id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 68.7k ⌀ | citation stringlengths 0 10.7k ⌀ | cardData null | likes int64 0 3.55k | downloads int64 0 10.1M | card stringlengths 0 1.01M |
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autoevaluate/autoeval-eval-zeroshot__twitter-financial-news-topic-zeroshot__twitte-178919-28982144928 | 2023-10-04T14:04:01.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- zeroshot/twitter-financial-news-topic
eval_info:
task: summarization
model: phpaiola/ptt5-base-summ-temario
metrics: ['bertscore']
dataset_name: zeroshot/twitter-financial-news-topic
dataset_config: zeroshot--twitter-financial-news-topic
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: phpaiola/ptt5-base-summ-temario
* Dataset: zeroshot/twitter-financial-news-topic
* Config: zeroshot--twitter-financial-news-topic
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@peterdevathala](https://huggingface.co/peterdevathala) for evaluating this model. |
autoevaluate/autoeval-eval-zeroshot__twitter-financial-news-topic-zeroshot__twitte-178919-28982144929 | 2023-10-04T14:56:56.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- zeroshot/twitter-financial-news-topic
eval_info:
task: summarization
model: facebook/bart-large-cnn
metrics: ['bertscore']
dataset_name: zeroshot/twitter-financial-news-topic
dataset_config: zeroshot--twitter-financial-news-topic
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: zeroshot/twitter-financial-news-topic
* Config: zeroshot--twitter-financial-news-topic
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@peterdevathala](https://huggingface.co/peterdevathala) for evaluating this model. |
autoevaluate/autoeval-eval-zeroshot__twitter-financial-news-topic-zeroshot__twitte-e590a9-28983144930 | 2023-10-04T14:04:12.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- zeroshot/twitter-financial-news-topic
eval_info:
task: summarization
model: phpaiola/ptt5-base-summ-temario
metrics: ['bertscore']
dataset_name: zeroshot/twitter-financial-news-topic
dataset_config: zeroshot--twitter-financial-news-topic
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: phpaiola/ptt5-base-summ-temario
* Dataset: zeroshot/twitter-financial-news-topic
* Config: zeroshot--twitter-financial-news-topic
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@peterdevathala](https://huggingface.co/peterdevathala) for evaluating this model. |
autoevaluate/autoeval-eval-zeroshot__twitter-financial-news-topic-zeroshot__twitte-e590a9-28983144931 | 2023-10-04T14:54:14.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- zeroshot/twitter-financial-news-topic
eval_info:
task: summarization
model: facebook/bart-large-cnn
metrics: ['bertscore']
dataset_name: zeroshot/twitter-financial-news-topic
dataset_config: zeroshot--twitter-financial-news-topic
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: zeroshot/twitter-financial-news-topic
* Config: zeroshot--twitter-financial-news-topic
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@peterdevathala](https://huggingface.co/peterdevathala) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-8cee52-28984144932 | 2023-10-04T14:00:15.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-b8dfc7-29110144933 | 2023-10-04T14:00:25.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-6f0cb9-29355144934 | 2023-10-04T14:00:35.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-6f0cb9-29355144935 | 2023-10-04T14:00:44.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-6f0cb9-29355144936 | 2023-10-04T14:00:52.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-18d944-29628144937 | 2023-10-04T14:01:02.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-banking77-default-6f5a44-29679144938 | 2023-10-04T14:01:12.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-conll2003-conll2003-b8d238-30069144939 | 2023-10-04T14:01:20.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-id_clickbait-annotated-d5b1f7-30309144940 | 2023-10-04T14:01:32.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-sentiment-be35d9-30474144941 | 2023-10-04T14:02:43.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: cardiffnlp/twitter-roberta-base-sentiment-latest
metrics: []
dataset_name: tweet_eval
dataset_config: sentiment
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: cardiffnlp/twitter-roberta-base-sentiment-latest
* Dataset: tweet_eval
* Config: sentiment
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ericbugin](https://huggingface.co/ericbugin) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-736f56-30712144944 | 2023-10-04T14:03:15.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-736f56-30712144945 | 2023-10-04T14:02:21.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-736f56-30712144946 | 2023-10-04T14:02:29.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-736f56-30712144948 | 2023-10-04T14:02:49.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-ade_corpus_v2-Ade_corpus_v2_classification-5cc293-30676144942 | 2023-10-04T14:03:07.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-93ad2d-30713144950 | 2023-10-04T14:04:12.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-93ad2d-30713144951 | 2023-10-04T14:03:21.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-93ad2d-30713144952 | 2023-10-04T14:03:31.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-93ad2d-30713144953 | 2023-10-04T14:04:45.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: elozano/tweet_offensive_eval
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: elozano/tweet_offensive_eval
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-736f56-30712144947 | 2023-10-04T14:04:47.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: elozano/tweet_offensive_eval
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: elozano/tweet_offensive_eval
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-93ad2d-30713144954 | 2023-10-04T14:03:50.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144955 | 2023-10-04T14:05:09.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: cardiffnlp/roberta-base-offensive
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: cardiffnlp/roberta-base-offensive
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144956 | 2023-10-04T14:05:10.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: cardiffnlp/twitter-roberta-base-2021-124m-offensive
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144957 | 2023-10-04T14:04:15.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144958 | 2023-10-04T14:04:29.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144959 | 2023-10-04T14:05:44.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- tweet_eval
eval_info:
task: multi_class_classification
model: elozano/tweet_offensive_eval
metrics: ['bertscore']
dataset_name: tweet_eval
dataset_config: offensive
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: elozano/tweet_offensive_eval
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@fabeelaalirawther@gmail.com](https://huggingface.co/fabeelaalirawther@gmail.com) for evaluating this model. |
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144960 | 2023-10-04T14:04:50.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-Jean-Baptiste__wikiner_fr-Jean-Baptiste__wikiner_fr-995435-30782144961 | 2023-10-04T14:04:59.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-Jean-Baptiste__wikiner_fr-Jean-Baptiste__wikiner_fr-995435-30782144962 | 2023-10-04T14:05:07.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-imdb-plain_text-d548d6-30846144963 | 2023-10-04T14:05:17.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-zeroshot__twitter-financial-news-sentiment-zeroshot__tw-cfc4d6-30970144964 | 2023-10-04T14:05:27.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
tessiw/test | 2023-10-04T14:07:26.000Z | [
"region:us"
] | tessiw | null | null | null | 0 | 0 | ---
configs:
- config_name: default
data_files:
- split: train2
path: data/train2-*
dataset_info:
features:
- name: id
dtype: string
- name: system_prompt
dtype: string
- name: question
dtype: string
- name: response
dtype: string
splits:
- name: train2
num_bytes: 1754
num_examples: 3
download_size: 6433
dataset_size: 1754
---
# Dataset Card for "test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
autoevaluate/autoeval-eval-squad_kor_v1-squad_kor_v1-773ead-31137144965 | 2023-10-04T14:05:36.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-ade_corpus_v2-Ade_corpus_v2_classification-e5a500-31239144966 | 2023-10-04T14:05:47.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad_it-default-8e27e4-31506144967 | 2023-10-04T14:05:56.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad_it-default-626c41-31522144968 | 2023-10-04T14:06:05.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-67ab09-31609144969 | 2023-10-04T14:11:55.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: 0ys/mt5-small-finetuned-amazon-en-es
metrics: []
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-67ab09-31609144970 | 2023-10-04T14:16:23.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: ARTeLab/it5-summarization-ilpost
metrics: []
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144971 | 2023-10-04T14:12:03.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: 0ys/mt5-small-finetuned-amazon-en-es
metrics: ['rouge']
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144972 | 2023-10-04T14:16:47.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: ARTeLab/it5-summarization-ilpost
metrics: ['rouge']
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144973 | 2023-10-04T14:17:01.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: ARTeLab/it5-summarization-fanpage
metrics: ['rouge']
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model. |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-e1b364-31627144974 | 2023-10-04T14:17:00.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: ARTeLab/it5-summarization-fanpage
metrics: []
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sr5434](https://huggingface.co/sr5434) for evaluating this model. |
autoevaluate/autoeval-eval-multi_nli-default-725a45-31703144975 | 2023-10-04T15:14:29.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- multi_nli
eval_info:
task: natural_language_inference
model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg
metrics: []
dataset_name: multi_nli
dataset_config: default
dataset_split: train
col_mapping:
text1: premise
text2: hypothesis
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg
* Dataset: multi_nli
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@2552](https://huggingface.co/2552) for evaluating this model. |
autoevaluate/autoeval-eval-squad_it-default-23b92b-31766144976 | 2023-10-04T14:07:17.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-e82217-31832144977 | 2023-10-04T14:07:27.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144978 | 2023-10-04T14:07:36.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144979 | 2023-10-04T14:07:45.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144980 | 2023-10-04T14:07:54.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144981 | 2023-10-04T14:08:06.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144982 | 2023-10-04T14:08:15.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144983 | 2023-10-04T14:08:23.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144984 | 2023-10-04T14:08:34.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144985 | 2023-10-04T14:08:45.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144986 | 2023-10-04T14:08:55.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-01abad-31923144987 | 2023-10-04T14:09:05.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144988 | 2023-10-04T14:09:16.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144989 | 2023-10-04T14:09:25.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144990 | 2023-10-04T14:09:34.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144991 | 2023-10-04T14:09:45.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144992 | 2023-10-04T14:09:55.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144993 | 2023-10-04T14:10:04.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144994 | 2023-10-04T14:10:14.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144995 | 2023-10-04T14:10:25.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144996 | 2023-10-04T14:10:34.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-commanderstrife__jnlpba-jnlpba-cb558b-31925144997 | 2023-10-04T14:10:43.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927144998 | 2023-10-04T14:10:51.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927144999 | 2023-10-04T14:11:01.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145000 | 2023-10-04T14:16:15.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- drAbreu/bc4chemd_ner
eval_info:
task: entity_extraction
model: sschet/biobert_chemical_ner
metrics: []
dataset_name: drAbreu/bc4chemd_ner
dataset_config: bc4chemd
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: sschet/biobert_chemical_ner
* Dataset: drAbreu/bc4chemd_ner
* Config: bc4chemd
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sschet](https://huggingface.co/sschet) for evaluating this model. |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145001 | 2023-10-04T14:11:20.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145002 | 2023-10-04T14:11:31.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145003 | 2023-10-04T14:11:42.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145004 | 2023-10-04T14:11:50.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145005 | 2023-10-04T14:12:00.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145006 | 2023-10-04T14:12:11.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145007 | 2023-10-04T14:12:20.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-cuad-default-1afd53-32124145008 | 2023-10-04T14:12:29.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad_it-default-deec75-32207145009 | 2023-10-04T14:12:40.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-billsum-default-bec98f-32334145010 | 2023-10-04T14:12:51.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-billsum-default-bec98f-32334145011 | 2023-10-04T14:28:44.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- billsum
eval_info:
task: summarization
model: PoseyATX/Moist-Pony
metrics: []
dataset_name: billsum
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: PoseyATX/Moist-Pony
* Dataset: billsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@poseyatx](https://huggingface.co/poseyatx) for evaluating this model. |
autoevaluate/autoeval-eval-ade_corpus_v2-Ade_corpus_v2_classification-b93f9f-32775145012 | 2023-10-04T14:13:09.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-amazon_polarity-amazon_polarity-d08caa-33166145013 | 2023-10-04T14:13:19.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-xsum-default-403a15-33262145014 | 2023-10-04T14:15:56.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xsum
eval_info:
task: summarization
model: Alred/t5-small-finetuned-summarization-cnn
metrics: []
dataset_name: xsum
dataset_config: default
dataset_split: test
col_mapping:
text: document
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Alred/t5-small-finetuned-summarization-cnn
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@dfantasy](https://huggingface.co/dfantasy) for evaluating this model. |
open-llm-leaderboard/details_bongchoi__test-llama2-70b | 2023-10-04T14:14:30.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 0 | ---
pretty_name: Evaluation run of bongchoi/test-llama2-70b
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [bongchoi/test-llama2-70b](https://huggingface.co/bongchoi/test-llama2-70b) on\
\ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 61 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 agregated 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_bongchoi__test-llama2-70b\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-10-04T14:13:10.692338](https://huggingface.co/datasets/open-llm-leaderboard/details_bongchoi__test-llama2-70b/blob/main/results_2023-10-04T14-13-10.692338.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\": 0.6967225637378714,\n\
\ \"acc_stderr\": 0.030867069907791145,\n \"acc_norm\": 0.7008615431872544,\n\
\ \"acc_norm_stderr\": 0.030836865817034945,\n \"mc1\": 0.3108935128518972,\n\
\ \"mc1_stderr\": 0.016203316673559696,\n \"mc2\": 0.44923493721887353,\n\
\ \"mc2_stderr\": 0.01390226410719232\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6262798634812287,\n \"acc_stderr\": 0.014137708601759091,\n\
\ \"acc_norm\": 0.6732081911262798,\n \"acc_norm_stderr\": 0.013706665975587333\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6760605457080263,\n\
\ \"acc_stderr\": 0.00467020812857923,\n \"acc_norm\": 0.8733320055765784,\n\
\ \"acc_norm_stderr\": 0.0033192094001351187\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n\
\ \"acc_stderr\": 0.04171654161354544,\n \"acc_norm\": 0.6296296296296297,\n\
\ \"acc_norm_stderr\": 0.04171654161354544\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.8092105263157895,\n \"acc_stderr\": 0.031975658210325,\n\
\ \"acc_norm\": 0.8092105263157895,\n \"acc_norm_stderr\": 0.031975658210325\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.72,\n\
\ \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\": 0.72,\n \
\ \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7169811320754716,\n \"acc_stderr\": 0.027724236492700918,\n\
\ \"acc_norm\": 0.7169811320754716,\n \"acc_norm_stderr\": 0.027724236492700918\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8472222222222222,\n\
\ \"acc_stderr\": 0.030085743248565666,\n \"acc_norm\": 0.8472222222222222,\n\
\ \"acc_norm_stderr\": 0.030085743248565666\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \
\ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\": 0.6,\n\
\ \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.048523658709391,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.048523658709391\n },\n\
\ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6416184971098265,\n\
\ \"acc_stderr\": 0.03656343653353159,\n \"acc_norm\": 0.6416184971098265,\n\
\ \"acc_norm_stderr\": 0.03656343653353159\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082635,\n\
\ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082635\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n\
\ \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.6638297872340425,\n \"acc_stderr\": 0.030881618520676942,\n\
\ \"acc_norm\": 0.6638297872340425,\n \"acc_norm_stderr\": 0.030881618520676942\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4473684210526316,\n\
\ \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.4473684210526316,\n\
\ \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.6551724137931034,\n \"acc_stderr\": 0.03960933549451207,\n\
\ \"acc_norm\": 0.6551724137931034,\n \"acc_norm_stderr\": 0.03960933549451207\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.43386243386243384,\n \"acc_stderr\": 0.025525034382474894,\n \"\
acc_norm\": 0.43386243386243384,\n \"acc_norm_stderr\": 0.025525034382474894\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.47619047619047616,\n\
\ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n\
\ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \
\ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620332\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8193548387096774,\n\
\ \"acc_stderr\": 0.02188617856717253,\n \"acc_norm\": 0.8193548387096774,\n\
\ \"acc_norm_stderr\": 0.02188617856717253\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n\
\ \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\"\
: 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.8303030303030303,\n \"acc_stderr\": 0.029311188674983134,\n\
\ \"acc_norm\": 0.8303030303030303,\n \"acc_norm_stderr\": 0.029311188674983134\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.8787878787878788,\n \"acc_stderr\": 0.023253157951942084,\n \"\
acc_norm\": 0.8787878787878788,\n \"acc_norm_stderr\": 0.023253157951942084\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9430051813471503,\n \"acc_stderr\": 0.016731085293607555,\n\
\ \"acc_norm\": 0.9430051813471503,\n \"acc_norm_stderr\": 0.016731085293607555\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.7410256410256411,\n \"acc_stderr\": 0.02221110681006167,\n \
\ \"acc_norm\": 0.7410256410256411,\n \"acc_norm_stderr\": 0.02221110681006167\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.35555555555555557,\n \"acc_stderr\": 0.029185714949857403,\n \
\ \"acc_norm\": 0.35555555555555557,\n \"acc_norm_stderr\": 0.029185714949857403\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.7647058823529411,\n \"acc_stderr\": 0.02755361446786381,\n \
\ \"acc_norm\": 0.7647058823529411,\n \"acc_norm_stderr\": 0.02755361446786381\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.4304635761589404,\n \"acc_stderr\": 0.04042809961395634,\n \"\
acc_norm\": 0.4304635761589404,\n \"acc_norm_stderr\": 0.04042809961395634\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8733944954128441,\n \"acc_stderr\": 0.014257128686165169,\n \"\
acc_norm\": 0.8733944954128441,\n \"acc_norm_stderr\": 0.014257128686165169\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.6342592592592593,\n \"acc_stderr\": 0.032847388576472056,\n \"\
acc_norm\": 0.6342592592592593,\n \"acc_norm_stderr\": 0.032847388576472056\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8970588235294118,\n \"acc_stderr\": 0.02132833757080437,\n \"\
acc_norm\": 0.8970588235294118,\n \"acc_norm_stderr\": 0.02132833757080437\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8776371308016878,\n \"acc_stderr\": 0.021331741829746786,\n \
\ \"acc_norm\": 0.8776371308016878,\n \"acc_norm_stderr\": 0.021331741829746786\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.8026905829596412,\n\
\ \"acc_stderr\": 0.02670985334496796,\n \"acc_norm\": 0.8026905829596412,\n\
\ \"acc_norm_stderr\": 0.02670985334496796\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8778625954198473,\n \"acc_stderr\": 0.028718776889342344,\n\
\ \"acc_norm\": 0.8778625954198473,\n \"acc_norm_stderr\": 0.028718776889342344\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8760330578512396,\n \"acc_stderr\": 0.03008309871603521,\n \"\
acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.03008309871603521\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n\
\ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\
\ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.803680981595092,\n \"acc_stderr\": 0.031207970394709218,\n\
\ \"acc_norm\": 0.803680981595092,\n \"acc_norm_stderr\": 0.031207970394709218\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5357142857142857,\n\
\ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.5357142857142857,\n\
\ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\
\ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.905982905982906,\n\
\ \"acc_stderr\": 0.01911989279892498,\n \"acc_norm\": 0.905982905982906,\n\
\ \"acc_norm_stderr\": 0.01911989279892498\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.74,\n \"acc_stderr\": 0.04408440022768077,\n \
\ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.04408440022768077\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8620689655172413,\n\
\ \"acc_stderr\": 0.012331009307795656,\n \"acc_norm\": 0.8620689655172413,\n\
\ \"acc_norm_stderr\": 0.012331009307795656\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7774566473988439,\n \"acc_stderr\": 0.02239421566194282,\n\
\ \"acc_norm\": 0.7774566473988439,\n \"acc_norm_stderr\": 0.02239421566194282\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4547486033519553,\n\
\ \"acc_stderr\": 0.016653875777524012,\n \"acc_norm\": 0.4547486033519553,\n\
\ \"acc_norm_stderr\": 0.016653875777524012\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7810457516339869,\n \"acc_stderr\": 0.02367908986180772,\n\
\ \"acc_norm\": 0.7810457516339869,\n \"acc_norm_stderr\": 0.02367908986180772\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7877813504823151,\n\
\ \"acc_stderr\": 0.023222756797435115,\n \"acc_norm\": 0.7877813504823151,\n\
\ \"acc_norm_stderr\": 0.023222756797435115\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.8364197530864198,\n \"acc_stderr\": 0.020581466138257114,\n\
\ \"acc_norm\": 0.8364197530864198,\n \"acc_norm_stderr\": 0.020581466138257114\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.5673758865248227,\n \"acc_stderr\": 0.02955545423677884,\n \
\ \"acc_norm\": 0.5673758865248227,\n \"acc_norm_stderr\": 0.02955545423677884\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5319426336375489,\n\
\ \"acc_stderr\": 0.012744149704869645,\n \"acc_norm\": 0.5319426336375489,\n\
\ \"acc_norm_stderr\": 0.012744149704869645\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.75,\n \"acc_stderr\": 0.026303648393696036,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.026303648393696036\n \
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\"\
: 0.7565359477124183,\n \"acc_stderr\": 0.01736247376214662,\n \"\
acc_norm\": 0.7565359477124183,\n \"acc_norm_stderr\": 0.01736247376214662\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6909090909090909,\n\
\ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\
\ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7918367346938775,\n \"acc_stderr\": 0.0259911176728133,\n\
\ \"acc_norm\": 0.7918367346938775,\n \"acc_norm_stderr\": 0.0259911176728133\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.900497512437811,\n\
\ \"acc_stderr\": 0.021166216304659393,\n \"acc_norm\": 0.900497512437811,\n\
\ \"acc_norm_stderr\": 0.021166216304659393\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.92,\n \"acc_stderr\": 0.0272659924344291,\n \
\ \"acc_norm\": 0.92,\n \"acc_norm_stderr\": 0.0272659924344291\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5301204819277109,\n\
\ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\
\ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.027097290118070806,\n\
\ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.027097290118070806\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3108935128518972,\n\
\ \"mc1_stderr\": 0.016203316673559696,\n \"mc2\": 0.44923493721887353,\n\
\ \"mc2_stderr\": 0.01390226410719232\n }\n}\n```"
repo_url: https://huggingface.co/bongchoi/test-llama2-70b
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|arc:challenge|25_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hellaswag|10_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T14-13-10.692338.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T14-13-10.692338.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-04T14-13-10.692338.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-04T14-13-10.692338.parquet'
- config_name: results
data_files:
- split: 2023_10_04T14_13_10.692338
path:
- results_2023-10-04T14-13-10.692338.parquet
- split: latest
path:
- results_2023-10-04T14-13-10.692338.parquet
---
# Dataset Card for Evaluation run of bongchoi/test-llama2-70b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/bongchoi/test-llama2-70b
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [bongchoi/test-llama2-70b](https://huggingface.co/bongchoi/test-llama2-70b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 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 agregated 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_bongchoi__test-llama2-70b",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-04T14:13:10.692338](https://huggingface.co/datasets/open-llm-leaderboard/details_bongchoi__test-llama2-70b/blob/main/results_2023-10-04T14-13-10.692338.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": 0.6967225637378714,
"acc_stderr": 0.030867069907791145,
"acc_norm": 0.7008615431872544,
"acc_norm_stderr": 0.030836865817034945,
"mc1": 0.3108935128518972,
"mc1_stderr": 0.016203316673559696,
"mc2": 0.44923493721887353,
"mc2_stderr": 0.01390226410719232
},
"harness|arc:challenge|25": {
"acc": 0.6262798634812287,
"acc_stderr": 0.014137708601759091,
"acc_norm": 0.6732081911262798,
"acc_norm_stderr": 0.013706665975587333
},
"harness|hellaswag|10": {
"acc": 0.6760605457080263,
"acc_stderr": 0.00467020812857923,
"acc_norm": 0.8733320055765784,
"acc_norm_stderr": 0.0033192094001351187
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.33,
"acc_stderr": 0.04725815626252605,
"acc_norm": 0.33,
"acc_norm_stderr": 0.04725815626252605
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6296296296296297,
"acc_stderr": 0.04171654161354544,
"acc_norm": 0.6296296296296297,
"acc_norm_stderr": 0.04171654161354544
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.8092105263157895,
"acc_stderr": 0.031975658210325,
"acc_norm": 0.8092105263157895,
"acc_norm_stderr": 0.031975658210325
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.72,
"acc_stderr": 0.04512608598542127,
"acc_norm": 0.72,
"acc_norm_stderr": 0.04512608598542127
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7169811320754716,
"acc_stderr": 0.027724236492700918,
"acc_norm": 0.7169811320754716,
"acc_norm_stderr": 0.027724236492700918
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.8472222222222222,
"acc_stderr": 0.030085743248565666,
"acc_norm": 0.8472222222222222,
"acc_norm_stderr": 0.030085743248565666
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.51,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.51,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.6,
"acc_stderr": 0.049236596391733084,
"acc_norm": 0.6,
"acc_norm_stderr": 0.049236596391733084
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.37,
"acc_stderr": 0.048523658709391,
"acc_norm": 0.37,
"acc_norm_stderr": 0.048523658709391
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6416184971098265,
"acc_stderr": 0.03656343653353159,
"acc_norm": 0.6416184971098265,
"acc_norm_stderr": 0.03656343653353159
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.37254901960784315,
"acc_stderr": 0.04810840148082635,
"acc_norm": 0.37254901960784315,
"acc_norm_stderr": 0.04810840148082635
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.77,
"acc_stderr": 0.04229525846816506,
"acc_norm": 0.77,
"acc_norm_stderr": 0.04229525846816506
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.6638297872340425,
"acc_stderr": 0.030881618520676942,
"acc_norm": 0.6638297872340425,
"acc_norm_stderr": 0.030881618520676942
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4473684210526316,
"acc_stderr": 0.04677473004491199,
"acc_norm": 0.4473684210526316,
"acc_norm_stderr": 0.04677473004491199
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.6551724137931034,
"acc_stderr": 0.03960933549451207,
"acc_norm": 0.6551724137931034,
"acc_norm_stderr": 0.03960933549451207
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.43386243386243384,
"acc_stderr": 0.025525034382474894,
"acc_norm": 0.43386243386243384,
"acc_norm_stderr": 0.025525034382474894
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.47619047619047616,
"acc_stderr": 0.04467062628403273,
"acc_norm": 0.47619047619047616,
"acc_norm_stderr": 0.04467062628403273
},
"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": 0.8193548387096774,
"acc_stderr": 0.02188617856717253,
"acc_norm": 0.8193548387096774,
"acc_norm_stderr": 0.02188617856717253
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5123152709359606,
"acc_stderr": 0.035169204442208966,
"acc_norm": 0.5123152709359606,
"acc_norm_stderr": 0.035169204442208966
},
"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": 0.8303030303030303,
"acc_stderr": 0.029311188674983134,
"acc_norm": 0.8303030303030303,
"acc_norm_stderr": 0.029311188674983134
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.8787878787878788,
"acc_stderr": 0.023253157951942084,
"acc_norm": 0.8787878787878788,
"acc_norm_stderr": 0.023253157951942084
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9430051813471503,
"acc_stderr": 0.016731085293607555,
"acc_norm": 0.9430051813471503,
"acc_norm_stderr": 0.016731085293607555
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.7410256410256411,
"acc_stderr": 0.02221110681006167,
"acc_norm": 0.7410256410256411,
"acc_norm_stderr": 0.02221110681006167
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.35555555555555557,
"acc_stderr": 0.029185714949857403,
"acc_norm": 0.35555555555555557,
"acc_norm_stderr": 0.029185714949857403
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.7647058823529411,
"acc_stderr": 0.02755361446786381,
"acc_norm": 0.7647058823529411,
"acc_norm_stderr": 0.02755361446786381
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.4304635761589404,
"acc_stderr": 0.04042809961395634,
"acc_norm": 0.4304635761589404,
"acc_norm_stderr": 0.04042809961395634
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8733944954128441,
"acc_stderr": 0.014257128686165169,
"acc_norm": 0.8733944954128441,
"acc_norm_stderr": 0.014257128686165169
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.6342592592592593,
"acc_stderr": 0.032847388576472056,
"acc_norm": 0.6342592592592593,
"acc_norm_stderr": 0.032847388576472056
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8970588235294118,
"acc_stderr": 0.02132833757080437,
"acc_norm": 0.8970588235294118,
"acc_norm_stderr": 0.02132833757080437
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.8776371308016878,
"acc_stderr": 0.021331741829746786,
"acc_norm": 0.8776371308016878,
"acc_norm_stderr": 0.021331741829746786
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.8026905829596412,
"acc_stderr": 0.02670985334496796,
"acc_norm": 0.8026905829596412,
"acc_norm_stderr": 0.02670985334496796
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.8778625954198473,
"acc_stderr": 0.028718776889342344,
"acc_norm": 0.8778625954198473,
"acc_norm_stderr": 0.028718776889342344
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.8760330578512396,
"acc_stderr": 0.03008309871603521,
"acc_norm": 0.8760330578512396,
"acc_norm_stderr": 0.03008309871603521
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.8333333333333334,
"acc_stderr": 0.03602814176392645,
"acc_norm": 0.8333333333333334,
"acc_norm_stderr": 0.03602814176392645
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.803680981595092,
"acc_stderr": 0.031207970394709218,
"acc_norm": 0.803680981595092,
"acc_norm_stderr": 0.031207970394709218
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.5357142857142857,
"acc_stderr": 0.04733667890053756,
"acc_norm": 0.5357142857142857,
"acc_norm_stderr": 0.04733667890053756
},
"harness|hendrycksTest-management|5": {
"acc": 0.8349514563106796,
"acc_stderr": 0.03675668832233188,
"acc_norm": 0.8349514563106796,
"acc_norm_stderr": 0.03675668832233188
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.905982905982906,
"acc_stderr": 0.01911989279892498,
"acc_norm": 0.905982905982906,
"acc_norm_stderr": 0.01911989279892498
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.74,
"acc_stderr": 0.04408440022768077,
"acc_norm": 0.74,
"acc_norm_stderr": 0.04408440022768077
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8620689655172413,
"acc_stderr": 0.012331009307795656,
"acc_norm": 0.8620689655172413,
"acc_norm_stderr": 0.012331009307795656
},
"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": 0.4547486033519553,
"acc_stderr": 0.016653875777524012,
"acc_norm": 0.4547486033519553,
"acc_norm_stderr": 0.016653875777524012
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7810457516339869,
"acc_stderr": 0.02367908986180772,
"acc_norm": 0.7810457516339869,
"acc_norm_stderr": 0.02367908986180772
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.7877813504823151,
"acc_stderr": 0.023222756797435115,
"acc_norm": 0.7877813504823151,
"acc_norm_stderr": 0.023222756797435115
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.8364197530864198,
"acc_stderr": 0.020581466138257114,
"acc_norm": 0.8364197530864198,
"acc_norm_stderr": 0.020581466138257114
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.5673758865248227,
"acc_stderr": 0.02955545423677884,
"acc_norm": 0.5673758865248227,
"acc_norm_stderr": 0.02955545423677884
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.5319426336375489,
"acc_stderr": 0.012744149704869645,
"acc_norm": 0.5319426336375489,
"acc_norm_stderr": 0.012744149704869645
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.75,
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"acc_norm": 0.75,
"acc_norm_stderr": 0.026303648393696036
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.7565359477124183,
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"acc_norm": 0.7565359477124183,
"acc_norm_stderr": 0.01736247376214662
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6909090909090909,
"acc_stderr": 0.044262946482000985,
"acc_norm": 0.6909090909090909,
"acc_norm_stderr": 0.044262946482000985
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.7918367346938775,
"acc_stderr": 0.0259911176728133,
"acc_norm": 0.7918367346938775,
"acc_norm_stderr": 0.0259911176728133
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.900497512437811,
"acc_stderr": 0.021166216304659393,
"acc_norm": 0.900497512437811,
"acc_norm_stderr": 0.021166216304659393
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.92,
"acc_stderr": 0.0272659924344291,
"acc_norm": 0.92,
"acc_norm_stderr": 0.0272659924344291
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5301204819277109,
"acc_stderr": 0.03885425420866767,
"acc_norm": 0.5301204819277109,
"acc_norm_stderr": 0.03885425420866767
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8538011695906432,
"acc_stderr": 0.027097290118070806,
"acc_norm": 0.8538011695906432,
"acc_norm_stderr": 0.027097290118070806
},
"harness|truthfulqa:mc|0": {
"mc1": 0.3108935128518972,
"mc1_stderr": 0.016203316673559696,
"mc2": 0.44923493721887353,
"mc2_stderr": 0.01390226410719232
}
}
```
### 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] |
autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_dev-mathemakitte-a11de2-45191145157 | 2023-10-04T14:13:36.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-xsum-default-cf6255-33263145015 | 2023-10-04T14:16:03.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xsum
eval_info:
task: summarization
model: t5-small
metrics: []
dataset_name: xsum
dataset_config: default
dataset_split: test
col_mapping:
text: document
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@thefirebanks](https://huggingface.co/thefirebanks) for evaluating this model. |
autoevaluate/autoeval-eval-ag_news-default-3c97aa-33465145016 | 2023-10-04T14:13:48.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad_v2-squad_v2-79ae53-33494145017 | 2023-10-04T14:13:57.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-xsum-default-01da82-33500145018 | 2023-10-04T14:16:30.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xsum
eval_info:
task: summarization
model: t5-small
metrics: []
dataset_name: xsum
dataset_config: default
dataset_split: test
col_mapping:
text: document
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@dfantasy](https://huggingface.co/dfantasy) for evaluating this model. |
autoevaluate/autoeval-eval-yelp_review_full-yelp_review_full-4aa164-33656145019 | 2023-10-04T14:14:17.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-yelp_review_full-yelp_review_full-4aa164-33656145020 | 2023-10-04T14:14:26.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-3c7ce4-33925145021 | 2023-10-04T14:14:35.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-allocine-allocine-a88052-34639145022 | 2023-10-04T14:14:47.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-allocine-allocine-16a42b-34641145023 | 2023-10-04T14:14:55.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-squad-plain_text-c462da-35081145024 | 2023-10-04T14:15:05.000Z | [
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | Entry not found |
autoevaluate/autoeval-eval-amazon_reviews_multi-en-4405a7-35409145025 | 2023-10-04T14:16:40.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- amazon_reviews_multi
eval_info:
task: summarization
model: 0ys/mt5-small-finetuned-amazon-en-es
metrics: ['accuracy', 'bertscore', 'precision']
dataset_name: amazon_reviews_multi
dataset_config: en
dataset_split: test
col_mapping:
text: review_body
target: review_title
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: amazon_reviews_multi
* Config: en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Caxmann](https://huggingface.co/Caxmann) for evaluating this model. |
autoevaluate/autoeval-eval-gnad10-default-1a81d6-36119145026 | 2023-10-04T14:16:33.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | null | 0 | 0 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- gnad10
eval_info:
task: multi_class_classification
model: Mathking/bert-base-german-cased-gnad10
metrics: []
dataset_name: gnad10
dataset_config: default
dataset_split: train
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Mathking/bert-base-german-cased-gnad10
* Dataset: gnad10
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@BraveStone9](https://huggingface.co/BraveStone9) for evaluating this model. |
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