Phoenix_DPO_60B / README.md
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Adding Evaluation Results
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---
license: other
tags:
- yi
- moe
license_name: yi-license
license_link: https://huggingface.co./01-ai/Yi-34B-200K/blob/main/LICENSE
model-index:
- name: Phoenix_DPO_60B
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: 71.16
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
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: 85.46
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
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: 77.66
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
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: 63.84
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
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: 84.93
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
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: 69.83
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Phoenix_DPO_60B
name: Open LLM Leaderboard
---
this is a DPO fine-tuned MoE model with 60B parameter.
```
DPO Trainer
TRL supports the DPO Trainer for training language models from preference data, as described in the paper Direct Preference Optimization: Your Language Model is Secretly a Reward Model by Rafailov et al., 2023.
```
GGUF format is ready at [cloudyu/Phoenix_DPO_60B_gguf](https://huggingface.co./cloudyu/Phoenix_DPO_60B_gguf)
# [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_cloudyu__Phoenix_DPO_60B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |75.48|
|AI2 Reasoning Challenge (25-Shot)|71.16|
|HellaSwag (10-Shot) |85.46|
|MMLU (5-Shot) |77.66|
|TruthfulQA (0-shot) |63.84|
|Winogrande (5-shot) |84.93|
|GSM8k (5-shot) |69.83|