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--- |
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license: agpl-3.0 |
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tags: |
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- merge |
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- wizardlm |
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- mique |
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pipeline_tag: text-generation |
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model-index: |
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- name: WizardLM-Math-70B-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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 67.06 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 86.01 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 69.14 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 57.07 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 81.77 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-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: GSM8k (5-shot) |
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type: gsm8k |
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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: 64.44 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/WizardLM-Math-70B-v0.1 |
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name: Open LLM Leaderboard |
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--- |
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## Examples |
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There are three killers in a room. Someone enters the room and kills one of them. Nobody leaves the room. How many killers are left in the room? Explain your reasoning step by step. |
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``` |
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Step 1: Identify the initial situation |
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There are three killers in a room, which we can label as A, B, and C. |
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Step 2: Describe the event |
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Someone (let's call this person D) enters the room and kills one of the killers. For the sake of simplicity, let's say that Killer A is killed. |
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Step 3: Analyze the new situation |
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After the event, there are now two killers left in the room: B and C. The person who entered the room, D, is also still present. However, since D did not leave the room after killing A, it means that D is also a killer. Therefore, there are actually three killers in the room: B, C, and D. |
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Final Answer: After the event, there are three killers left in the room: B, C, and D. |
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``` |
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Mark is faster than Mary , Mary is faster than Joe. Is Joe faster than Mark? Let's think step by step |
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``` |
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Step 1: Understand the given information |
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We know that Mark is faster than Mary, and Mary is faster than Joe. This means that Mark is the fastest among the three, followed by Mary, and then Joe. |
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Step 2: Analyze the question |
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The question asks if Joe is faster than Mark. Based on the given information, we can conclude that Joe is not faster than Mark. In fact, Mark is faster than Joe. |
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Final Answer: No, Joe is not faster than Mark. |
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``` |
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If I lay 2 wet shirts out in the sun flat on the ground to dry and it takes 5 hours until they are dry, how long would it take to dry 4 shirts of the same type that way simultanously? |
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``` |
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The time taken for a shirt to dry depends on several factors such as the material of the shirt, the humidity, temperature, wind speed, etc. However, if we assume that all four shirts have similar properties and the weather conditions remain constant, then you can expect the drying time to be proportional to the number of shirts. |
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In other words, if two shirts take 5 hours to dry, then four shirts will likely take twice as long, or 10 hours. This is because there is more fabric to dry, which means it will absorb more water from the air, thus taking longer to reach equilibrium with the surrounding environment. |
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However, this is just an estimate, and the actual drying time may vary depending on the specific circumstances. |
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``` |
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Wrong, it takes the same amount of time! |
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explain step by step 25-4*2+3=? |
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``` |
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Step 1: Perform the multiplication operation first. |
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25 - 4 * 2 + 3 = 25 - 8 + 3 |
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Step 2: Now, perform the subtraction and addition operations from left to right. |
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25 - 8 + 3 = 17 + 3 |
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Step 3: Finally, perform the remaining addition operation. |
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17 + 3 = 20 |
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So, 25-4*2+3 equals 20. |
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``` |
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## Eval |
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### WizardLM/WizardLM-70B-V1.0 vs. MaziyarPanahi/WizardLM-Math-70B-v0.1 |
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 |
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### Leaderboard |
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|
|
```python |
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{ |
|
"all": { |
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"acc": 0.6914116069568377, |
|
"acc_stderr": 0.03063431437342948, |
|
"acc_norm": 0.6938613221179539, |
|
"acc_norm_stderr": 0.031238741076549784, |
|
"mc1": 0.40269277845777235, |
|
"mc1_stderr": 0.01716883093518722, |
|
"mc2": 0.5707095526544473, |
|
"mc2_stderr": 0.01525040450448649 |
|
}, |
|
"harness|arc:challenge|25": { |
|
"acc": 0.6322525597269625, |
|
"acc_stderr": 0.014090995618168482, |
|
"acc_norm": 0.6706484641638225, |
|
"acc_norm_stderr": 0.013734057652635474 |
|
}, |
|
"harness|hellaswag|10": { |
|
"acc": 0.6746664011153157, |
|
"acc_stderr": 0.0046754187743142306, |
|
"acc_norm": 0.8600876319458275, |
|
"acc_norm_stderr": 0.0034618713240671846 |
|
}, |
|
"harness|hendrycksTest-abstract_algebra|5": { |
|
"acc": 0.34, |
|
"acc_stderr": 0.04760952285695236, |
|
"acc_norm": 0.34, |
|
"acc_norm_stderr": 0.04760952285695236 |
|
}, |
|
"harness|hendrycksTest-anatomy|5": { |
|
"acc": 0.6518518518518519, |
|
"acc_stderr": 0.041153246103369526, |
|
"acc_norm": 0.6518518518518519, |
|
"acc_norm_stderr": 0.041153246103369526 |
|
}, |
|
"harness|hendrycksTest-astronomy|5": { |
|
"acc": 0.7894736842105263, |
|
"acc_stderr": 0.03317672787533157, |
|
"acc_norm": 0.7894736842105263, |
|
"acc_norm_stderr": 0.03317672787533157 |
|
}, |
|
"harness|hendrycksTest-business_ethics|5": { |
|
"acc": 0.73, |
|
"acc_stderr": 0.04461960433384741, |
|
"acc_norm": 0.73, |
|
"acc_norm_stderr": 0.04461960433384741 |
|
}, |
|
"harness|hendrycksTest-clinical_knowledge|5": { |
|
"acc": 0.7283018867924528, |
|
"acc_stderr": 0.027377706624670713, |
|
"acc_norm": 0.7283018867924528, |
|
"acc_norm_stderr": 0.027377706624670713 |
|
}, |
|
"harness|hendrycksTest-college_biology|5": { |
|
"acc": 0.8194444444444444, |
|
"acc_stderr": 0.032166008088022675, |
|
"acc_norm": 0.8194444444444444, |
|
"acc_norm_stderr": 0.032166008088022675 |
|
}, |
|
"harness|hendrycksTest-college_chemistry|5": { |
|
"acc": 0.5, |
|
"acc_stderr": 0.050251890762960605, |
|
"acc_norm": 0.5, |
|
"acc_norm_stderr": 0.050251890762960605 |
|
}, |
|
"harness|hendrycksTest-college_computer_science|5": { |
|
"acc": 0.57, |
|
"acc_stderr": 0.049756985195624284, |
|
"acc_norm": 0.57, |
|
"acc_norm_stderr": 0.049756985195624284 |
|
}, |
|
"harness|hendrycksTest-college_mathematics|5": { |
|
"acc": 0.37, |
|
"acc_stderr": 0.04852365870939099, |
|
"acc_norm": 0.37, |
|
"acc_norm_stderr": 0.04852365870939099 |
|
}, |
|
"harness|hendrycksTest-college_medicine|5": { |
|
"acc": 0.6878612716763006, |
|
"acc_stderr": 0.035331333893236574, |
|
"acc_norm": 0.6878612716763006, |
|
"acc_norm_stderr": 0.035331333893236574 |
|
}, |
|
"harness|hendrycksTest-college_physics|5": { |
|
"acc": 0.35294117647058826, |
|
"acc_stderr": 0.047551296160629475, |
|
"acc_norm": 0.35294117647058826, |
|
"acc_norm_stderr": 0.047551296160629475 |
|
}, |
|
"harness|hendrycksTest-computer_security|5": { |
|
"acc": 0.7, |
|
"acc_stderr": 0.046056618647183814, |
|
"acc_norm": 0.7, |
|
"acc_norm_stderr": 0.046056618647183814 |
|
}, |
|
"harness|hendrycksTest-conceptual_physics|5": { |
|
"acc": 0.676595744680851, |
|
"acc_stderr": 0.030579442773610337, |
|
"acc_norm": 0.676595744680851, |
|
"acc_norm_stderr": 0.030579442773610337 |
|
}, |
|
"harness|hendrycksTest-econometrics|5": { |
|
"acc": 0.40350877192982454, |
|
"acc_stderr": 0.046151869625837026, |
|
"acc_norm": 0.40350877192982454, |
|
"acc_norm_stderr": 0.046151869625837026 |
|
}, |
|
"harness|hendrycksTest-electrical_engineering|5": { |
|
"acc": 0.5793103448275863, |
|
"acc_stderr": 0.04113914981189261, |
|
"acc_norm": 0.5793103448275863, |
|
"acc_norm_stderr": 0.04113914981189261 |
|
}, |
|
"harness|hendrycksTest-elementary_mathematics|5": { |
|
"acc": 0.4497354497354497, |
|
"acc_stderr": 0.02562085704293665, |
|
"acc_norm": 0.4497354497354497, |
|
"acc_norm_stderr": 0.02562085704293665 |
|
}, |
|
"harness|hendrycksTest-formal_logic|5": { |
|
"acc": 0.46825396825396826, |
|
"acc_stderr": 0.04463112720677172, |
|
"acc_norm": 0.46825396825396826, |
|
"acc_norm_stderr": 0.04463112720677172 |
|
}, |
|
"harness|hendrycksTest-global_facts|5": { |
|
"acc": 0.46, |
|
"acc_stderr": 0.05009082659620332, |
|
"acc_norm": 0.46, |
|
"acc_norm_stderr": 0.05009082659620332 |
|
}, |
|
"harness|hendrycksTest-high_school_biology|5": { |
|
"acc": 0.8129032258064516, |
|
"acc_stderr": 0.022185710092252252, |
|
"acc_norm": 0.8129032258064516, |
|
"acc_norm_stderr": 0.022185710092252252 |
|
}, |
|
"harness|hendrycksTest-high_school_chemistry|5": { |
|
"acc": 0.5369458128078818, |
|
"acc_stderr": 0.035083705204426656, |
|
"acc_norm": 0.5369458128078818, |
|
"acc_norm_stderr": 0.035083705204426656 |
|
}, |
|
"harness|hendrycksTest-high_school_computer_science|5": { |
|
"acc": 0.79, |
|
"acc_stderr": 0.040936018074033256, |
|
"acc_norm": 0.79, |
|
"acc_norm_stderr": 0.040936018074033256 |
|
}, |
|
"harness|hendrycksTest-high_school_european_history|5": { |
|
"acc": 0.8363636363636363, |
|
"acc_stderr": 0.02888787239548795, |
|
"acc_norm": 0.8363636363636363, |
|
"acc_norm_stderr": 0.02888787239548795 |
|
}, |
|
"harness|hendrycksTest-high_school_geography|5": { |
|
"acc": 0.8686868686868687, |
|
"acc_stderr": 0.024063156416822502, |
|
"acc_norm": 0.8686868686868687, |
|
"acc_norm_stderr": 0.024063156416822502 |
|
}, |
|
"harness|hendrycksTest-high_school_government_and_politics|5": { |
|
"acc": 0.927461139896373, |
|
"acc_stderr": 0.018718998520678178, |
|
"acc_norm": 0.927461139896373, |
|
"acc_norm_stderr": 0.018718998520678178 |
|
}, |
|
"harness|hendrycksTest-high_school_macroeconomics|5": { |
|
"acc": 0.7025641025641025, |
|
"acc_stderr": 0.023177408131465953, |
|
"acc_norm": 0.7025641025641025, |
|
"acc_norm_stderr": 0.023177408131465953 |
|
}, |
|
"harness|hendrycksTest-high_school_mathematics|5": { |
|
"acc": 0.34814814814814815, |
|
"acc_stderr": 0.02904560029061626, |
|
"acc_norm": 0.34814814814814815, |
|
"acc_norm_stderr": 0.02904560029061626 |
|
}, |
|
"harness|hendrycksTest-high_school_microeconomics|5": { |
|
"acc": 0.7941176470588235, |
|
"acc_stderr": 0.02626502460827588, |
|
"acc_norm": 0.7941176470588235, |
|
"acc_norm_stderr": 0.02626502460827588 |
|
}, |
|
"harness|hendrycksTest-high_school_physics|5": { |
|
"acc": 0.4503311258278146, |
|
"acc_stderr": 0.04062290018683776, |
|
"acc_norm": 0.4503311258278146, |
|
"acc_norm_stderr": 0.04062290018683776 |
|
}, |
|
"harness|hendrycksTest-high_school_psychology|5": { |
|
"acc": 0.8954128440366973, |
|
"acc_stderr": 0.013120530245265593, |
|
"acc_norm": 0.8954128440366973, |
|
"acc_norm_stderr": 0.013120530245265593 |
|
}, |
|
"harness|hendrycksTest-high_school_statistics|5": { |
|
"acc": 0.5787037037037037, |
|
"acc_stderr": 0.03367462138896078, |
|
"acc_norm": 0.5787037037037037, |
|
"acc_norm_stderr": 0.03367462138896078 |
|
}, |
|
"harness|hendrycksTest-high_school_us_history|5": { |
|
"acc": 0.9166666666666666, |
|
"acc_stderr": 0.019398452135813905, |
|
"acc_norm": 0.9166666666666666, |
|
"acc_norm_stderr": 0.019398452135813905 |
|
}, |
|
"harness|hendrycksTest-high_school_world_history|5": { |
|
"acc": 0.8860759493670886, |
|
"acc_stderr": 0.020681745135884565, |
|
"acc_norm": 0.8860759493670886, |
|
"acc_norm_stderr": 0.020681745135884565 |
|
}, |
|
"harness|hendrycksTest-human_aging|5": { |
|
"acc": 0.757847533632287, |
|
"acc_stderr": 0.028751392398694755, |
|
"acc_norm": 0.757847533632287, |
|
"acc_norm_stderr": 0.028751392398694755 |
|
}, |
|
"harness|hendrycksTest-human_sexuality|5": { |
|
"acc": 0.8702290076335878, |
|
"acc_stderr": 0.029473649496907065, |
|
"acc_norm": 0.8702290076335878, |
|
"acc_norm_stderr": 0.029473649496907065 |
|
}, |
|
"harness|hendrycksTest-international_law|5": { |
|
"acc": 0.8181818181818182, |
|
"acc_stderr": 0.03520893951097655, |
|
"acc_norm": 0.8181818181818182, |
|
"acc_norm_stderr": 0.03520893951097655 |
|
}, |
|
"harness|hendrycksTest-jurisprudence|5": { |
|
"acc": 0.8148148148148148, |
|
"acc_stderr": 0.03755265865037181, |
|
"acc_norm": 0.8148148148148148, |
|
"acc_norm_stderr": 0.03755265865037181 |
|
}, |
|
"harness|hendrycksTest-logical_fallacies|5": { |
|
"acc": 0.7791411042944786, |
|
"acc_stderr": 0.03259177392742179, |
|
"acc_norm": 0.7791411042944786, |
|
"acc_norm_stderr": 0.03259177392742179 |
|
}, |
|
"harness|hendrycksTest-machine_learning|5": { |
|
"acc": 0.48214285714285715, |
|
"acc_stderr": 0.047427623612430116, |
|
"acc_norm": 0.48214285714285715, |
|
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|
}, |
|
"harness|hendrycksTest-management|5": { |
|
"acc": 0.8446601941747572, |
|
"acc_stderr": 0.03586594738573974, |
|
"acc_norm": 0.8446601941747572, |
|
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|
}, |
|
"harness|hendrycksTest-marketing|5": { |
|
"acc": 0.905982905982906, |
|
"acc_stderr": 0.019119892798924974, |
|
"acc_norm": 0.905982905982906, |
|
"acc_norm_stderr": 0.019119892798924974 |
|
}, |
|
"harness|hendrycksTest-medical_genetics|5": { |
|
"acc": 0.67, |
|
"acc_stderr": 0.047258156262526066, |
|
"acc_norm": 0.67, |
|
"acc_norm_stderr": 0.047258156262526066 |
|
}, |
|
"harness|hendrycksTest-miscellaneous|5": { |
|
"acc": 0.8697318007662835, |
|
"acc_stderr": 0.012036729568216054, |
|
"acc_norm": 0.8697318007662835, |
|
"acc_norm_stderr": 0.012036729568216054 |
|
}, |
|
"harness|hendrycksTest-moral_disputes|5": { |
|
"acc": 0.7774566473988439, |
|
"acc_stderr": 0.02239421566194282, |
|
"acc_norm": 0.7774566473988439, |
|
"acc_norm_stderr": 0.02239421566194282 |
|
}, |
|
"harness|hendrycksTest-moral_scenarios|5": { |
|
"acc": 0.5553072625698324, |
|
"acc_stderr": 0.016619881988177012, |
|
"acc_norm": 0.5553072625698324, |
|
"acc_norm_stderr": 0.016619881988177012 |
|
}, |
|
"harness|hendrycksTest-nutrition|5": { |
|
"acc": 0.7516339869281046, |
|
"acc_stderr": 0.024739981355113592, |
|
"acc_norm": 0.7516339869281046, |
|
"acc_norm_stderr": 0.024739981355113592 |
|
}, |
|
"harness|hendrycksTest-philosophy|5": { |
|
"acc": 0.77491961414791, |
|
"acc_stderr": 0.023720088516179027, |
|
"acc_norm": 0.77491961414791, |
|
"acc_norm_stderr": 0.023720088516179027 |
|
}, |
|
"harness|hendrycksTest-prehistory|5": { |
|
"acc": 0.7962962962962963, |
|
"acc_stderr": 0.02240967454730417, |
|
"acc_norm": 0.7962962962962963, |
|
"acc_norm_stderr": 0.02240967454730417 |
|
}, |
|
"harness|hendrycksTest-professional_accounting|5": { |
|
"acc": 0.5390070921985816, |
|
"acc_stderr": 0.029736592526424445, |
|
"acc_norm": 0.5390070921985816, |
|
"acc_norm_stderr": 0.029736592526424445 |
|
}, |
|
"harness|hendrycksTest-professional_law|5": { |
|
"acc": 0.5586701434159062, |
|
"acc_stderr": 0.012682016335646683, |
|
"acc_norm": 0.5586701434159062, |
|
"acc_norm_stderr": 0.012682016335646683 |
|
}, |
|
"harness|hendrycksTest-professional_medicine|5": { |
|
"acc": 0.7242647058823529, |
|
"acc_stderr": 0.027146271936625162, |
|
"acc_norm": 0.7242647058823529, |
|
"acc_norm_stderr": 0.027146271936625162 |
|
}, |
|
"harness|hendrycksTest-professional_psychology|5": { |
|
"acc": 0.761437908496732, |
|
"acc_stderr": 0.017242385828779627, |
|
"acc_norm": 0.761437908496732, |
|
"acc_norm_stderr": 0.017242385828779627 |
|
}, |
|
"harness|hendrycksTest-public_relations|5": { |
|
"acc": 0.7454545454545455, |
|
"acc_stderr": 0.041723430387053825, |
|
"acc_norm": 0.7454545454545455, |
|
"acc_norm_stderr": 0.041723430387053825 |
|
}, |
|
"harness|hendrycksTest-security_studies|5": { |
|
"acc": 0.7877551020408163, |
|
"acc_stderr": 0.026176967197866767, |
|
"acc_norm": 0.7877551020408163, |
|
"acc_norm_stderr": 0.026176967197866767 |
|
}, |
|
"harness|hendrycksTest-sociology|5": { |
|
"acc": 0.8805970149253731, |
|
"acc_stderr": 0.02292879327721974, |
|
"acc_norm": 0.8805970149253731, |
|
"acc_norm_stderr": 0.02292879327721974 |
|
}, |
|
"harness|hendrycksTest-us_foreign_policy|5": { |
|
"acc": 0.9, |
|
"acc_stderr": 0.030151134457776334, |
|
"acc_norm": 0.9, |
|
"acc_norm_stderr": 0.030151134457776334 |
|
}, |
|
"harness|hendrycksTest-virology|5": { |
|
"acc": 0.5602409638554217, |
|
"acc_stderr": 0.03864139923699122, |
|
"acc_norm": 0.5602409638554217, |
|
"acc_norm_stderr": 0.03864139923699122 |
|
}, |
|
"harness|hendrycksTest-world_religions|5": { |
|
"acc": 0.8596491228070176, |
|
"acc_stderr": 0.0266405825391332, |
|
"acc_norm": 0.8596491228070176, |
|
"acc_norm_stderr": 0.0266405825391332 |
|
}, |
|
"harness|truthfulqa:mc|0": { |
|
"mc1": 0.40269277845777235, |
|
"mc1_stderr": 0.01716883093518722, |
|
"mc2": 0.5707095526544473, |
|
"mc2_stderr": 0.01525040450448649 |
|
}, |
|
"harness|winogrande|5": { |
|
"acc": 0.8176795580110497, |
|
"acc_stderr": 0.010851565594267207 |
|
}, |
|
"harness|gsm8k|5": { |
|
"acc": 0.6444275966641395, |
|
"acc_stderr": 0.013185402252713852 |
|
} |
|
} |
|
``` |
|
# [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_MaziyarPanahi__WizardLM-Math-70B-v0.1) |
|
|
|
| Metric |Value| |
|
|---------------------------------|----:| |
|
|Avg. |70.92| |
|
|AI2 Reasoning Challenge (25-Shot)|67.06| |
|
|HellaSwag (10-Shot) |86.01| |
|
|MMLU (5-Shot) |69.14| |
|
|TruthfulQA (0-shot) |57.07| |
|
|Winogrande (5-shot) |81.77| |
|
|GSM8k (5-shot) |64.44| |
|
|
|
|
