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---
license: other
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
base_model: Columbia-NLP/gemma-2b-zephyr-sft
model-index:
- name: gemma-2b-zephyr-dpo
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: 52.22
name: normalized accuracy
- 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: 73.11
name: normalized accuracy
- 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: 42.55
name: accuracy
- 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: 42.64
- 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: 64.4
name: accuracy
- 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: 19.94
name: accuracy
---
# Model Card for Gemma 2B Zephyr DPO
We trained the [google/gemma-2b](https://huggingface.co/google/gemma-2b) with DPO and data from `argilla/dpo-mix-7k`.
We carefully selected the hyper-parameters to achieve the best DPO performance.
## Model description
- **Model type:** A 2.5B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
- **Language(s) (NLP):** Primarily English
- **License:** Gemma Terms of Use
- **Finetuned from model:** [google/gemma-2b](https://huggingface.co/google/gemma-2b)
## License
This model has the same license as the [original Gemma model collection](https://ai.google.dev/gemma/terms)
## OpenLLM Leaderboard Performance
| Models | Avg. | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8k |
|-----------------------------------------|------|-------|-----------|------|------------|------------|-------|
| google/gemma-2b | 46.37| 48.38 | 71.77 | 41.77| 33.08 | 66.77 | 16.91 |
| google/gemma-2b-it | 42.75| 43.94 | 62.70 | 37.65| 45.82 | 60.93 | 5.46 |
| wandb/gemma-2b-zephyr-sft | 47.18| 49.74 | 72.38 | 41.37| 34.42 | **66.93** | 18.27 |
| wandb/gemma-2b-zephyr-dpo | 46.92| 49.66 | 72.23 | 41.13| 34.47 | 66.54 | 17.51 |
| Columbia-NLP/gemma-2b-zephyr-sft | 48.75| 51.80 | 72.63 | 42.20| 41.96 | 63.85 | **20.09** |
| **Columbia-NLP/gemma-2b-zephyr-dpo** | **49.14**| **52.22** | **73.11** | **42.55**| **42.64** | 64.40 | 19.94 |
## MT-Bench
We evaluate our model with `GPT-4-0125-preview` as the judge.
| Model | Total | Coding | Extraction | Humanities | Math | Reasoning | Roleplay | STEM | Writing |
|------------------------------------------|-------|--------|------------|------------|------|-----------|----------|------|---------|
| google/gemma-2b-it | 4.71 | 2.95 | **4.35** | 6.15 | 2.90 | 3.50 | 5.60 | **5.50** | **6.70** |
| wandb/gemma-2b-zephyr-sft | 4.03 | 3.10 | 3.15 | 5.00 | 2.70 | 2.65 | 5.10 | 4.80 | 5.75 |
| wandb/gemma-2b-zephyr-dpo | 4.06 | 2.80 | 2.90 | 5.55 | 2.65 | 2.70 | 5.20 | 4.80 | 5.85 |
| anakin87_gemma-2b-orpo | 4.14 | 3.00 | 3.70 | 6.30 | 2.70 | 2.35 | 5.68 | 4.75 | 4.75 |
| Columbia-NLP/gemma-2b-zephyr-sft | 4.34 | 3.10 | 3.70 | 6.25 | 2.65 | 2.70 | 5.55 | 5.25 | 5.50 |
| **Columbia-NLP/gemma-2b-zephyr-dpo** | **4.75** | **3.50** | 4.05 | **6.75** | **3.30** | **3.70** | **5.85** | 5.40 | 5.53 | |