---
language:
- en
license: llama3
library_name: transformers
tags:
- orpo
- llama 3
- rlhf
- sft
base_model:
- meta-llama/Meta-Llama-3-70B
datasets:
- mlabonne/orpo-dpo-mix-40k
model-index:
- name: Llama-3-70B-Orpo-v0.1
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 20.49
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 24.09
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 13.52
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 1.01
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 16.28
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 32.14
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dfurman/Llama-3-70B-Orpo-v0.1
name: Open LLM Leaderboard
---
# dfurman/Llama-3-70B-Orpo-v0.1
This is an ORPO fine-tune of [meta-llama/Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) on 2k samples of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k).
It's a successful fine-tune that follows the ChatML template!
## 🔎 Application
This model uses a context window of 8k. It was trained with the ChatML template.
## 🏆 Evaluation
### Open LLM Leaderboard
| Model ID | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: | --------: | --------: |
| [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Meta-Llama-3-70B-Instruct) | 77.88 | 71.42 | 85.69 | 80.06 | 61.81 | 82.87 | 85.44 |
| [**dfurman/Llama-3-70B-Orpo-v0.1**](https://huggingface.co/dfurman/Llama-3-70B-Orpo-v0.1) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_dfurman__Llama-3-70B-Orpo-v0.1) | **74.67** | **68.69** | **88.01** | **79.39** | **49.62** | **85.48** | **76.8** |
| [meta-llama/Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) [📄](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Meta-Llama-3-70B) | 73.96 | 68.77 | 87.98 | 79.23 | 45.56 | 85.32 | 76.88 |
## 📈 Training curves
You can find the experiment on W&B at [this address](https://wandb.ai/dryanfurman/huggingface/runs/ojsbud95/workspace?nw=nwuserdryanfurman).
## 💻 Usage
Setup
```python
!pip install -qU transformers accelerate bitsandbytes
from transformers import AutoTokenizer, BitsAndBytesConfig
import transformers
import torch
if torch.cuda.get_device_capability()[0] >= 8:
!pip install -qqq flash-attn
attn_implementation = "flash_attention_2"
torch_dtype = torch.bfloat16
else:
attn_implementation = "eager"
torch_dtype = torch.float16
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch_dtype,
bnb_4bit_use_double_quant=True,
)
model = "dfurman/Llama-3-70B-Orpo-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={
"torch_dtype": torch_dtype,
"quantization_config": bnb_config,
"device_map": "auto",
"attn_implementation": attn_implementation,
}
)
```
### Run
```python
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Tell me a recipe for a spicy margarita."},
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
print("***Prompt:\n", prompt)
outputs = pipeline(prompt, max_new_tokens=1000, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print("***Generation:\n", outputs[0]["generated_text"][len(prompt):])
```
Output
```
"""
"""
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_dfurman__Llama-3-70B-Orpo-v0.1)
| Metric |Value|
|-------------------|----:|
|Avg. |17.92|
|IFEval (0-Shot) |20.49|
|BBH (3-Shot) |24.09|
|MATH Lvl 5 (4-Shot)|13.52|
|GPQA (0-shot) | 1.01|
|MuSR (0-shot) |16.28|
|MMLU-PRO (5-shot) |32.14|