metadata
language:
- en
license: cc-by-nc-sa-4.0
library_name: transformers
datasets:
- kyujinpy/Open-platypus-Commercial
pipeline_tag: text-generation
model-index:
- name: SOLAR-Platypus-10.7B-v1
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: 61.69
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
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: 84.23
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
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: 60.37
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
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: 51.58
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
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: 82.79
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
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: 11.07
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/SOLAR-Platypus-10.7B-v1
name: Open LLM Leaderboard
SOLAR-Platypus-10.7B-v1
Model Details
Model Developers Kyujin Han (kyujinpy)
Input Models input text only.
Output Models generate text only.
Model Architecture
SOLAR-Platypus-10.7B-v1 is an auto-regressive language model based on the Llama2 architecture.
Base Model
upstage/SOLAR-10.7B-v1.0
Training Dataset
kyujinpy/Open-platypus-Commercial.
Notice
While training, I used LoRA.
The lora_r values is 16.
Q-LoRA config
- LoRA_r: 16
- LoRA_alpha: 16
- LoRA_dropout: 0.05
- LoRA_target_modules: [gate_proj, up_proj, down_proj]
Prompt
- Alpaca template.
Model Benchmark
Open leaderboard
- Follow up as link.
Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
---|---|---|---|---|---|---|---|
SOLAR-Platypus-10.7B-v1 | 58.62 | 61.69 | 84.23 | 60.37 | 51.58 | 82.79 | 11.07 |
SOLAR-Platypus-10.7B-v2 | 55.25 | 59.39 | 83.57 | 59.93 | 43.15 | 81.45 | 4.02 |
upstage/SOLAR-10.7B-v1.0 | 66.04 | 61.95 | 84.60 | 65.48 | 45.04 | 83.66 | 55.50 |
Implementation Code
### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "kyujinpy/SOLAR-Platypus-10.7B-v1"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 58.62 |
AI2 Reasoning Challenge (25-Shot) | 61.69 |
HellaSwag (10-Shot) | 84.23 |
MMLU (5-Shot) | 60.37 |
TruthfulQA (0-shot) | 51.58 |
Winogrande (5-shot) | 82.79 |
GSM8k (5-shot) | 11.07 |