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---
language:
- en
license: other
tags:
- chat
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
model-index:
- name: Smaug-Qwen2-72B-Instruct
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: 78.25
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
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: 56.27
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
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: 35.35
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
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: 14.88
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
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: 15.18
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
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: 46.56
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/Smaug-Qwen2-72B-Instruct
name: Open LLM Leaderboard
---
# Smaug-Qwen2-72B-Instruct
# Introduction
We introduce the latest in the Smaug series - a finetune of [Qwen2-72B-Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct)
Compared to Qwen2-72B-Instruct, Smaug has better BBH, LiveCodeBench, and Arena-Hard scores (see evaluation results below).
## How to use
The prompt format is unchanged from Qwen2-72B-Instruct.
### Use with transformers
See the snippet below for usage with Transformers:
```python
import transformers
import torch
model_id = "abacusai/Smaug-Qwen2-72B-Instruct"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
{"role": "user", "content": "Who are you?"},
]
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])
```
# Evaluation Results
## Big-Bench Hard (BBH)
Note: These results are with corrected parsing for BBH from Eleuther's [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness). See [this PR](https://github.com/EleutherAI/lm-evaluation-harness/pull/2013).
#### Overall:
| Model | Groups | Version | Filter | n-shot | Metric | Value | | Stderr |
|----------------------------|--------|---------|------------|--------|-------------|--------|---|--------|
| **Smaug-Qwen2-72B-Instruct** | bbh | N/A | get-answer | 3 | exact_match | 0.8241 | ± | 0.0042 |
| Qwen2-72B-Instruct | bbh | N/A | get-answer | 3 | exact_match | 0.8036 | ± | 0.0044 |
#### Breakdown:
Smaug-Qwen2-72B-Instruct:
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr |
|-----------------------------------------------------------|---------|------------|--------|-------------|--------|--------|
| bbh | N/A | get-answer | 3 | exact_match | 0.8241 | 0.0042 |
| - bbh_cot_fewshot_boolean_expressions | 2 | get-answer | 3 | exact_match | 0.9640 | 0.0118 |
| - bbh_cot_fewshot_causal_judgement | 2 | get-answer | 3 | exact_match | 0.6578 | 0.0348 |
| - bbh_cot_fewshot_date_understanding | 2 | get-answer | 3 | exact_match | 0.8360 | 0.0235 |
| - bbh_cot_fewshot_disambiguation_qa | 2 | get-answer | 3 | exact_match | 0.8280 | 0.0239 |
| - bbh_cot_fewshot_dyck_languages | 2 | get-answer | 3 | exact_match | 0.3360 | 0.0299 |
| - bbh_cot_fewshot_formal_fallacies | 2 | get-answer | 3 | exact_match | 0.7120 | 0.0287 |
| - bbh_cot_fewshot_geometric_shapes | 2 | get-answer | 3 | exact_match | 0.5320 | 0.0316 |
| - bbh_cot_fewshot_hyperbaton | 2 | get-answer | 3 | exact_match | 0.9880 | 0.0069 |
| - bbh_cot_fewshot_logical_deduction_five_objects | 2 | get-answer | 3 | exact_match | 0.7680 | 0.0268 |
| - bbh_cot_fewshot_logical_deduction_seven_objects | 2 | get-answer | 3 | exact_match | 0.5360 | 0.0316 |
| - bbh_cot_fewshot_logical_deduction_three_objects | 2 | get-answer | 3 | exact_match | 0.9720 | 0.0105 |
| - bbh_cot_fewshot_movie_recommendation | 2 | get-answer | 3 | exact_match | 0.8000 | 0.0253 |
| - bbh_cot_fewshot_multistep_arithmetic_two | 2 | get-answer | 3 | exact_match | 0.9720 | 0.0105 |
| - bbh_cot_fewshot_navigate | 2 | get-answer | 3 | exact_match | 0.9640 | 0.0118 |
| - bbh_cot_fewshot_object_counting | 2 | get-answer | 3 | exact_match | 0.9200 | 0.0172 |
| - bbh_cot_fewshot_penguins_in_a_table | 2 | get-answer | 3 | exact_match | 0.8493 | 0.0297 |
| - bbh_cot_fewshot_reasoning_about_colored_objects | 2 | get-answer | 3 | exact_match | 0.7560 | 0.0272 |
| - bbh_cot_fewshot_ruin_names | 2 | get-answer | 3 | exact_match | 0.8520 | 0.0225 |
| - bbh_cot_fewshot_salient_translation_error_detection | 2 | get-answer | 3 | exact_match | 0.5920 | 0.0311 |
| - bbh_cot_fewshot_snarks | 2 | get-answer | 3 | exact_match | 0.9101 | 0.0215 |
| - bbh_cot_fewshot_sports_understanding | 2 | get-answer | 3 | exact_match | 0.9440 | 0.0146 |
| - bbh_cot_fewshot_temporal_sequences | 2 | get-answer | 3 | exact_match | 1.0000 | 0.0000 |
| - bbh_cot_fewshot_tracking_shuffled_objects_five_objects | 2 | get-answer | 3 | exact_match | 0.9800 | 0.0089 |
| - bbh_cot_fewshot_tracking_shuffled_objects_seven_objects | 2 | get-answer | 3 | exact_match | 0.9560 | 0.0130 |
| - bbh_cot_fewshot_tracking_shuffled_objects_three_objects | 2 | get-answer | 3 | exact_match | 0.9640 | 0.0118 |
| - bbh_cot_fewshot_web_of_lies | 2 | get-answer | 3 | exact_match | 1.0000 | 0.0000 |
| - bbh_cot_fewshot_word_sorting | 2 | get-answer | 3 | exact_match | 0.6560 | 0.0301 |
Qwen2-72B-Instruct:
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr |
|-----------------------------------------------------------|---------|------------|--------|-------------|--------|--------|
| bbh | N/A | get-answer | 3 | exact_match | 0.8036 | 0.0044 |
| - bbh_cot_fewshot_boolean_expressions | 2 | get-answer | 3 | exact_match | 0.9640 | 0.0118 |
| - bbh_cot_fewshot_causal_judgement | 2 | get-answer | 3 | exact_match | 0.6684 | 0.0345 |
| - bbh_cot_fewshot_date_understanding | 2 | get-answer | 3 | exact_match | 0.8000 | 0.0253 |
| - bbh_cot_fewshot_disambiguation_qa | 2 | get-answer | 3 | exact_match | 0.8360 | 0.0235 |
| - bbh_cot_fewshot_dyck_languages | 2 | get-answer | 3 | exact_match | 0.3040 | 0.0292 |
| - bbh_cot_fewshot_formal_fallacies | 2 | get-answer | 3 | exact_match | 0.7480 | 0.0275 |
| - bbh_cot_fewshot_geometric_shapes | 2 | get-answer | 3 | exact_match | 0.4960 | 0.0317 |
| - bbh_cot_fewshot_hyperbaton | 2 | get-answer | 3 | exact_match | 0.9440 | 0.0146 |
| - bbh_cot_fewshot_logical_deduction_five_objects | 2 | get-answer | 3 | exact_match | 0.6800 | 0.0296 |
| - bbh_cot_fewshot_logical_deduction_seven_objects | 2 | get-answer | 3 | exact_match | 0.4720 | 0.0316 |
| - bbh_cot_fewshot_logical_deduction_three_objects | 2 | get-answer | 3 | exact_match | 0.9200 | 0.0172 |
| - bbh_cot_fewshot_movie_recommendation | 2 | get-answer | 3 | exact_match | 0.7800 | 0.0263 |
| - bbh_cot_fewshot_multistep_arithmetic_two | 2 | get-answer | 3 | exact_match | 0.9760 | 0.0097 |
| - bbh_cot_fewshot_navigate | 2 | get-answer | 3 | exact_match | 0.9520 | 0.0135 |
| - bbh_cot_fewshot_object_counting | 2 | get-answer | 3 | exact_match | 0.9480 | 0.0141 |
| - bbh_cot_fewshot_penguins_in_a_table | 2 | get-answer | 3 | exact_match | 0.5753 | 0.0410 |
| - bbh_cot_fewshot_reasoning_about_colored_objects | 2 | get-answer | 3 | exact_match | 0.8120 | 0.0248 |
| - bbh_cot_fewshot_ruin_names | 2 | get-answer | 3 | exact_match | 0.8760 | 0.0209 |
| - bbh_cot_fewshot_salient_translation_error_detection | 2 | get-answer | 3 | exact_match | 0.5880 | 0.0312 |
| - bbh_cot_fewshot_snarks | 2 | get-answer | 3 | exact_match | 0.8764 | 0.0247 |
| - bbh_cot_fewshot_sports_understanding | 2 | get-answer | 3 | exact_match | 0.9080 | 0.0183 |
| - bbh_cot_fewshot_temporal_sequences | 2 | get-answer | 3 | exact_match | 0.9960 | 0.0040 |
| - bbh_cot_fewshot_tracking_shuffled_objects_five_objects | 2 | get-answer | 3 | exact_match | 0.9160 | 0.0176 |
| - bbh_cot_fewshot_tracking_shuffled_objects_seven_objects | 2 | get-answer | 3 | exact_match | 0.9400 | 0.0151 |
| - bbh_cot_fewshot_tracking_shuffled_objects_three_objects | 2 | get-answer | 3 | exact_match | 0.9440 | 0.0146 |
| - bbh_cot_fewshot_web_of_lies | 2 | get-answer | 3 | exact_match | 1.0000 | 0.0000 |
| - bbh_cot_fewshot_word_sorting | 2 | get-answer | 3 | exact_match | 0.6680 | 0.0298 |
## LiveCodeBench
| Model | Pass@1 | Easy Pass@1 | Medium Pass@1 | Hard Pass@1 |
|--------------------------|--------|-------------|---------------|-------------|
| **Smaug-Qwen2-72B-Instruct** | 0.3357 | 0.7286 | 0.1633 | 0.0000 |
| Qwen2-72B-Instruct | 0.3139 | 0.6810 | 0.1531 | 0.0000 |
## Arena-Hard
Score vs selected others (sourced from: (https://lmsys.org/blog/2024-04-19-arena-hard/#full-leaderboard-with-gpt-4-turbo-as-judge)). GPT-4o and Gemini-1.5-pro-latest were missing from the original blob post, and we produced those numbers from a local run using the same methodology.
| Model | Score | 95% Confidence Interval | Average Tokens |
| :---- | ---------: | ----------: | ------: |
| GPT-4-Turbo-2024-04-09 | 82.6 | (-1.8, 1.6) | 662 |
| GPT-4o | 78.3 | (-2.4, 2.1) | 685 |
| Gemini-1.5-pro-latest | 72.1 | (-2.3, 2.2) | 630 |
| Claude-3-Opus-20240229 | 60.4 | (-3.3, 2.4) | 541 |
| Smaug-Llama-3-70B-Instruct | 56.7 | (-2.2, 2.6) | 661 |
| GPT-4-0314 | 50.0 | (-0.0, 0.0) | 423 |
| **Smaug-Qwen2-72B-Instruct** | 48.0 | (-1.8, 2.1) | 628 |
| Claude-3-Sonnet-20240229 | 46.8 | (-2.1, 2.2) | 552 |
| Qwen2-72B-Instruct | 43.5 | (-2.6, 2.7) | 531 |
| Llama-3-70B-Instruct | 41.1 | (-2.5, 2.4) | 583 |
| GPT-4-0613 | 37.9 | (-2.2, 2.0) | 354 |
| Mistral-Large-2402 | 37.7 | (-1.9, 2.6) | 400 |
| Mixtral-8x22B-Instruct-v0.1 | 36.4 | (-2.7, 2.9) | 430 |
| Qwen1.5-72B-Chat | 36.1 | (-2.5, 2.2) | 474 |
| Command-R-Plus | 33.1 | (-2.1, 2.2) | 541 |
| Mistral-Medium | 31.9 | (-2.3, 2.4) | 485 |
| GPT-3.5-Turbo-0613 | 24.8 | (-1.6, 2.0) | 401 |
## MT-Bench
First turn
| Model | Turn | Score |
|--------------------------|------|---------|
| Qwen2-72B-Instruct | 1 | 9.18125 |
| Smaug-Qwen2-72B-Instruct | 1 | 9.05625 |
Second turn
| Model | Turn | Score |
|--------------------------|------|---------|
| Qwen2-72B-Instruct | 2 | 8.74684 |
| Smaug-Qwen2-72B-Instruct | 2 | 8.67500 |
Average
| Model | Score |
|--------------------------|---------|
| Qwen2-72B-Instruct | 8.96541 |
| Smaug-Qwen2-72B-Instruct | 8.86563 |
# [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_abacusai__Smaug-Qwen2-72B-Instruct)
| Metric |Value|
|-------------------|----:|
|Avg. |41.08|
|IFEval (0-Shot) |78.25|
|BBH (3-Shot) |56.27|
|MATH Lvl 5 (4-Shot)|35.35|
|GPQA (0-shot) |14.88|
|MuSR (0-shot) |15.18|
|MMLU-PRO (5-shot) |46.56|
|