is a merge of the following models using mergekit:
This is my very first merge I have ever attempted. The motivation behind this merge is to try and create a 13B version of jebcarter/psyonic-cetacean-20B. I don't have a good GPU (GTX 1660 6GB), so although I can merge the model, I cannot actually run it. However, the Open LLM Leaderboard ranks this merge with 63.48 avg point, which is higher than both KoboldAI/LLaMA2-13B-Psyfighter2 and jebcarter/psyonic-cetacean-20B, so I must did something right. The next step is to quantize this merge into GGUF so I can actually run it with KoboldCpp.
🧩 Configuration
models:
- model: KoboldAI/LLaMA2-13B-Psyfighter2
- model: microsoft/Orca-2-13b
parameters:
density: 0.40
weight: [0, 0.3, 0.7, 1]
merge_method: ties
base_model: KoboldAI/LLaMA2-13B-Psyfighter2
parameters:
normalize: true
int8_mask: true
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 63.48 |
| AI2 Reasoning Challenge (25-Shot) | 62.46 |
| HellaSwag (10-Shot) | 81.74 |
| MMLU (5-Shot) | 60.31 |
| TruthfulQA (0-shot) | 55.40 |
| Winogrande (5-shot) | 77.27 |
| GSM8k (5-shot) | 43.67 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard62.460
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard81.740
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard60.310
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard55.400
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.270
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard43.670