open-llm-leaderboard-old/details_PulsarAI__Nebula-v2-7B

---
pretty_name: Evaluation run of PulsarAI/Nebula-v2-7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [PulsarAI/Nebula-v2-7B](https://huggingface.co/PulsarAI/Nebula-v2-7B) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 1 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_PulsarAI__Nebula-v2-7B\"\
,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\
\ are the [latest results from run 2023-12-02T13:58:09.073163](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Nebula-v2-7B/blob/main/results_2023-12-02T13-58-09.073163.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.3169067475360121,\n\
\ \"acc_stderr\": 0.012815868296721373\n },\n \"harness|gsm8k|5\":\
\ {\n \"acc\": 0.3169067475360121,\n \"acc_stderr\": 0.012815868296721373\n\
\ }\n}\n```"
repo_url: https://huggingface.co/PulsarAI/Nebula-v2-7B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [e-mail]
configs:
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_02T13_58_09.073163
path:
- '**/details_harness|gsm8k|5_2023-12-02T13-58-09.073163.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-02T13-58-09.073163.parquet'
- config_name: results
data_files:
- split: 2023_12_02T13_58_09.073163
path:
- results_2023-12-02T13-58-09.073163.parquet
- split: latest
path:
- results_2023-12-02T13-58-09.073163.parquet
---

# Dataset Card for Evaluation run of PulsarAI/Nebula-v2-7B

## Dataset Description

- **Homepage:**
- **Repository:** https://huggingface.co/PulsarAI/Nebula-v2-7B
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [e-mail]

### Dataset Summary

Dataset automatically created during the evaluation run of model [PulsarAI/Nebula-v2-7B](https://huggingface.co/PulsarAI/Nebula-v2-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).

The dataset is composed of 1 configuration, each one coresponding to one of the evaluated task.

The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.

An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).

To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_PulsarAI__Nebula-v2-7B",
"harness_gsm8k_5",
split="train")
```

## Latest results

These are the [latest results from run 2023-12-02T13:58:09.073163](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Nebula-v2-7B/blob/main/results_2023-12-02T13-58-09.073163.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):

```python
{
"all": {
"acc": 0.3169067475360121,
"acc_stderr": 0.012815868296721373
},
"harness|gsm8k|5": {
"acc": 0.3169067475360121,
"acc_stderr": 0.012815868296721373
}
}
```

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]

原始信息汇总

数据集卡片 for Evaluation run of PulsarAI/Nebula-v2-7B

数据集描述

数据集概述

数据集是在模型 PulsarAI/Nebula-v2-7B 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集由1个配置组成，每个配置对应一个评估任务。

数据集从1次运行中创建。每次运行可以在每个配置中作为一个特定的分割找到，分割名称使用运行的 timestamp。"train" 分割总是指向最新的结果。

一个额外的配置 "results" 存储了所有运行的聚合结果（并用于计算和显示 Open LLM Leaderboard 上的聚合指标）。

最新结果

以下是来自 2023-12-02T13:58:09.073163 运行的最新结果：

python { "all": { "acc": 0.3169067475360121, "acc_stderr": 0.012815868296721373 }, "harness|gsm8k|5": { "acc": 0.3169067475360121, "acc_stderr": 0.012815868296721373 } }

数据集结构

配置

• config_name: harness_gsm8k_5

  • 分割: 2023_12_02T13_58_09.073163
    • 路径: **/details_harness|gsm8k|5_2023-12-02T13-58-09.073163.parquet
  • 分割: latest
    • 路径: **/details_harness|gsm8k|5_2023-12-02T13-58-09.073163.parquet

• config_name: results

  • 分割: 2023_12_02T13_58_09.073163
    • 路径: results_2023-12-02T13-58-09.073163.parquet
  • 分割: latest
    • 路径: results_2023-12-02T13-58-09.073163.parquet