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