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kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2

sourceHugging Facecc-by-nc-sa-4.0updated 3y agoView on Hugging Face
4likes79downloads
Model Card

Sakura-SOLRCA-Math-Instruct-DPO-v2

<img src='./sakura.png' width=512>

Model Details

Model Developers Kyujin Han (kyujinpy)

Method Using DPO method. With Intel/orca_dpo_pairs and argilla/distilabel-math-preference-dpo.

I shared the merge version kyujinpy/orca_math_dpo.

I shared the information about my model. (training and code) Please see: ⭐Sakura-SOLAR.

Model Benchmark

Open leaderboard

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ModelAverageARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
Sakura-SOLRCA-Math-Instruct-DPO-v274.1771.2588.5266.1372.1683.0363.91
Sakura-SOLRCA-Math-Instruct-DPO-v174.1371.2588.4866.2172.1282.8763.84
Sakura-SOLRCA-Instruct-DPO74.0571.1688.4966.1772.1082.9563.46
Sakura-SOLAR-Instruct-DPO-v274.1470.9088.4166.4871.8683.4363.76
kyujinpy/Sakura-SOLAR-Instruct74.4070.9988.4266.3371.7983.6665.20

Implementation Code

python
### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2"
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

MetricValue
Avg.74.17
AI2 Reasoning Challenge (25-Shot)71.25
HellaSwag (10-Shot)88.52
MMLU (5-Shot)66.13
TruthfulQA (0-shot)72.16
Winogrande (5-shot)83.03
GSM8k (5-shot)63.91