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---
language:
- en
license: apache-2.0
datasets:
- argilla/ultrafeedback-binarized-preferences-cleaned
model-index:
- name: DPO_mistral_v01_7b_ultra_0130_1k
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: 57.17
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
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: 79.16
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
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: 55.85
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
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: 55.62
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
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: 72.85
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
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: 26.31
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_v01_7b_ultra_0130_1k
name: Open LLM Leaderboard
---
Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performanceTesting Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performanceTesting Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performanceTesting Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance Testing Mistral-Instruct model with Orca DPO dataset. Trying to see the effects of DPO for own study. Used Mistral-7B-Instrcut-v0.2 model due to its good performance
# [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_kwchoi__DPO_mistral_v01_7b_ultra_0130_1k)
| Metric |Value|
|---------------------------------|----:|
|Avg. |57.83|
|AI2 Reasoning Challenge (25-Shot)|57.17|
|HellaSwag (10-Shot) |79.16|
|MMLU (5-Shot) |55.85|
|TruthfulQA (0-shot) |55.62|
|Winogrande (5-shot) |72.85|
|GSM8k (5-shot) |26.31|
|