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---
language:
- en
license: cc-by-2.0
tags:
- finance
- legal
- biology
- art
model-index:
- name: SatoshiNv5
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 60.49
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 82.94
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 63.42
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 41.8
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 78.69
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 34.72
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chrischain/SatoshiNv5
name: Open LLM Leaderboard
---
Behold, one of the first fine-tunes of Mistral's 7B 0.2 Base model. SatoshiN is trained on 4 epochs 2e-4 learning rate (cosine) of a diverse custom data-set, combined with a polishing round of that same data-set at a 1e-4 linear learning rate.
It's a nice assistant that isn't afraid to ask questions, and gather additional information before providing a response to user prompts.
SatoshiN | Base-Model
Wikitext Perplexity: 6.27 | 5.4
**Similar to SOTA, this model runs a bit hot, try using lower temperatures below .5 if experiencing any nonsense)
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_chrischain__SatoshiNv5)
| Metric |Value|
|---------------------------------|----:|
|Avg. |60.34|
|AI2 Reasoning Challenge (25-Shot)|60.49|
|HellaSwag (10-Shot) |82.94|
|MMLU (5-Shot) |63.42|
|TruthfulQA (0-shot) |41.80|
|Winogrande (5-shot) |78.69|
|GSM8k (5-shot) |34.72|
|