Model Card for xDAN-SlimOrca
Slerp merge of Silicon-Maid-7B, piano-medley-7b, xDAN-L1-Chat-RL-v1, and mistral-7b-slimorcaboros.
.yaml file for mergekit
slices:
- sources:
- model: Azazelle/Silicon-Medley
layer_range: [0, 32]
- model: Azazelle/xDAN-SlimOrca
layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
t:
- filter: self_attn
value: [0.19, 0.59, 0.43, 0.76, 1]
- filter: mlp
value: [0.81, 0.41, 0.57, 0.24, 0]
- value: 0.5 # fallback for rest of tensors
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 69.70 |
| AI2 Reasoning Challenge (25-Shot) | 67.15 |
| HellaSwag (10-Shot) | 86.01 |
| MMLU (5-Shot) | 64.75 |
| TruthfulQA (0-shot) | 60.88 |
| Winogrande (5-shot) | 78.61 |
| GSM8k (5-shot) | 60.80 |
- Downloads last month
- 1,324
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard67.150
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.010
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.750
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard60.880
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard78.610
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard60.800