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---
license: other
library_name: transformers
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- mlabonne/orpo-dpo-mix-40k
- Open-Orca/SlimOrca-Dedup
- jondurbin/airoboros-3.2
- microsoft/orca-math-word-problems-200k
- m-a-p/Code-Feedback
- MaziyarPanahi/WizardLM_evol_instruct_V2_196k
model-index:
- name: llama-3-neural-chat-v1-8b
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: 60.84
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
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: 84.13
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
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: 64.69
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
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: 56.34
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
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: 78.22
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
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: 54.81
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b
name: Open LLM Leaderboard
---
# llama-3-neural-chat-v1-8b
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
I fine-tuned llama-3 8B on an approach similar to Intel's neural chat language model. I have slightly modified the data sources so it is stronger in coding, math, and writing. I use both SFT and DPO.
- **Developed by:** Locutusque
- **Model type:** Built with Meta Llama 3
- **Language(s) (NLP):** Many?
- **License:** Llama 3 license https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
## Quants
### EXL2 [@bartowski](https://huggingface.co/bartowski/)
- https://huggingface.co/bartowski/llama-3-neural-chat-v1-8b-exl2
### GGUF [@bartowski](https://huggingface.co/bartowski/)
- https://huggingface.co/bartowski/llama-3-neural-chat-v1-8b-GGUF
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
This model has great performance in writing and coding.
## Training Data
- Open-Orca/SlimOrca-Dedup
- jondurbin/airoboros-3.2
- microsoft/orca-math-word-problems-200k
- m-a-p/Code-Feedback
- MaziyarPanahi/WizardLM_evol_instruct_V2_196k
- mlabonne/orpo-dpo-mix-40k
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
Conversational AI.
## Evaluations
| Tasks |Version| Filter |n-shot| Metric |Value | |Stderr|
|---------------------------------|-------|----------------|-----:|-----------|-----:|---|-----:|
|truthfulqa_mc2 | 2|none | 0|acc |0.5627|± |0.0154|
|gsm8k | 3|strict-match | 5|exact_match|0.5481|± |0.0137|
| | |flexible-extract| 5|exact_match|0.5557|± |0.0137|
|agieval_nous |N/A |none | 0|acc |0.3763|± |0.0093|
| | |none | 0|acc_norm |0.3665|± |0.0093|
| - agieval_aqua_rat | 1|none | 0|acc |0.2087|± |0.0255|
| | |none | 0|acc_norm |0.2047|± |0.0254|
| - agieval_logiqa_en | 1|none | 0|acc |0.3456|± |0.0187|
| | |none | 0|acc_norm |0.3594|± |0.0188|
| - agieval_lsat_ar | 1|none | 0|acc |0.1826|± |0.0255|
| | |none | 0|acc_norm |0.1783|± |0.0253|
| - agieval_lsat_lr | 1|none | 0|acc |0.3549|± |0.0212|
| | |none | 0|acc_norm |0.3451|± |0.0211|
| - agieval_lsat_rc | 1|none | 0|acc |0.5242|± |0.0305|
| | |none | 0|acc_norm |0.5130|± |0.0305|
| - agieval_sat_en | 1|none | 0|acc |0.6650|± |0.0330|
| | |none | 0|acc_norm |0.6505|± |0.0333|
| - agieval_sat_en_without_passage| 1|none | 0|acc |0.4175|± |0.0344|
| | |none | 0|acc_norm |0.3738|± |0.0338|
| - agieval_sat_math | 1|none | 0|acc |0.4227|± |0.0334|
| | |none | 0|acc_norm |0.3682|± |0.0326|
# [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_Locutusque__llama-3-neural-chat-v1-8b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |66.50|
|AI2 Reasoning Challenge (25-Shot)|60.84|
|HellaSwag (10-Shot) |84.13|
|MMLU (5-Shot) |64.69|
|TruthfulQA (0-shot) |56.34|
|Winogrande (5-shot) |78.22|
|GSM8k (5-shot) |54.81|
|