Tiger-7b-v0.1
This is a merge of pre-trained language models created using mergekit.
Metrics
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
merge
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
layer_range: [0, 32]
- model: NeuralNovel/Gecko-7B-v0.1-DPO
layer_range: [0, 32]
merge_method: slerp
base_model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
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
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 65.02 |
| AI2 Reasoning Challenge (25-Shot) | 59.98 |
| HellaSwag (10-Shot) | 83.21 |
| MMLU (5-Shot) | 61.42 |
| TruthfulQA (0-shot) | 61.03 |
| Winogrande (5-shot) | 77.66 |
| GSM8k (5-shot) | 46.78 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard59.980
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard83.210
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard61.420
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard61.030
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.660
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard46.780