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---
license: apache-2.0
library_name: transformers
datasets:
- Intel/orca_dpo_pairs
base_model: NeuralNovel/Gecko-7B-v0.1
inference: false
model-index:
- name: Gecko-7B-v0.1-DPO
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: 56.74
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
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: 82.38
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
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: 60.42
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
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: 57.42
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
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: 77.35
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
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: 45.03
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Gecko-7B-v0.1-DPO
name: Open LLM Leaderboard
---
# NeuralNovel/Gecko-7B-v0.1-DPO
Designed to generate instructive and narrative text, with a focus on mathematics & numeracy.
Full-parameter fine-tune (FFT) of Mistral-7B-Instruct-v0.2, with apache-2.0 license.
You may download and use this model for research, training and commercial purposes.
This model is suitable for commercial deployment.
[Join our Discord!](https://discord.gg/rJXGjmxqzS)
<a href='https://ko-fi.com/S6S2UH2TC' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
### Data-set
The model was finetuned using the orca_dpo_pairs dataset
### Summary
Fine-tuned with the intention of following all prompt directions, making it more suitable for math questions and problem solving.
#### Out-of-Scope Use
The model may not perform well in scenarios unrelated to instructive and narrative text generation. Misuse or applications outside its designed scope may result in suboptimal outcomes.
### Bias, Risks, and Limitations
This model may not work as intended. As such all users are encouraged to use this model with caution and respect.
This model is for testing and research purposes only, it has reduced levels of alignment and as a result may produce NSFW or harmful content.
The user is responsible for their output and must use this model responsibly.
### Hardware and Training
Trained on a single 80GB A100 for 2 hours trained using Axolotl
Thank you to **h2m** for the generous funding.
# [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_NeuralNovel__Gecko-7B-v0.1-DPO)
| Metric |Value|
|---------------------------------|----:|
|Avg. |63.22|
|AI2 Reasoning Challenge (25-Shot)|56.74|
|HellaSwag (10-Shot) |82.38|
|MMLU (5-Shot) |60.42|
|TruthfulQA (0-shot) |57.42|
|Winogrande (5-shot) |77.35|
|GSM8k (5-shot) |45.03|
|