datasetId
stringlengths 5
121
| author
stringlengths 2
42
| last_modified
unknown | downloads
int64 0
36.3M
| likes
int64 0
5.62k
| tags
sequencelengths 1
7.92k
| task_categories
sequencelengths 0
40
⌀ | createdAt
unknown | card
stringlengths 19
977k
|
---|---|---|---|---|---|---|---|---|
pe-nlp/ov-kit-files-filtered-dedup-v2 | pe-nlp | "2024-06-04T03:24:01Z" | 0 | 0 | [
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:11:01Z" | ---
dataset_info:
features:
- name: file_path
dtype: string
- name: content
dtype: string
- name: size
dtype: int64
- name: lang
dtype: string
- name: avg_line_length
dtype: float64
- name: max_line_length
dtype: int64
- name: alphanum_fraction
dtype: float64
splits:
- name: train
num_bytes: 131808984.32157095
num_examples: 13422
download_size: 41164163
dataset_size: 131808984.32157095
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Navi2184/training | Navi2184 | "2024-05-27T09:16:55Z" | 0 | 0 | [
"license:llama3",
"region:us"
] | null | "2024-05-27T09:16:55Z" | ---
license: llama3
---
|
arjunshajitech/sample_dataset_ml | arjunshajitech | "2024-05-27T09:19:05Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:19:01Z" | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 121879.0
num_examples: 1
download_size: 125034
dataset_size: 121879.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.21_tag | rakshya34 | "2024-05-27T09:20:31Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:20:30Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: float64
- name: phonemes
dtype: string
splits:
- name: train
num_bytes: 2100525
num_examples: 5000
download_size: 998537
dataset_size: 2100525
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.22_tag | rakshya34 | "2024-05-27T12:18:09Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:29:13Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2459572
num_examples: 5000
download_size: 964261
dataset_size: 2459572
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
procit005/final_2 | procit005 | "2024-05-27T09:35:19Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:35:17Z" | ---
dataset_info:
features:
- name: train
struct:
- name: dimension
struct:
- name: length
dtype: float64
- name: width
dtype: float64
- name: occupied_space
dtype: string
- name: time
dtype: string
- name: type
dtype: string
splits:
- name: train
num_bytes: 1141
num_examples: 24
- name: test
num_bytes: 145
num_examples: 3
- name: eval
num_bytes: 145
num_examples: 3
download_size: 9481
dataset_size: 1431
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: eval
path: data/eval-*
---
|
Huggmachas/Humor_dataset | Huggmachas | "2024-05-27T09:37:24Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:37:19Z" | ---
dataset_info:
features:
- name: Text
dtype: string
- name: Lang
dtype: string
- name: Label
dtype: int64
splits:
- name: train
num_bytes: 500764
num_examples: 3418
download_size: 281608
dataset_size: 500764
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.23_tag | rakshya34 | "2024-05-27T12:18:42Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:37:54Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2447473
num_examples: 5000
download_size: 956394
dataset_size: 2447473
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
IntellyaDS/wikipedia-23-11-sr | IntellyaDS | "2024-06-03T10:36:27Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:43:40Z" | ---
license: apache-2.0
---
|
rakshya34/filtered_voice_english_v1.24_tag | rakshya34 | "2024-05-27T12:19:15Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:46:19Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2469311
num_examples: 5000
download_size: 966815
dataset_size: 2469311
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.25_tag | rakshya34 | "2024-05-27T12:19:48Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T09:54:49Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2492519
num_examples: 5000
download_size: 982526
dataset_size: 2492519
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
MusketCat/CyberMysticism | MusketCat | "2024-05-27T17:35:47Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:02:09Z" | ---
license: apache-2.0
---
|
rakshya34/filtered_voice_english_v1.27_tag | rakshya34 | "2024-05-27T10:07:35Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:07:34Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: float64
- name: phonemes
dtype: string
splits:
- name: train
num_bytes: 2077426
num_examples: 5000
download_size: 980434
dataset_size: 2077426
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Huggmachas/Hate_Dataset | Huggmachas | "2024-05-27T10:14:44Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:14:39Z" | ---
dataset_info:
features:
- name: id
dtype: int64
- name: id_str
dtype: string
- name: full_text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 562324
num_examples: 2940
download_size: 392059
dataset_size: 562324
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.28_tag | rakshya34 | "2024-05-27T12:20:23Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:16:03Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2481963
num_examples: 5000
download_size: 965757
dataset_size: 2481963
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
CHHHH/M3AV_v1.0 | CHHHH | "2024-06-01T12:35:47Z" | 0 | 0 | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | "2024-05-27T10:20:11Z" | ---
license: cc-by-nc-sa-4.0
---
Project website: https://jack-zc8.github.io/M3AV-dataset-page/ |
rakshya34/filtered_voice_english_v1.29_tag | rakshya34 | "2024-05-27T12:20:56Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:24:48Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2449310
num_examples: 5000
download_size: 955370
dataset_size: 2449310
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Angel55/sample_spider_data | Angel55 | "2024-05-27T10:43:54Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:33:08Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 1976728
num_examples: 969
download_size: 190517
dataset_size: 1976728
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
|
rakshya34/filtered_voice_english_v1.30_tag | rakshya34 | "2024-05-27T12:21:29Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:33:34Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2465265
num_examples: 5000
download_size: 960745
dataset_size: 2465265
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
theodorr/mls_10k_eng_encodec | theodorr | "2024-05-27T13:20:39Z" | 0 | 0 | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:34:13Z" | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: original_path
dtype: string
- name: begin_time
dtype: float64
- name: end_time
dtype: float64
- name: transcript
dtype: string
- name: audio_duration
dtype: float64
- name: speaker_id
dtype: string
- name: book_id
dtype: string
- name: audio_token
sequence:
sequence:
sequence:
sequence: int64
splits:
- name: train
num_bytes: 244934398940.205
num_examples: 2420047
download_size: 171168727024
dataset_size: 244934398940.205
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
deboleen6/telugu_tts | deboleen6 | "2024-05-27T10:53:59Z" | 0 | 1 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:37:31Z" | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: speaker_id
dtype: int64
splits:
- name: train
num_bytes: 603114413.488
num_examples: 4448
download_size: 466010970
dataset_size: 603114413.488
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
CAGV/marcus | CAGV | "2024-05-27T10:48:56Z" | 0 | 0 | [
"license:openrail",
"size_categories:n<1K",
"format:audiofolder",
"modality:audio",
"library:datasets",
"library:mlcroissant",
"region:us"
] | null | "2024-05-27T10:40:27Z" | ---
license: openrail
---
|
rakshya34/filtered_voice_english_v1.31_tag | rakshya34 | "2024-05-27T12:22:01Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:42:16Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2375915
num_examples: 5000
download_size: 890882
dataset_size: 2375915
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
baby88888888/666666 | baby88888888 | "2024-05-27T10:44:14Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:1K<n<10K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:42:48Z" | ---
license: apache-2.0
---
|
Angel55/sample_data | Angel55 | "2024-05-27T12:18:14Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:46:30Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: test
num_bytes: 6053
num_examples: 5
download_size: 8850
dataset_size: 6053
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
|
rakshya34/filtered_voice_english_v1.32_tag | rakshya34 | "2024-05-27T12:22:34Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:51:19Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2405183
num_examples: 5000
download_size: 918773
dataset_size: 2405183
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
bloomdata/wikisql | bloomdata | "2024-05-27T10:55:45Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T10:53:31Z" | ---
license: apache-2.0
---
|
rakshya34/filtered_voice_english_v1.33_tag | rakshya34 | "2024-05-27T12:23:07Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:00:27Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2477280
num_examples: 5000
download_size: 967960
dataset_size: 2477280
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
bloomdata/spider | bloomdata | "2024-05-27T11:26:33Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:1K<n<10K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:08:08Z" | ---
license: apache-2.0
---
|
rakshya34/filtered_voice_english_v1.35_tag | rakshya34 | "2024-05-27T11:13:22Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:13:20Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: float64
- name: phonemes
dtype: string
splits:
- name: train
num_bytes: 2091394
num_examples: 5000
download_size: 986698
dataset_size: 2091394
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.36_tag | rakshya34 | "2024-05-27T12:23:43Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:22:14Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2462261
num_examples: 5000
download_size: 969379
dataset_size: 2462261
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
CVPR2024/CVPR2024-papers-abstract-index | CVPR2024 | "2024-06-16T22:29:52Z" | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | "2024-05-27T11:22:50Z" | ---
license: apache-2.0
---
|
RochatAI/ShareGPT-COIG | RochatAI | "2024-05-27T11:31:24Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:26:31Z" | ---
license: apache-2.0
dataset_info:
features:
- name: messages
list:
- name: from
dtype: string
- name: value
dtype: string
- name: system
dtype: string
splits:
- name: train
num_bytes: 281928865
num_examples: 275985
download_size: 127001629
dataset_size: 281928865
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
The original data is from https://huggingface.co/datasets/BAAI/COIG. Format the original data to ShareGPT format.
|
DT4LM/sst2_adversarial_training | DT4LM | "2024-05-27T11:26:47Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:26:43Z" | ---
dataset_info:
features:
- name: sentence
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 361083.9155290884
num_examples: 5457
download_size: 227440
dataset_size: 361083.9155290884
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.37_tag | rakshya34 | "2024-05-27T12:24:15Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:31:10Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
splits:
- name: train
num_bytes: 2463033
num_examples: 5000
download_size: 976268
dataset_size: 2463033
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mesolitica/google-image-malaysia-location-dedup | mesolitica | "2024-05-28T09:49:54Z" | 0 | 0 | [
"task_categories:image-feature-extraction",
"region:us"
] | [
"image-feature-extraction"
] | "2024-05-27T11:34:15Z" | ---
task_categories:
- image-feature-extraction
---
# Google Image Malaysia Location Dedup
Original dataset https://huggingface.co/datasets/malaysia-ai/crawl-google-image-malaysia-location
Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/vlm/dedup-malaysia-location
## Dedup 50% similar
[dedup-0.5.jsonl](dedup-0.5.jsonl), total deduped 227937 images,
```
{'filename': 'train-00812-of-01000.parquet',
'keyword': 'Taman Megah Jaya Ayer Tawar',
'no': 16,
'selected_indices': [2556, 2559, 2575, 2577, 2586, 2587, 2595]}
```
## Dedup 60% similar
[dedup-0.6.jsonl](dedup-0.6.jsonl), total deduped 487301 images,
```
{'filename': 'train-00404-of-01000.parquet',
'keyword': 'Kampung Tok Wan Nik Padang Besar',
'no': 92,
'selected_indices': [2100, 2102, 2103, 2104]}
```
- `filename` is the parquet file from the original repository.
- `selected_indices` is the index of dataframe of that filename.
## Embedding
We convert to embedding using https://huggingface.co/google/siglip-base-patch16-512, we use MosaicML for faster indexing,
```python
from streaming import MDSWriter
from streaming.base.format.mds.encodings import Encoding, _encodings
from streaming import LocalDataset
import streaming
import numpy as np
from tqdm import tqdm
class Float32(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.float32)
_encodings['float32'] = Float32
dataset = LocalDataset('embedding')
``` |
Kuvvi/dataandmodel | Kuvvi | "2024-05-27T11:35:31Z" | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | "2024-05-27T11:35:30Z" | ---
license: apache-2.0
---
|
rakshya34/filtered_voice_english_v1.38_tag | rakshya34 | "2024-05-27T11:39:31Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:39:30Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: float64
- name: phonemes
dtype: string
splits:
- name: train
num_bytes: 1980168
num_examples: 5000
download_size: 903378
dataset_size: 1980168
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
DuongTrongChi/thanos | DuongTrongChi | "2024-05-30T03:15:10Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:42:10Z" | ---
dataset_info:
features:
- name: category
dtype: string
- name: category_id
dtype: int64
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 114839.29571428572
num_examples: 631
download_size: 48916
dataset_size: 114839.29571428572
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
anonydass/finetuning_demo | anonydass | "2024-05-27T11:44:49Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:44:48Z" | ---
dataset_info:
features:
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 2045
num_examples: 4
download_size: 3386
dataset_size: 2045
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
philipp-zettl/GGU-xx | philipp-zettl | "2024-06-17T10:00:17Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:51:00Z" | ---
dataset_info:
features:
- name: sample
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 39382
num_examples: 1049
download_size: 20576
dataset_size: 39382
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
deboleen6/telugu_OpenSLR | deboleen6 | "2024-05-27T11:56:22Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:51:42Z" | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: speaker_id
dtype: string
splits:
- name: train
num_bytes: 603118861.488
num_examples: 4448
download_size: 466007876
dataset_size: 603118861.488
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
TerminatorJ/PDB_Ribonanzanet | TerminatorJ | "2024-05-29T10:41:30Z" | 0 | 0 | [
"license:mit",
"size_categories:n<1K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:51:54Z" | ---
license: mit
configs:
- config_name: default
data_files:
- split: train
path: train.csv
- split: test
path: test.csv
- split: validation
path: val.csv
---
|
DokHee/FT | DokHee | "2024-05-27T12:22:43Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:52:01Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 4734
num_examples: 10
download_size: 6824
dataset_size: 4734
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
SenseLLM/ReflectionSeq-DS | SenseLLM | "2024-06-08T07:38:05Z" | 0 | 3 | [
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2405.17057",
"region:us",
"code"
] | [
"text-generation"
] | "2024-05-27T11:53:33Z" | ---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- code
pretty_name: reflection_seq_for_code_generation
size_categories:
- 10K<n<100K
---
## ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
<p align="center">
<a href="https://arxiv.org/abs/2405.17057">📄 Paper</a> •
<a href="https://github.com/SenseLLM/ReflectionCoder">🏠 Repo</a> •
<a href="https://huggingface.co/SenseLLM/ReflectionCoder-DS-33B">🤖 Models</a> •
<a href="https://huggingface.co/datasets/SenseLLM/ReflectionSeq-GPT">📚 Datasets </a>
</p>
## Introduction
ReflectionCoder is a novel approach that effectively leverages reflection sequences constructed by integrating compiler feedback to improve one-off code generation performance. Please refer to our paper and repo for more details!
![](method.png)
<hr>
## Models
| Model | Checkpoint | Size | HumanEval (+) | MBPP (+) | License|
|:-------|:------------|:------|:---------------|:----------|:--------|
| ReflectionCoder-CL-7B | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-CL-7B) | 7B | 75.0 (68.9) | 72.2 (61.4) | [Llama2](https://ai.meta.com/llama/license/) |
| ReflectionCoder-CL-34B | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-CL-34B) | 34B | 70.7 (66.5) | 68.4 (56.6) | [Llama2](https://ai.meta.com/llama/license/) |
| ReflectionCoder-DS-6.7B | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-DS-6.7B) | 6.7B | 80.5 (74.4) | 81.5 (69.6) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
| ReflectionCoder-DS-33B | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-DS-33B) | 33B | 82.9 (76.8) | 84.1 (72.0) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
## Datasets
| Dataset | Link | License |
|:-------------------|:----------------|:----------------------------------------------|
| ReflectionSeq-GPT | 🤗 [HF Link](https://huggingface.co/datasets/SenseLM/ReflectionSeq-GPT) | [License](LICENSE) |
| ReflectionSeq-DS | 🤗 [HF Link](https://huggingface.co/datasets/SenseLM/ReflectionSeq-DS) | [License](LICENSE) |
## How to Use
#### Chat Format
Following chat templates of most models, we use two special tokens to wrap the message of user and assistant, *i.e.*, ``<|user|>``, ``<|assistant|>``, and ``<|endofmessage|>``. Furthermore, we use two special tokens to wrap the content of different blocks, *i.e.*, ``<|text|>`` and ``<|endofblock|>``. You can use the following template to prompt our ReflectionCoder.
```python
<|user|><|text|>
Your Instruction
<|endofblock|><|endofmessage|><|assistant|>
```
#### Inference Code
Please refer to our GitHub Repo [need update](https://ai.meta.com/llama/license/) for more technical details.
## Citation
If you find this repo useful for your research, please kindly cite our paper:
```
@misc{ren2024reflectioncoder,
title={ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation},
author={Houxing Ren and Mingjie Zhan and Zhongyuan Wu and Aojun Zhou and Junting Pan and Hongsheng Li},
year={2024},
eprint={2405.17057},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
## Acknowledgments
We thank the following amazing projects that truly inspired us:
- [CodeLlama](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/)
- [DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder)
- [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder)
- [Evol-CodeAlpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
- [MagiCoder](https://github.com/ise-uiuc/magicoder/tree/main)
- [EvalPlus](https://github.com/evalplus/evalplus)
- [OpenCoderInterpreter](https://github.com/OpenCodeInterpreter/OpenCodeInterpreter/tree/main) |
mfrx/electrocity | mfrx | "2024-05-27T11:56:44Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T11:55:51Z" | ---
license: apache-2.0
---
|
realbenpope/PERSUADE_manageable | realbenpope | "2024-05-27T12:47:22Z" | 0 | 0 | [
"task_categories:text-classification",
"task_categories:feature-extraction",
"task_categories:zero-shot-classification",
"language:en",
"license:mit",
"size_categories:100K<n<1M",
"region:us",
"education",
"writing"
] | [
"text-classification",
"feature-extraction",
"zero-shot-classification"
] | "2024-05-27T12:18:38Z" | ---
license: mit
task_categories:
- text-classification
- feature-extraction
- zero-shot-classification
language:
- en
pretty_name: PERSUADE manageable
tags:
- education
- writing
size_categories:
- 100K<n<1M
---
# PERSUADE_manageable
This is a more space efficient version of the [PERSUADE dataset](https://the-learning-agency-lab.com/learning-exchange/persuade-dataset/) with the full_text split into a second file, reducing it from 750mb to 130mb Everything else remains the same. |
Magneto/CustomPhi3VisionData_v3 | Magneto | "2024-05-27T12:45:55Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T12:20:13Z" | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: pixel_values
sequence:
sequence:
sequence:
sequence: float64
splits:
- name: train
num_bytes: 122737772355
num_examples: 2660
download_size: 20100863583
dataset_size: 122737772355
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
gingercake01/240527STT_audio_noise_2930samples | gingercake01 | "2024-05-27T13:51:45Z" | 0 | 0 | [
"license:mit",
"size_categories:1K<n<10K",
"format:parquet",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T12:28:28Z" | ---
license: mit
dataset_info:
features:
- name: input_features
sequence:
sequence: float32
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 2251399480
num_examples: 2344
- name: test
num_bytes: 281425736
num_examples: 293
- name: valid
num_bytes: 281424000
num_examples: 293
download_size: 728396086
dataset_size: 2814249216
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
---
|
opelumen/tai_0001 | opelumen | "2024-05-27T20:25:45Z" | 0 | 0 | [
"license:mit",
"size_categories:n<1K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T12:31:51Z" | ---
license: mit
---
|
fine-tuned/BAAI_bge-m3-27052024-w9t8-webapp | fine-tuned | "2024-05-27T12:41:16Z" | 0 | 0 | [
"task_categories:feature-extraction",
"task_categories:sentence-similarity",
"language:fr",
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"mteb",
"Intimate",
"Care",
"Hygiene",
"Products",
"Health"
] | [
"feature-extraction",
"sentence-similarity"
] | "2024-05-27T12:41:16Z" | ---
license: apache-2.0
task_categories:
- feature-extraction
- sentence-similarity
language:
- fr
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Intimate
- Care
- Hygiene
- Products
- Health
pretty_name: e-commerce search for intimate care products
size_categories:
- n<1K
---
# BAAI_bge-m3-27052024-w9t8-webapp Dataset
## Dataset Description
The dataset "e-commerce search for intimate care products" is a generated dataset designed to support the development of domain specific embedding models for retrieval tasks.
## Associated Model
This dataset was used to train the [**BAAI_bge-m3-27052024-w9t8-webapp**](https://huggingface.co/fine-tuned/BAAI_bge-m3-27052024-w9t8-webapp) model.
## How to Use
To use this dataset for model training or evaluation, you can load it using the Hugging Face `datasets` library as follows:
```python
from datasets import load_dataset
dataset = load_dataset("fine-tuned/BAAI_bge-m3-27052024-w9t8-webapp")
print(dataset['test'][0])
```
|
llmem/conversation_alpha_01 | llmem | "2024-05-27T12:57:11Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T12:47:48Z" | ---
dataset_info:
features:
- name: conversation
dtype: string
- name: session
dtype: int64
splits:
- name: train
num_bytes: 25375
num_examples: 9
download_size: 18291
dataset_size: 25375
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Yukify/finetune-llama3-for-smp-regpart-3-shot | Yukify | "2024-05-27T12:48:52Z" | 0 | 0 | [
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T12:48:36Z" | ---
license: apache-2.0
---
|
MAPS-research/GelRec_images_1 | MAPS-research | "2024-06-18T16:39:48Z" | 0 | 0 | [
"task_categories:text-to-image",
"language:en",
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | [
"text-to-image"
] | "2024-05-27T12:57:55Z" | ---
dataset_info:
features:
- name: image
dtype: image
- name: base_model
dtype: string
- name: model_id
dtype: float64
- name: model_name
dtype: string
- name: modelVersion_id
dtype: int64
- name: modelVersion_name
dtype: string
- name: lora_scale
dtype: float64
- name: prompt_id
dtype: int64
- name: prompt
dtype: string
- name: negative_prompt
dtype: string
- name: seed
dtype: int64
splits:
- name: train
num_bytes: 10894595130.6
num_examples: 8040
download_size: 11006254884
dataset_size: 10894595130.6
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-to-image
language:
- en
---
**Images Generated by Different LoRA and Prompts**
- **Prompt IDs**: 2, 16, 42, 51
- **Number of Models per Prompt**: 10
- **Number of Images per Model**: 201
- **Seed Range**: [0, 500, 10000, ..., 100000]
- **Base Model**: SDXL 1.0 |
QHQK/conversation_hall_completion_v2 | QHQK | "2024-05-29T12:29:55Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:01:12Z" | ---
dataset_info:
features:
- name: question_id
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: choice_a
dtype: string
- name: choice_b
dtype: string
- name: choice_c
dtype: string
- name: choice_d
dtype: string
- name: image_source
dtype: string
- name: image
dtype: image
- name: category
dtype: string
splits:
- name: test
num_bytes: 93269630.25
num_examples: 1270
download_size: 38010954
dataset_size: 93269630.25
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
|
dimitarpg13/DIS5K | dimitarpg13 | "2024-05-27T14:54:04Z" | 0 | 0 | [
"license:openrail",
"modality:image",
"region:us"
] | null | "2024-05-27T13:06:18Z" | ---
license: openrail
---
|
alexandreteles/fama_fraternitatis_multiturn | alexandreteles | "2024-05-27T14:14:52Z" | 0 | 0 | [
"task_categories:text-generation",
"language:en",
"license:c-uda",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/2325",
"region:us",
"spirituality",
"occultism",
"esoterism"
] | [
"text-generation"
] | "2024-05-27T13:09:34Z" | ---
license: c-uda
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 233932
num_examples: 112
download_size: 74302
dataset_size: 233932
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-generation
language:
- en
tags:
- spirituality
- occultism
- esoterism
pretty_name: Fama Fraternitatis Rosae Crucis (multiturn)
size_categories:
- n<1K
---
# Fama Fraternitatis Rosae Crucis Multiturn Conversation Dataset
## Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of the "Fama Fraternitatis." The text, known for its deep allegorical content, serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
## Objective
The primary objective of this dataset is to facilitate the development and testing of AI models specialized in understanding and generating responses grounded in esoteric philosophy. By providing a rich set of dialogues based on the "Fama Fraternitatis," the dataset aims to promote deeper intellectual engagement with historic philosophical texts and their contemporary relevance in esoteric studies.
## Access
The dataset is available under the [c-uda](https://github.com/microsoft/Computational-Use-of-Data-Agreement/blob/master/C-UDA-1.0.md) license, intended for educational and research purposes..
## Contribution
Contributions to the dataset are welcome, especially those that expand the depth and range of philosophical inquiries. |
mogoi/re_01_12 | mogoi | "2024-05-27T13:19:49Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:12:15Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 211177
num_examples: 1950
download_size: 14273
dataset_size: 211177
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_01_34 | mogoi | "2024-05-27T13:20:05Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:12:26Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 218985
num_examples: 1950
download_size: 17681
dataset_size: 218985
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_03_12 | mogoi | "2024-05-27T13:20:35Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:12:43Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 222694
num_examples: 1950
download_size: 22232
dataset_size: 222694
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_03_345 | mogoi | "2024-05-27T13:20:50Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:12:54Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 332241
num_examples: 2850
download_size: 32900
dataset_size: 332241
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
coatedincrimson/LeedoONEUS | coatedincrimson | "2024-05-27T13:18:08Z" | 0 | 0 | [
"license:openrail",
"region:us"
] | null | "2024-05-27T13:16:26Z" | ---
license: openrail
---
|
Farjfar/SGS-ukpolitics-train | Farjfar | "2024-05-27T13:20:37Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:20:33Z" | ---
dataset_info:
features:
- name: body_cleaned
dtype: string
- name: id
dtype: string
- name: subreddit
dtype: string
- name: year
dtype: int64
- name: annotation1
dtype: string
- name: annotation2
dtype: string
- name: gold_annotation
dtype: string
- name: bio_annotation
sequence: string
- name: ids
sequence: int64
- name: tokenized_body_cleaned
sequence: string
- name: continuation
dtype: string
- name: first_two_sentences
dtype: string
- name: continuation_tokenized
sequence: string
- name: tokenized_length
dtype: int64
- name: ids_continuation
sequence: int64
splits:
- name: train
num_bytes: 2564526
num_examples: 401
download_size: 900565
dataset_size: 2564526
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_06_13 | mogoi | "2024-05-27T13:22:16Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:21:19Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 185521
num_examples: 1650
download_size: 16301
dataset_size: 185521
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_06_2 | mogoi | "2024-05-27T13:22:25Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:21:27Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 118638
num_examples: 1050
download_size: 13424
dataset_size: 118638
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_08_12 | mogoi | "2024-05-27T13:22:43Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:21:46Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 178965
num_examples: 1650
download_size: 16447
dataset_size: 178965
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mogoi/re_08_34 | mogoi | "2024-05-27T13:22:54Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:21:53Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 222176
num_examples: 1950
download_size: 19822
dataset_size: 222176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
QHQK/description_hall_completion_v2 | QHQK | "2024-05-29T12:28:23Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:23:47Z" | ---
dataset_info:
features:
- name: question_id
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: choice_a
dtype: string
- name: choice_b
dtype: string
- name: choice_c
dtype: string
- name: choice_d
dtype: string
- name: image_source
dtype: string
- name: image
dtype: image
- name: category
dtype: string
splits:
- name: test
num_bytes: 70464191.0
num_examples: 879
download_size: 44010036
dataset_size: 70464191.0
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
|
mbiarreta/MariposasClasif | mbiarreta | "2024-05-27T13:32:54Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:24:07Z" | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Anartia jatrophae
'1': Caligo atreus
'2': Danaus plexippus
'3': Dryas iulia
'4': Siproeta stelenes
splits:
- name: train
num_bytes: 194810357.178
num_examples: 1842
- name: validation
num_bytes: 22775122.0
num_examples: 208
- name: test
num_bytes: 54352736.0
num_examples: 515
download_size: 273069690
dataset_size: 271938215.178
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
ttgroup/blueneg-release | ttgroup | "2024-06-14T04:06:41Z" | 0 | 0 | [
"license:other",
"modality:image",
"doi:10.57967/hf/2551",
"region:us",
"negative film",
"printed photo",
"high dynamic range",
"ultra-high resolution",
"image restoration"
] | null | "2024-05-27T13:26:06Z" | ---
license: other
license_name: license.txt
license_link: LICENSE
tags:
- negative film
- printed photo
- high dynamic range
- ultra-high resolution
- image restoration
pretty_name: BlueNeg Dataset
---
# BlueNeg: A 35mm Negative Film Dataset for Restoring Channel-Heterogeneous Deterioration
## Description
This set of images is collected for studying the research problem of restoring the corrupted negative films. Due to the physical nature of negative film, the red, green, and blue light-sensitive layers are located differently inside the negative film. Therefore, the rates of deterioration of these three layers are different. Tien-Tsin Wong found that the blue channel is relatively vulnerable compared to the other two channels. Because the blue light-sensitive layer is on the outermost layer on the emulsion side. That is, the deterioration rates are heterogeneous. This characteristic is inherited from its ancestor, i.e., storing the three color negatives (R, G, B) on three separate glass plates by Prokudin-Gorsky.
Since the blue channel is more vulnerable and the other two channels are relatively well-preserved, this means we can restore the blue channel by exploiting the retained information from the red and green channels to restore the color photograph. This is especially sound with
the latest AI technologies. Unfortunately, most existing photo restoration techniques are developed based on printed photographs, in which the nature of deterioration is different from that of the negatives. This is why this dataset is created.
## Data Information
<table style="border-collapse:collapse;border-spacing:0" class="tg"><thead>
<tr><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Data Source</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Partition</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Number</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Folder</th>
<th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Bits per channel</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Resolution (may varies)</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">File extension</th><th style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;font-weight:bold;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Public</th></tr>
</thead>
<tbody>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Negative films</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">297</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">negative-16bit</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">16</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">10,128 x 6,840</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">dng</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Yes</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-intact</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">194</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Printed photo</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">247</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">printed-16bit</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">16</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">2,994 x 1,920</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">tif</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Yes</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-intact</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">151</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Negative preview (after negation)</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">297</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">negative-preview-8bit</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">8</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">1,322 x 892</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">preview.png</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal" rowspan="2">Yes</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-intact</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">194</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Pseudo ground truth</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">247</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">pseudogt-8bit</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">8</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">< 1,322 x 892</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">pseudogt.png</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Yes</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Printed photo (testset)</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">30</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">-</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">16</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">2,994 x 1,920</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">tif</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">No</td></tr>
<tr><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">Pseudo ground truth (testset)</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">blue-corrupted</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">30</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">-</td>
<td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">8</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">< 1,322 x 892</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">pseudogt.png</td><td style="border-color:inherit;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;overflow:hidden;padding:10px 5px;text-align:center;vertical-align:top;word-break:normal">No</td></tr>
</tbody></table>
## Meta Information
The meta information is stored in the `meta.json` and `transformations.pkl`. The meta information includes the following fields:
- `meta.json`
- filename
- partition
- is_testset
- date
- roll_id
- number_in_roll
- location
- geo_location
- film_type
- negative_path
- printed_path
- preview_path
- pseudogt_path
- scene_property
- is_indoor
- is_daytime
- `transformations.pkl`: a python dict using filename (without extension) as key, and the value is a dict with the following fields:
- matrix: the perspective projection matrix to warp the printed photo to the negative preview
- bbox: the bounding box of the warped printed photo in the negative preview; the bounding box is in the format of [x0, y0, x1, y1], preview[y0:y1, x0:x1, :] has the same size as pseudo ground truth
## Naming Convention
`YYYYMMDD[R]-NN-NAME.EXT`
- `YYYYMMDD`: The date when the photo was taken (might not always be accurate, but roughly correct).
- `[R]`: the roll number, if available
- `NN`: the photo number in the roll
- `NAME`: the photo's name, usually the location or the subject of the photo.
- `EXT`: the file extension, e.g., `.dng`, `.tif`, `.preview.png`, `.pseudogt.png`, etc.
## License
Our license shares the same spirit with the [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/). However, please note that our license is not CC-BY 4.0. Please check the LICENSE file for more details.
```
All photos are owned and copyrighted by Tien-Tsin Wong. You are
automatically granted with permission to use the images for academic
and commerical usages, provided that the image credit
"Copyrighted by Tien-Tsin Wong" is included in any forms of
publication, reproduction, redistribution, or derivatives of the images.
```
## Citation
If you find the dataset is useful to you, please also cite our publication below in your work/publication.
- Hanyuan Liu, Chengze Li, Minshan Xie, Zhenni Wang, Jiawen Liang, Chi-Sing Leung, and Tien-Tsin Wong,
"BlueNeg: BlueNeg: A 35mm Negative Film Dataset for Restoring Channel-Heterogeneous Deterioration",
arXiv preprint, 2024.
```bibtex
@misc{blueneg,
title={BlueNeg: A 35mm Negative Film Dataset for Restoring Channel-Heterogeneous Deterioration},
author={Hanyuan Liu and Chengze Li and Minshan Xie and Zhenni Wang and Jiawen Liang and Chi-Sing Leung and and Tien-Tsin Wong},
year={2024},
eprint={to be updated},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
``` |
rexching/dataset_0001 | rexching | "2024-05-27T13:26:57Z" | 0 | 0 | [
"format:parquet",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:26:54Z" | ---
dataset_info:
features: []
splits:
- name: train
num_bytes: 0
num_examples: 0
download_size: 324
dataset_size: 0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
haixuantao/just_gripper_eval_3 | haixuantao | "2024-05-27T13:38:21Z" | 0 | 0 | [
"license:mit",
"region:us"
] | null | "2024-05-27T13:37:30Z" | ---
license: mit
dataset_info:
features:
- name: index
dtype: int64
- name: observation.images.cam_right_wrist
dtype: video_frame
- name: observation.images.cam_high
dtype: video_frame
- name: observation.state
sequence: float32
length: 14
- name: observation.images.cam_left_wrist
dtype: video_frame
- name: action
sequence: float32
length: 14
- name: episode_index
dtype: int64
- name: observation.images.cam_low
dtype: video_frame
- name: frame_index
dtype: int64
- name: next.done
dtype: bool
- name: timestamp
dtype: float32
splits:
- name: train
num_bytes: 475350
num_examples: 1200
download_size: 162171
dataset_size: 475350
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
ByungJoo/custom_dataset | ByungJoo | "2024-05-27T14:15:03Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:49:22Z" | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1908
num_examples: 16
download_size: 1771
dataset_size: 1908
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
NCube/europa-random-split | NCube | "2024-06-03T02:58:36Z" | 0 | 0 | [
"language:fr",
"language:de",
"language:en",
"language:it",
"language:nl",
"language:el",
"language:da",
"language:pt",
"language:es",
"language:sv",
"language:fi",
"language:lt",
"language:et",
"language:cs",
"language:hu",
"language:lv",
"language:sl",
"language:pl",
"language:mt",
"language:sk",
"language:ro",
"language:bg",
"language:hr",
"language:ga",
"license:mit",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2403.00252",
"region:us",
"keyphrase-generation",
"text-to-text",
"legal"
] | null | "2024-05-27T13:51:17Z" | ---
language:
- fr
- de
- en
- it
- nl
- el
- da
- pt
- es
- sv
- fi
- lt
- et
- cs
- hu
- lv
- sl
- pl
- mt
- sk
- ro
- bg
- hr
- ga
license: mit
size_categories:
- 100K<n<1M
pretty_name: Europa Random Split
dataset_info:
features:
- name: celex_id
dtype: string
- name: lang
dtype: string
- name: input_text
dtype: string
- name: keyphrases
sequence: string
splits:
- name: train
num_bytes: 6405779590
num_examples: 159306
- name: valid
num_bytes: 2182262528
num_examples: 53943
- name: test
num_bytes: 2853853947
num_examples: 71708
download_size: 5183354316
dataset_size: 11441896065
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
tags:
- keyphrase-generation
- text-to-text
- legal
---
# Dataset Card for EUROPA
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
EUROPA is a dataset designed for training and evaluating multilingual keyphrase generation models in the legal domain. It consists of legal judgments from the Court of Justice of the European Union (EU) and includes instances in all 24 official EU languages.
**Key Features**:
**Multilingual:** Covers 24 official EU languages.
**Domain-Specific:** Focuses on legal documents.
**Source:** Derived from Court of Justice of the European Union judgments.
- **Curated by:** N3 team
- **Languages:** French, German, English, Italian, Dutch, Greek, Danish, Portuguese, Spanish, Swedish, Finnish, Lithuanian, Estonian, Czech, Hungarian, Latvian, Slovenian, Polish, Maltese, Slovak, Romanian, Bulgarian, Croatian, Irish
- **License:** MIT License
### Dataset Sources
- **Paper:** https://arxiv.org/abs/2403.00252
## Dataset Structure
- **celex_id:** CELEX identifier inherited from CJEU. Different translated versions of the same judgment share the same celex_id. If you wish to have a unique identifier for each instance, you can concatenate `lang` and `celex_id` values;
- **lang:** ISO 639-1 language code;
- **input:** judgment transcription or translation;
- **keyphrases:** reference keyphrases drafted by the CJEU.
This page presents an randomly split version of the dataset, thus allowing all sets to have the same distribution in terms of vocabulary and languages. More details can be found in Appendix H of our paper.
- **training set**: 159 306 instances;
- **validation set**: 53 943 instances;
- **test set**: 71 708 instances.
## Citation
```
@article{salaun2024europa,
title={EUROPA: A Legal Multilingual Keyphrase Generation Dataset},
author={Sala{\"u}n, Olivier and Piedboeuf, Fr{\'e}d{\'e}ric and Le Berre, Guillaume and Hermelo, David Alfonso and Langlais, Philippe},
journal={arXiv preprint arXiv:2403.00252},
year={2024}
}
``` |
nhyha/QA-Dataset | nhyha | "2024-05-28T09:25:51Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T13:57:51Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 20409
num_examples: 30
download_size: 14672
dataset_size: 20409
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
gurdeep101/mini-platypus | gurdeep101 | "2024-05-28T14:20:34Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:02:50Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 4186564
num_examples: 1000
download_size: 2245921
dataset_size: 4186564
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
Filtered version of mini platypus dataset created as a part of code along tutorial from databricks here
https://www.datacamp.com/code-along/fine-tuning-your-own-llama-2-model
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
alexandreteles/chymical_wedding_of_christian_rosenkreutz_multiturn | alexandreteles | "2024-05-27T18:10:41Z" | 0 | 0 | [
"task_categories:text-generation",
"language:en",
"license:c-uda",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/2326",
"region:us",
"spirituality",
"occultism",
"esoterism"
] | [
"text-generation"
] | "2024-05-27T14:06:58Z" | ---
license: c-uda
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 963095
num_examples: 528
download_size: 367520
dataset_size: 963095
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-generation
language:
- en
tags:
- spirituality
- occultism
- esoterism
size_categories:
- n<1K
pretty_name: The Chymical Wedding of Christian Rosenkreutz (multiturn)
---
# The Chymical Wedding of Christian Rosenkreutz Multiturn Conversation Dataset
## Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of "The Chymical Wedding of Christian Rosenkreutz." The text, known for its deep allegorical content, serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
## Objective
The primary objective of this dataset is to facilitate the development and testing of AI models specialized in understanding and generating responses grounded in esoteric philosophy. By providing a rich set of dialogues based on "The Chymical Wedding of Christian Rosenkreutz," the dataset aims to promote deeper intellectual engagement with historic philosophical texts and their contemporary relevance in esoteric studies.
## Access
The dataset is available under the [c-uda](https://github.com/microsoft/Computational-Use-of-Data-Agreement/blob/master/C-UDA-1.0.md) license, intended for educational and research purposes..
## Contribution
Contributions to the dataset are welcome, especially those that expand the depth and range of philosophical inquiries. |
fresvyx/alpaca2-imam | fresvyx | "2024-05-27T14:07:53Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:07:49Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 2580358
num_examples: 1000
download_size: 1367091
dataset_size: 2580358
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental | OALL | "2024-05-27T14:09:25Z" | 0 | 0 | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:09:15Z" | ---
pretty_name: Evaluation run of Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental](https://huggingface.co/Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental).\n\
\nThe dataset is composed of 136 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.\n\nTo load the details from a run, you can for instance do the following:\n\
```python\nfrom datasets import load_dataset\ndata = load_dataset(\"OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental\"\
,\n\t\"lighteval_xstory_cloze_ar_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2024-05-27T14:06:39.187751](https://huggingface.co/datasets/OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental/blob/main/results_2024-05-27T14-06-39.187751.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_norm\": 0.4253986985051422,\n\
\ \"acc_norm_stderr\": 0.0384347707626982,\n \"acc\": 0.5956320317670417,\n\
\ \"acc_stderr\": 0.012629580396570928\n },\n \"community|acva:Algeria|0\"\
: {\n \"acc_norm\": 0.5743589743589743,\n \"acc_norm_stderr\": 0.03549871080367707\n\
\ },\n \"community|acva:Ancient_Egypt|0\": {\n \"acc_norm\": 0.10158730158730159,\n\
\ \"acc_norm_stderr\": 0.01704876125499024\n },\n \"community|acva:Arab_Empire|0\"\
: {\n \"acc_norm\": 0.4377358490566038,\n \"acc_norm_stderr\": 0.030533338430467512\n\
\ },\n \"community|acva:Arabic_Architecture|0\": {\n \"acc_norm\":\
\ 0.47692307692307695,\n \"acc_norm_stderr\": 0.0358596530894741\n },\n\
\ \"community|acva:Arabic_Art|0\": {\n \"acc_norm\": 0.39487179487179486,\n\
\ \"acc_norm_stderr\": 0.03509545602262037\n },\n \"community|acva:Arabic_Astronomy|0\"\
: {\n \"acc_norm\": 0.49230769230769234,\n \"acc_norm_stderr\": 0.03589365940635213\n\
\ },\n \"community|acva:Arabic_Calligraphy|0\": {\n \"acc_norm\": 0.5294117647058824,\n\
\ \"acc_norm_stderr\": 0.03131846503821582\n },\n \"community|acva:Arabic_Ceremony|0\"\
: {\n \"acc_norm\": 0.5351351351351351,\n \"acc_norm_stderr\": 0.03676936950948699\n\
\ },\n \"community|acva:Arabic_Clothing|0\": {\n \"acc_norm\": 0.4717948717948718,\n\
\ \"acc_norm_stderr\": 0.035840746749208334\n },\n \"community|acva:Arabic_Culture|0\"\
: {\n \"acc_norm\": 0.2564102564102564,\n \"acc_norm_stderr\": 0.031349709942744934\n\
\ },\n \"community|acva:Arabic_Food|0\": {\n \"acc_norm\": 0.46153846153846156,\n\
\ \"acc_norm_stderr\": 0.03579154352544571\n },\n \"community|acva:Arabic_Funeral|0\"\
: {\n \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.050529115263991134\n\
\ },\n \"community|acva:Arabic_Geography|0\": {\n \"acc_norm\": 0.6344827586206897,\n\
\ \"acc_norm_stderr\": 0.04013124195424386\n },\n \"community|acva:Arabic_History|0\"\
: {\n \"acc_norm\": 0.3641025641025641,\n \"acc_norm_stderr\": 0.0345465386778639\n\
\ },\n \"community|acva:Arabic_Language_Origin|0\": {\n \"acc_norm\"\
: 0.6,\n \"acc_norm_stderr\": 0.050529115263991134\n },\n \"community|acva:Arabic_Literature|0\"\
: {\n \"acc_norm\": 0.496551724137931,\n \"acc_norm_stderr\": 0.041665675771015785\n\
\ },\n \"community|acva:Arabic_Math|0\": {\n \"acc_norm\": 0.40512820512820513,\n\
\ \"acc_norm_stderr\": 0.03524577495610961\n },\n \"community|acva:Arabic_Medicine|0\"\
: {\n \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.041546596717075474\n\
\ },\n \"community|acva:Arabic_Music|0\": {\n \"acc_norm\": 0.23741007194244604,\n\
\ \"acc_norm_stderr\": 0.036220593237998276\n },\n \"community|acva:Arabic_Ornament|0\"\
: {\n \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.03384487217112065\n\
\ },\n \"community|acva:Arabic_Philosophy|0\": {\n \"acc_norm\": 0.5310344827586206,\n\
\ \"acc_norm_stderr\": 0.04158632762097828\n },\n \"community|acva:Arabic_Physics_and_Chemistry|0\"\
: {\n \"acc_norm\": 0.5333333333333333,\n \"acc_norm_stderr\": 0.03581804596782232\n\
\ },\n \"community|acva:Arabic_Wedding|0\": {\n \"acc_norm\": 0.6205128205128205,\n\
\ \"acc_norm_stderr\": 0.03483959266365359\n },\n \"community|acva:Bahrain|0\"\
: {\n \"acc_norm\": 0.37777777777777777,\n \"acc_norm_stderr\": 0.07309112127323451\n\
\ },\n \"community|acva:Comoros|0\": {\n \"acc_norm\": 0.4444444444444444,\n\
\ \"acc_norm_stderr\": 0.07491109582924915\n },\n \"community|acva:Egypt_modern|0\"\
: {\n \"acc_norm\": 0.5684210526315789,\n \"acc_norm_stderr\": 0.05108592673308946\n\
\ },\n \"community|acva:InfluenceFromAncientEgypt|0\": {\n \"acc_norm\"\
: 0.5384615384615384,\n \"acc_norm_stderr\": 0.0357915435254457\n },\n\
\ \"community|acva:InfluenceFromByzantium|0\": {\n \"acc_norm\": 0.7172413793103448,\n\
\ \"acc_norm_stderr\": 0.037528339580033376\n },\n \"community|acva:InfluenceFromChina|0\"\
: {\n \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.03174930436412669\n\
\ },\n \"community|acva:InfluenceFromGreece|0\": {\n \"acc_norm\":\
\ 0.6461538461538462,\n \"acc_norm_stderr\": 0.03433004254147036\n },\n\
\ \"community|acva:InfluenceFromIslam|0\": {\n \"acc_norm\": 0.31724137931034485,\n\
\ \"acc_norm_stderr\": 0.038783523721386215\n },\n \"community|acva:InfluenceFromPersia|0\"\
: {\n \"acc_norm\": 0.7028571428571428,\n \"acc_norm_stderr\": 0.03464507889884372\n\
\ },\n \"community|acva:InfluenceFromRome|0\": {\n \"acc_norm\": 0.5743589743589743,\n\
\ \"acc_norm_stderr\": 0.03549871080367708\n },\n \"community|acva:Iraq|0\"\
: {\n \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.0521414859075246\n\
\ },\n \"community|acva:Islam_Education|0\": {\n \"acc_norm\": 0.4564102564102564,\n\
\ \"acc_norm_stderr\": 0.03576123096991215\n },\n \"community|acva:Islam_branches_and_schools|0\"\
: {\n \"acc_norm\": 0.4857142857142857,\n \"acc_norm_stderr\": 0.03788942763158507\n\
\ },\n \"community|acva:Islamic_law_system|0\": {\n \"acc_norm\": 0.4307692307692308,\n\
\ \"acc_norm_stderr\": 0.0355521325205876\n },\n \"community|acva:Jordan|0\"\
: {\n \"acc_norm\": 0.37777777777777777,\n \"acc_norm_stderr\": 0.07309112127323451\n\
\ },\n \"community|acva:Kuwait|0\": {\n \"acc_norm\": 0.3111111111111111,\n\
\ \"acc_norm_stderr\": 0.06979205927323111\n },\n \"community|acva:Lebanon|0\"\
: {\n \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.06267511942419626\n\
\ },\n \"community|acva:Libya|0\": {\n \"acc_norm\": 0.5111111111111111,\n\
\ \"acc_norm_stderr\": 0.07535922203472523\n },\n \"community|acva:Mauritania|0\"\
: {\n \"acc_norm\": 0.4888888888888889,\n \"acc_norm_stderr\": 0.07535922203472523\n\
\ },\n \"community|acva:Mesopotamia_civilization|0\": {\n \"acc_norm\"\
: 0.5806451612903226,\n \"acc_norm_stderr\": 0.03976361630387024\n },\n\
\ \"community|acva:Morocco|0\": {\n \"acc_norm\": 0.37777777777777777,\n\
\ \"acc_norm_stderr\": 0.0730911212732345\n },\n \"community|acva:Oman|0\"\
: {\n \"acc_norm\": 0.4222222222222222,\n \"acc_norm_stderr\": 0.07446027270295806\n\
\ },\n \"community|acva:Palestine|0\": {\n \"acc_norm\": 0.3764705882352941,\n\
\ \"acc_norm_stderr\": 0.052863310306265295\n },\n \"community|acva:Qatar|0\"\
: {\n \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.07385489458759965\n\
\ },\n \"community|acva:Saudi_Arabia|0\": {\n \"acc_norm\": 0.5435897435897435,\n\
\ \"acc_norm_stderr\": 0.03576123096991214\n },\n \"community|acva:Somalia|0\"\
: {\n \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.07385489458759965\n\
\ },\n \"community|acva:Sudan|0\": {\n \"acc_norm\": 0.4,\n \
\ \"acc_norm_stderr\": 0.07385489458759965\n },\n \"community|acva:Syria|0\"\
: {\n \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.07385489458759964\n\
\ },\n \"community|acva:Tunisia|0\": {\n \"acc_norm\": 0.26666666666666666,\n\
\ \"acc_norm_stderr\": 0.06666666666666665\n },\n \"community|acva:United_Arab_Emirates|0\"\
: {\n \"acc_norm\": 0.4823529411764706,\n \"acc_norm_stderr\": 0.054520483406618934\n\
\ },\n \"community|acva:Yemen|0\": {\n \"acc_norm\": 0.5,\n \
\ \"acc_norm_stderr\": 0.16666666666666666\n },\n \"community|acva:communication|0\"\
: {\n \"acc_norm\": 0.43131868131868134,\n \"acc_norm_stderr\": 0.02599443023962308\n\
\ },\n \"community|acva:computer_and_phone|0\": {\n \"acc_norm\": 0.45084745762711864,\n\
\ \"acc_norm_stderr\": 0.02901934773187137\n },\n \"community|acva:daily_life|0\"\
: {\n \"acc_norm\": 0.18694362017804153,\n \"acc_norm_stderr\": 0.021268948348414647\n\
\ },\n \"community|acva:entertainment|0\": {\n \"acc_norm\": 0.23389830508474577,\n\
\ \"acc_norm_stderr\": 0.024687839412166384\n },\n \"community|alghafa:mcq_exams_test_ar|0\"\
: {\n \"acc_norm\": 0.3303411131059246,\n \"acc_norm_stderr\": 0.01994668532793601\n\
\ },\n \"community|alghafa:meta_ar_dialects|0\": {\n \"acc_norm\":\
\ 0.3088044485634847,\n \"acc_norm_stderr\": 0.006290523225095885\n },\n\
\ \"community|alghafa:meta_ar_msa|0\": {\n \"acc_norm\": 0.3463687150837989,\n\
\ \"acc_norm_stderr\": 0.015913546784020117\n },\n \"community|alghafa:multiple_choice_facts_truefalse_balanced_task|0\"\
: {\n \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.05807730170189531\n\
\ },\n \"community|alghafa:multiple_choice_grounded_statement_soqal_task|0\"\
: {\n \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.04092881363092387\n\
\ },\n \"community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0\"\
: {\n \"acc_norm\": 0.4066666666666667,\n \"acc_norm_stderr\": 0.04024162665739063\n\
\ },\n \"community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0\"\
: {\n \"acc_norm\": 0.7697310819262039,\n \"acc_norm_stderr\": 0.004708744220539922\n\
\ },\n \"community|alghafa:multiple_choice_rating_sentiment_task|0\": {\n\
\ \"acc_norm\": 0.5296080066722268,\n \"acc_norm_stderr\": 0.006446869248966106\n\
\ },\n \"community|alghafa:multiple_choice_sentiment_task|0\": {\n \
\ \"acc_norm\": 0.3598837209302326,\n \"acc_norm_stderr\": 0.011576375321508726\n\
\ },\n \"community|arabic_exams|0\": {\n \"acc_norm\": 0.3780260707635009,\n\
\ \"acc_norm_stderr\": 0.020944238360403714\n },\n \"community|arabic_mmlu:abstract_algebra|0\"\
: {\n \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n\
\ },\n \"community|arabic_mmlu:anatomy|0\": {\n \"acc_norm\": 0.3851851851851852,\n\
\ \"acc_norm_stderr\": 0.042039210401562783\n },\n \"community|arabic_mmlu:astronomy|0\"\
: {\n \"acc_norm\": 0.4407894736842105,\n \"acc_norm_stderr\": 0.040403110624904356\n\
\ },\n \"community|arabic_mmlu:business_ethics|0\": {\n \"acc_norm\"\
: 0.58,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"community|arabic_mmlu:clinical_knowledge|0\"\
: {\n \"acc_norm\": 0.3886792452830189,\n \"acc_norm_stderr\": 0.03000048544867599\n\
\ },\n \"community|arabic_mmlu:college_biology|0\": {\n \"acc_norm\"\
: 0.3819444444444444,\n \"acc_norm_stderr\": 0.040629907841466674\n },\n\
\ \"community|arabic_mmlu:college_chemistry|0\": {\n \"acc_norm\": 0.25,\n\
\ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"community|arabic_mmlu:college_computer_science|0\"\
: {\n \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n\
\ },\n \"community|arabic_mmlu:college_mathematics|0\": {\n \"acc_norm\"\
: 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n },\n \"community|arabic_mmlu:college_medicine|0\"\
: {\n \"acc_norm\": 0.32947976878612717,\n \"acc_norm_stderr\": 0.03583901754736412\n\
\ },\n \"community|arabic_mmlu:college_physics|0\": {\n \"acc_norm\"\
: 0.27450980392156865,\n \"acc_norm_stderr\": 0.044405219061793254\n },\n\
\ \"community|arabic_mmlu:computer_security|0\": {\n \"acc_norm\": 0.5,\n\
\ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"community|arabic_mmlu:conceptual_physics|0\"\
: {\n \"acc_norm\": 0.34893617021276596,\n \"acc_norm_stderr\": 0.031158522131357756\n\
\ },\n \"community|arabic_mmlu:econometrics|0\": {\n \"acc_norm\":\
\ 0.3508771929824561,\n \"acc_norm_stderr\": 0.044895393502706986\n },\n\
\ \"community|arabic_mmlu:electrical_engineering|0\": {\n \"acc_norm\"\
: 0.46206896551724136,\n \"acc_norm_stderr\": 0.041546596717075474\n },\n\
\ \"community|arabic_mmlu:elementary_mathematics|0\": {\n \"acc_norm\"\
: 0.3333333333333333,\n \"acc_norm_stderr\": 0.024278568024307706\n },\n\
\ \"community|arabic_mmlu:formal_logic|0\": {\n \"acc_norm\": 0.31746031746031744,\n\
\ \"acc_norm_stderr\": 0.041634530313028585\n },\n \"community|arabic_mmlu:global_facts|0\"\
: {\n \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n\
\ },\n \"community|arabic_mmlu:high_school_biology|0\": {\n \"acc_norm\"\
: 0.3903225806451613,\n \"acc_norm_stderr\": 0.027751256636969576\n },\n\
\ \"community|arabic_mmlu:high_school_chemistry|0\": {\n \"acc_norm\"\
: 0.3645320197044335,\n \"acc_norm_stderr\": 0.0338640574606209\n },\n\
\ \"community|arabic_mmlu:high_school_computer_science|0\": {\n \"acc_norm\"\
: 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n },\n \"community|arabic_mmlu:high_school_european_history|0\"\
: {\n \"acc_norm\": 0.23636363636363636,\n \"acc_norm_stderr\": 0.03317505930009179\n\
\ },\n \"community|arabic_mmlu:high_school_geography|0\": {\n \"acc_norm\"\
: 0.3838383838383838,\n \"acc_norm_stderr\": 0.03464881675016338\n },\n\
\ \"community|arabic_mmlu:high_school_government_and_politics|0\": {\n \
\ \"acc_norm\": 0.38860103626943004,\n \"acc_norm_stderr\": 0.03517739796373134\n\
\ },\n \"community|arabic_mmlu:high_school_macroeconomics|0\": {\n \
\ \"acc_norm\": 0.37435897435897436,\n \"acc_norm_stderr\": 0.024537591572830503\n\
\ },\n \"community|arabic_mmlu:high_school_mathematics|0\": {\n \"\
acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.027309140588230175\n\
\ },\n \"community|arabic_mmlu:high_school_microeconomics|0\": {\n \
\ \"acc_norm\": 0.3319327731092437,\n \"acc_norm_stderr\": 0.030588697013783663\n\
\ },\n \"community|arabic_mmlu:high_school_physics|0\": {\n \"acc_norm\"\
: 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526731\n },\n\
\ \"community|arabic_mmlu:high_school_psychology|0\": {\n \"acc_norm\"\
: 0.381651376146789,\n \"acc_norm_stderr\": 0.020828148517022606\n },\n\
\ \"community|arabic_mmlu:high_school_statistics|0\": {\n \"acc_norm\"\
: 0.24537037037037038,\n \"acc_norm_stderr\": 0.029346665094372937\n },\n\
\ \"community|arabic_mmlu:high_school_us_history|0\": {\n \"acc_norm\"\
: 0.27450980392156865,\n \"acc_norm_stderr\": 0.031321798030832904\n },\n\
\ \"community|arabic_mmlu:high_school_world_history|0\": {\n \"acc_norm\"\
: 0.34177215189873417,\n \"acc_norm_stderr\": 0.030874537537553617\n },\n\
\ \"community|arabic_mmlu:human_aging|0\": {\n \"acc_norm\": 0.3991031390134529,\n\
\ \"acc_norm_stderr\": 0.03286745312567961\n },\n \"community|arabic_mmlu:human_sexuality|0\"\
: {\n \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.04328577215262972\n\
\ },\n \"community|arabic_mmlu:international_law|0\": {\n \"acc_norm\"\
: 0.5785123966942148,\n \"acc_norm_stderr\": 0.04507732278775087\n },\n\
\ \"community|arabic_mmlu:jurisprudence|0\": {\n \"acc_norm\": 0.46296296296296297,\n\
\ \"acc_norm_stderr\": 0.04820403072760627\n },\n \"community|arabic_mmlu:logical_fallacies|0\"\
: {\n \"acc_norm\": 0.4723926380368098,\n \"acc_norm_stderr\": 0.039223782906109894\n\
\ },\n \"community|arabic_mmlu:machine_learning|0\": {\n \"acc_norm\"\
: 0.3482142857142857,\n \"acc_norm_stderr\": 0.04521829902833586\n },\n\
\ \"community|arabic_mmlu:management|0\": {\n \"acc_norm\": 0.4368932038834951,\n\
\ \"acc_norm_stderr\": 0.04911147107365777\n },\n \"community|arabic_mmlu:marketing|0\"\
: {\n \"acc_norm\": 0.5683760683760684,\n \"acc_norm_stderr\": 0.0324483553531149\n\
\ },\n \"community|arabic_mmlu:medical_genetics|0\": {\n \"acc_norm\"\
: 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"community|arabic_mmlu:miscellaneous|0\"\
: {\n \"acc_norm\": 0.4623243933588761,\n \"acc_norm_stderr\": 0.017829131764287184\n\
\ },\n \"community|arabic_mmlu:moral_disputes|0\": {\n \"acc_norm\"\
: 0.407514450867052,\n \"acc_norm_stderr\": 0.026454578146931505\n },\n\
\ \"community|arabic_mmlu:moral_scenarios|0\": {\n \"acc_norm\": 0.23798882681564246,\n\
\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"community|arabic_mmlu:nutrition|0\"\
: {\n \"acc_norm\": 0.46405228758169936,\n \"acc_norm_stderr\": 0.028555827516528787\n\
\ },\n \"community|arabic_mmlu:philosophy|0\": {\n \"acc_norm\": 0.4212218649517685,\n\
\ \"acc_norm_stderr\": 0.028043399858210635\n },\n \"community|arabic_mmlu:prehistory|0\"\
: {\n \"acc_norm\": 0.4104938271604938,\n \"acc_norm_stderr\": 0.027371350925124764\n\
\ },\n \"community|arabic_mmlu:professional_accounting|0\": {\n \"\
acc_norm\": 0.2907801418439716,\n \"acc_norm_stderr\": 0.027090664368353178\n\
\ },\n \"community|arabic_mmlu:professional_law|0\": {\n \"acc_norm\"\
: 0.3109517601043025,\n \"acc_norm_stderr\": 0.011822252917799205\n },\n\
\ \"community|arabic_mmlu:professional_medicine|0\": {\n \"acc_norm\"\
: 0.21691176470588236,\n \"acc_norm_stderr\": 0.02503584522771127\n },\n\
\ \"community|arabic_mmlu:professional_psychology|0\": {\n \"acc_norm\"\
: 0.36764705882352944,\n \"acc_norm_stderr\": 0.019506291693954847\n },\n\
\ \"community|arabic_mmlu:public_relations|0\": {\n \"acc_norm\": 0.39090909090909093,\n\
\ \"acc_norm_stderr\": 0.04673752333670237\n },\n \"community|arabic_mmlu:security_studies|0\"\
: {\n \"acc_norm\": 0.4326530612244898,\n \"acc_norm_stderr\": 0.031717528240626645\n\
\ },\n \"community|arabic_mmlu:sociology|0\": {\n \"acc_norm\": 0.5621890547263682,\n\
\ \"acc_norm_stderr\": 0.035080801121998406\n },\n \"community|arabic_mmlu:us_foreign_policy|0\"\
: {\n \"acc_norm\": 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n\
\ },\n \"community|arabic_mmlu:virology|0\": {\n \"acc_norm\": 0.41566265060240964,\n\
\ \"acc_norm_stderr\": 0.03836722176598052\n },\n \"community|arabic_mmlu:world_religions|0\"\
: {\n \"acc_norm\": 0.4327485380116959,\n \"acc_norm_stderr\": 0.03799978644370608\n\
\ },\n \"community|arc_challenge_okapi_ar|0\": {\n \"acc_norm\": 0.36982758620689654,\n\
\ \"acc_norm_stderr\": 0.01418037210859747\n },\n \"community|arc_easy_ar|0\"\
: {\n \"acc_norm\": 0.41455160744500846,\n \"acc_norm_stderr\": 0.010134486532149578\n\
\ },\n \"community|boolq_ar|0\": {\n \"acc_norm\": 0.6220858895705521,\n\
\ \"acc_norm_stderr\": 0.00849336032152894\n },\n \"community|copa_ext_ar|0\"\
: {\n \"acc_norm\": 0.5666666666666667,\n \"acc_norm_stderr\": 0.05252667118728808\n\
\ },\n \"community|hellaswag_okapi_ar|0\": {\n \"acc_norm\": 0.26616508559590013,\n\
\ \"acc_norm_stderr\": 0.004615195054138359\n },\n \"community|openbook_qa_ext_ar|0\"\
: {\n \"acc_norm\": 0.4383838383838384,\n \"acc_norm_stderr\": 0.02232459513248414\n\
\ },\n \"community|piqa_ar|0\": {\n \"acc_norm\": 0.5575559192580469,\n\
\ \"acc_norm_stderr\": 0.011604078962074162\n },\n \"community|race_ar|0\"\
: {\n \"acc_norm\": 0.3590992087644553,\n \"acc_norm_stderr\": 0.006833878896866116\n\
\ },\n \"community|sciq_ar|0\": {\n \"acc_norm\": 0.4562814070351759,\n\
\ \"acc_norm_stderr\": 0.015798297434857358\n },\n \"community|toxigen_ar|0\"\
: {\n \"acc_norm\": 0.4320855614973262,\n \"acc_norm_stderr\": 0.01620887578524445\n\
\ },\n \"lighteval|xstory_cloze:ar|0\": {\n \"acc\": 0.5956320317670417,\n\
\ \"acc_stderr\": 0.012629580396570928\n },\n \"community|acva:_average|0\"\
: {\n \"acc_norm\": 0.45897910079456206,\n \"acc_norm_stderr\": 0.04763314008202572\n\
\ },\n \"community|alghafa:_average|0\": {\n \"acc_norm\": 0.454600416994282,\n\
\ \"acc_norm_stderr\": 0.02268116512425296\n },\n \"community|arabic_mmlu:_average|0\"\
: {\n \"acc_norm\": 0.3834369097890124,\n \"acc_norm_stderr\": 0.03575749811075187\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental
configs:
- config_name: community_acva_Algeria_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Algeria|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Algeria|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Ancient_Egypt_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Ancient_Egypt|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Ancient_Egypt|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arab_Empire_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arab_Empire|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arab_Empire|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Architecture_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Architecture|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Architecture|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Art_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Art|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Art|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Astronomy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Astronomy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Astronomy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Calligraphy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Calligraphy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Calligraphy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Ceremony_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Ceremony|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Ceremony|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Clothing_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Clothing|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Clothing|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Culture_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Culture|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Culture|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Food_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Food|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Food|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Funeral_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Funeral|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Funeral|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Geography_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Geography|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Geography|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_History_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_History|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_History|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Language_Origin_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Language_Origin|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Language_Origin|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Literature_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Literature|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Literature|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Math_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Math|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Math|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Medicine_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Medicine|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Medicine|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Music_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Music|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Music|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Ornament_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Ornament|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Ornament|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Philosophy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Philosophy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Philosophy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Physics_and_Chemistry_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Physics_and_Chemistry|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Physics_and_Chemistry|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Arabic_Wedding_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Arabic_Wedding|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Wedding|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Bahrain_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Bahrain|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Bahrain|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Comoros_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Comoros|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Comoros|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Egypt_modern_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Egypt_modern|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Egypt_modern|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromAncientEgypt_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromAncientEgypt|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromAncientEgypt|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromByzantium_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromByzantium|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromByzantium|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromChina_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromChina|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromChina|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromGreece_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromGreece|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromGreece|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromIslam_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromIslam|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromIslam|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromPersia_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromPersia|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromPersia|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_InfluenceFromRome_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:InfluenceFromRome|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromRome|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Iraq_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Iraq|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Iraq|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Islam_Education_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Islam_Education|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Islam_Education|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Islam_branches_and_schools_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Islam_branches_and_schools|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Islam_branches_and_schools|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Islamic_law_system_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Islamic_law_system|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Islamic_law_system|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Jordan_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Jordan|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Jordan|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Kuwait_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Kuwait|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Kuwait|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Lebanon_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Lebanon|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Lebanon|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Libya_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Libya|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Libya|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Mauritania_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Mauritania|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Mauritania|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Mesopotamia_civilization_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Mesopotamia_civilization|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Mesopotamia_civilization|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Morocco_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Morocco|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Morocco|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Oman_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Oman|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Oman|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Palestine_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Palestine|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Palestine|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Qatar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Qatar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Qatar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Saudi_Arabia_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Saudi_Arabia|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Saudi_Arabia|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Somalia_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Somalia|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Somalia|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Sudan_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Sudan|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Sudan|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Syria_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Syria|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Syria|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Tunisia_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Tunisia|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Tunisia|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_United_Arab_Emirates_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:United_Arab_Emirates|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:United_Arab_Emirates|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_Yemen_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:Yemen|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:Yemen|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_communication_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:communication|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:communication|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_computer_and_phone_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:computer_and_phone|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:computer_and_phone|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_daily_life_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:daily_life|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:daily_life|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_acva_entertainment_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|acva:entertainment|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|acva:entertainment|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_mcq_exams_test_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:mcq_exams_test_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:mcq_exams_test_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_meta_ar_dialects_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:meta_ar_dialects|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:meta_ar_dialects|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_meta_ar_msa_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:meta_ar_msa|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:meta_ar_msa|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_facts_truefalse_balanced_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_facts_truefalse_balanced_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_facts_truefalse_balanced_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_grounded_statement_soqal_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_soqal_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_soqal_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_rating_sentiment_no_neutral_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_rating_sentiment_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_alghafa_multiple_choice_sentiment_task_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|alghafa:multiple_choice_sentiment_task|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_sentiment_task|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_exams_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_exams|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_exams|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_abstract_algebra_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:abstract_algebra|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:abstract_algebra|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_anatomy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:anatomy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:anatomy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_astronomy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:astronomy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:astronomy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_business_ethics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:business_ethics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:business_ethics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_clinical_knowledge_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:clinical_knowledge|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:clinical_knowledge|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_biology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_biology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_biology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_chemistry_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_chemistry|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_chemistry|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_computer_science_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_computer_science|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_computer_science|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_mathematics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_medicine_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_medicine|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_medicine|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_college_physics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:college_physics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_physics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_computer_security_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:computer_security|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:computer_security|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_conceptual_physics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:conceptual_physics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:conceptual_physics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_econometrics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:econometrics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:econometrics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_electrical_engineering_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:electrical_engineering|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:electrical_engineering|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_elementary_mathematics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:elementary_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:elementary_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_formal_logic_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:formal_logic|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:formal_logic|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_global_facts_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:global_facts|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:global_facts|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_biology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_biology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_biology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_chemistry_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_chemistry|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_chemistry|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_computer_science_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_computer_science|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_computer_science|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_european_history_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_european_history|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_european_history|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_geography_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_geography|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_geography|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_government_and_politics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_government_and_politics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_government_and_politics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_macroeconomics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_macroeconomics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_macroeconomics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_mathematics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_mathematics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_microeconomics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_microeconomics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_microeconomics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_physics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_physics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_physics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_psychology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_psychology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_psychology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_statistics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_statistics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_statistics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_us_history_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_us_history|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_us_history|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_high_school_world_history_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:high_school_world_history|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_world_history|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_human_aging_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:human_aging|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:human_aging|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_human_sexuality_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:human_sexuality|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:human_sexuality|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_international_law_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:international_law|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:international_law|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_jurisprudence_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:jurisprudence|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:jurisprudence|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_logical_fallacies_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:logical_fallacies|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:logical_fallacies|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_machine_learning_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:machine_learning|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:machine_learning|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_management_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:management|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:management|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_marketing_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:marketing|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:marketing|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_medical_genetics_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:medical_genetics|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:medical_genetics|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_miscellaneous_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:miscellaneous|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:miscellaneous|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_moral_disputes_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:moral_disputes|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:moral_disputes|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_moral_scenarios_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:moral_scenarios|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:moral_scenarios|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_nutrition_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:nutrition|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:nutrition|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_philosophy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:philosophy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:philosophy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_prehistory_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:prehistory|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:prehistory|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_professional_accounting_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:professional_accounting|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_accounting|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_professional_law_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:professional_law|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_law|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_professional_medicine_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:professional_medicine|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_medicine|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_professional_psychology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:professional_psychology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_psychology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_public_relations_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:public_relations|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:public_relations|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_security_studies_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:security_studies|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:security_studies|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_sociology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:sociology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:sociology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_us_foreign_policy_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:us_foreign_policy|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:us_foreign_policy|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_virology_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:virology|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:virology|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arabic_mmlu_world_religions_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arabic_mmlu:world_religions|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:world_religions|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arc_challenge_okapi_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arc_challenge_okapi_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arc_challenge_okapi_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_arc_easy_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|arc_easy_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|arc_easy_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_boolq_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|boolq_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|boolq_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_copa_ext_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|copa_ext_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|copa_ext_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_hellaswag_okapi_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|hellaswag_okapi_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|hellaswag_okapi_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_openbook_qa_ext_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|openbook_qa_ext_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|openbook_qa_ext_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_piqa_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|piqa_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|piqa_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_race_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|race_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|race_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_sciq_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|sciq_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|sciq_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: community_toxigen_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_community|toxigen_ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_community|toxigen_ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: lighteval_xstory_cloze_ar_0
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- '**/details_lighteval|xstory_cloze:ar|0_2024-05-27T14-06-39.187751.parquet'
- split: latest
path:
- '**/details_lighteval|xstory_cloze:ar|0_2024-05-27T14-06-39.187751.parquet'
- config_name: results
data_files:
- split: 2024_05_27T14_06_39.187751
path:
- results_2024-05-27T14-06-39.187751.parquet
- split: latest
path:
- results_2024-05-27T14-06-39.187751.parquet
---
# Dataset Card for Evaluation run of Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental](https://huggingface.co/Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental).
The dataset is composed of 136 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.
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental",
"lighteval_xstory_cloze_ar_0",
split="train")
```
## Latest results
These are the [latest results from run 2024-05-27T14:06:39.187751](https://huggingface.co/datasets/OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental/blob/main/results_2024-05-27T14-06-39.187751.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_norm": 0.4253986985051422,
"acc_norm_stderr": 0.0384347707626982,
"acc": 0.5956320317670417,
"acc_stderr": 0.012629580396570928
},
"community|acva:Algeria|0": {
"acc_norm": 0.5743589743589743,
"acc_norm_stderr": 0.03549871080367707
},
"community|acva:Ancient_Egypt|0": {
"acc_norm": 0.10158730158730159,
"acc_norm_stderr": 0.01704876125499024
},
"community|acva:Arab_Empire|0": {
"acc_norm": 0.4377358490566038,
"acc_norm_stderr": 0.030533338430467512
},
"community|acva:Arabic_Architecture|0": {
"acc_norm": 0.47692307692307695,
"acc_norm_stderr": 0.0358596530894741
},
"community|acva:Arabic_Art|0": {
"acc_norm": 0.39487179487179486,
"acc_norm_stderr": 0.03509545602262037
},
"community|acva:Arabic_Astronomy|0": {
"acc_norm": 0.49230769230769234,
"acc_norm_stderr": 0.03589365940635213
},
"community|acva:Arabic_Calligraphy|0": {
"acc_norm": 0.5294117647058824,
"acc_norm_stderr": 0.03131846503821582
},
"community|acva:Arabic_Ceremony|0": {
"acc_norm": 0.5351351351351351,
"acc_norm_stderr": 0.03676936950948699
},
"community|acva:Arabic_Clothing|0": {
"acc_norm": 0.4717948717948718,
"acc_norm_stderr": 0.035840746749208334
},
"community|acva:Arabic_Culture|0": {
"acc_norm": 0.2564102564102564,
"acc_norm_stderr": 0.031349709942744934
},
"community|acva:Arabic_Food|0": {
"acc_norm": 0.46153846153846156,
"acc_norm_stderr": 0.03579154352544571
},
"community|acva:Arabic_Funeral|0": {
"acc_norm": 0.4,
"acc_norm_stderr": 0.050529115263991134
},
"community|acva:Arabic_Geography|0": {
"acc_norm": 0.6344827586206897,
"acc_norm_stderr": 0.04013124195424386
},
"community|acva:Arabic_History|0": {
"acc_norm": 0.3641025641025641,
"acc_norm_stderr": 0.0345465386778639
},
"community|acva:Arabic_Language_Origin|0": {
"acc_norm": 0.6,
"acc_norm_stderr": 0.050529115263991134
},
"community|acva:Arabic_Literature|0": {
"acc_norm": 0.496551724137931,
"acc_norm_stderr": 0.041665675771015785
},
"community|acva:Arabic_Math|0": {
"acc_norm": 0.40512820512820513,
"acc_norm_stderr": 0.03524577495610961
},
"community|acva:Arabic_Medicine|0": {
"acc_norm": 0.46206896551724136,
"acc_norm_stderr": 0.041546596717075474
},
"community|acva:Arabic_Music|0": {
"acc_norm": 0.23741007194244604,
"acc_norm_stderr": 0.036220593237998276
},
"community|acva:Arabic_Ornament|0": {
"acc_norm": 0.6666666666666666,
"acc_norm_stderr": 0.03384487217112065
},
"community|acva:Arabic_Philosophy|0": {
"acc_norm": 0.5310344827586206,
"acc_norm_stderr": 0.04158632762097828
},
"community|acva:Arabic_Physics_and_Chemistry|0": {
"acc_norm": 0.5333333333333333,
"acc_norm_stderr": 0.03581804596782232
},
"community|acva:Arabic_Wedding|0": {
"acc_norm": 0.6205128205128205,
"acc_norm_stderr": 0.03483959266365359
},
"community|acva:Bahrain|0": {
"acc_norm": 0.37777777777777777,
"acc_norm_stderr": 0.07309112127323451
},
"community|acva:Comoros|0": {
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.07491109582924915
},
"community|acva:Egypt_modern|0": {
"acc_norm": 0.5684210526315789,
"acc_norm_stderr": 0.05108592673308946
},
"community|acva:InfluenceFromAncientEgypt|0": {
"acc_norm": 0.5384615384615384,
"acc_norm_stderr": 0.0357915435254457
},
"community|acva:InfluenceFromByzantium|0": {
"acc_norm": 0.7172413793103448,
"acc_norm_stderr": 0.037528339580033376
},
"community|acva:InfluenceFromChina|0": {
"acc_norm": 0.26666666666666666,
"acc_norm_stderr": 0.03174930436412669
},
"community|acva:InfluenceFromGreece|0": {
"acc_norm": 0.6461538461538462,
"acc_norm_stderr": 0.03433004254147036
},
"community|acva:InfluenceFromIslam|0": {
"acc_norm": 0.31724137931034485,
"acc_norm_stderr": 0.038783523721386215
},
"community|acva:InfluenceFromPersia|0": {
"acc_norm": 0.7028571428571428,
"acc_norm_stderr": 0.03464507889884372
},
"community|acva:InfluenceFromRome|0": {
"acc_norm": 0.5743589743589743,
"acc_norm_stderr": 0.03549871080367708
},
"community|acva:Iraq|0": {
"acc_norm": 0.6470588235294118,
"acc_norm_stderr": 0.0521414859075246
},
"community|acva:Islam_Education|0": {
"acc_norm": 0.4564102564102564,
"acc_norm_stderr": 0.03576123096991215
},
"community|acva:Islam_branches_and_schools|0": {
"acc_norm": 0.4857142857142857,
"acc_norm_stderr": 0.03788942763158507
},
"community|acva:Islamic_law_system|0": {
"acc_norm": 0.4307692307692308,
"acc_norm_stderr": 0.0355521325205876
},
"community|acva:Jordan|0": {
"acc_norm": 0.37777777777777777,
"acc_norm_stderr": 0.07309112127323451
},
"community|acva:Kuwait|0": {
"acc_norm": 0.3111111111111111,
"acc_norm_stderr": 0.06979205927323111
},
"community|acva:Lebanon|0": {
"acc_norm": 0.2222222222222222,
"acc_norm_stderr": 0.06267511942419626
},
"community|acva:Libya|0": {
"acc_norm": 0.5111111111111111,
"acc_norm_stderr": 0.07535922203472523
},
"community|acva:Mauritania|0": {
"acc_norm": 0.4888888888888889,
"acc_norm_stderr": 0.07535922203472523
},
"community|acva:Mesopotamia_civilization|0": {
"acc_norm": 0.5806451612903226,
"acc_norm_stderr": 0.03976361630387024
},
"community|acva:Morocco|0": {
"acc_norm": 0.37777777777777777,
"acc_norm_stderr": 0.0730911212732345
},
"community|acva:Oman|0": {
"acc_norm": 0.4222222222222222,
"acc_norm_stderr": 0.07446027270295806
},
"community|acva:Palestine|0": {
"acc_norm": 0.3764705882352941,
"acc_norm_stderr": 0.052863310306265295
},
"community|acva:Qatar|0": {
"acc_norm": 0.6,
"acc_norm_stderr": 0.07385489458759965
},
"community|acva:Saudi_Arabia|0": {
"acc_norm": 0.5435897435897435,
"acc_norm_stderr": 0.03576123096991214
},
"community|acva:Somalia|0": {
"acc_norm": 0.6,
"acc_norm_stderr": 0.07385489458759965
},
"community|acva:Sudan|0": {
"acc_norm": 0.4,
"acc_norm_stderr": 0.07385489458759965
},
"community|acva:Syria|0": {
"acc_norm": 0.4,
"acc_norm_stderr": 0.07385489458759964
},
"community|acva:Tunisia|0": {
"acc_norm": 0.26666666666666666,
"acc_norm_stderr": 0.06666666666666665
},
"community|acva:United_Arab_Emirates|0": {
"acc_norm": 0.4823529411764706,
"acc_norm_stderr": 0.054520483406618934
},
"community|acva:Yemen|0": {
"acc_norm": 0.5,
"acc_norm_stderr": 0.16666666666666666
},
"community|acva:communication|0": {
"acc_norm": 0.43131868131868134,
"acc_norm_stderr": 0.02599443023962308
},
"community|acva:computer_and_phone|0": {
"acc_norm": 0.45084745762711864,
"acc_norm_stderr": 0.02901934773187137
},
"community|acva:daily_life|0": {
"acc_norm": 0.18694362017804153,
"acc_norm_stderr": 0.021268948348414647
},
"community|acva:entertainment|0": {
"acc_norm": 0.23389830508474577,
"acc_norm_stderr": 0.024687839412166384
},
"community|alghafa:mcq_exams_test_ar|0": {
"acc_norm": 0.3303411131059246,
"acc_norm_stderr": 0.01994668532793601
},
"community|alghafa:meta_ar_dialects|0": {
"acc_norm": 0.3088044485634847,
"acc_norm_stderr": 0.006290523225095885
},
"community|alghafa:meta_ar_msa|0": {
"acc_norm": 0.3463687150837989,
"acc_norm_stderr": 0.015913546784020117
},
"community|alghafa:multiple_choice_facts_truefalse_balanced_task|0": {
"acc_norm": 0.52,
"acc_norm_stderr": 0.05807730170189531
},
"community|alghafa:multiple_choice_grounded_statement_soqal_task|0": {
"acc_norm": 0.52,
"acc_norm_stderr": 0.04092881363092387
},
"community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0": {
"acc_norm": 0.4066666666666667,
"acc_norm_stderr": 0.04024162665739063
},
"community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0": {
"acc_norm": 0.7697310819262039,
"acc_norm_stderr": 0.004708744220539922
},
"community|alghafa:multiple_choice_rating_sentiment_task|0": {
"acc_norm": 0.5296080066722268,
"acc_norm_stderr": 0.006446869248966106
},
"community|alghafa:multiple_choice_sentiment_task|0": {
"acc_norm": 0.3598837209302326,
"acc_norm_stderr": 0.011576375321508726
},
"community|arabic_exams|0": {
"acc_norm": 0.3780260707635009,
"acc_norm_stderr": 0.020944238360403714
},
"community|arabic_mmlu:abstract_algebra|0": {
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"community|arabic_mmlu:anatomy|0": {
"acc_norm": 0.3851851851851852,
"acc_norm_stderr": 0.042039210401562783
},
"community|arabic_mmlu:astronomy|0": {
"acc_norm": 0.4407894736842105,
"acc_norm_stderr": 0.040403110624904356
},
"community|arabic_mmlu:business_ethics|0": {
"acc_norm": 0.58,
"acc_norm_stderr": 0.049604496374885836
},
"community|arabic_mmlu:clinical_knowledge|0": {
"acc_norm": 0.3886792452830189,
"acc_norm_stderr": 0.03000048544867599
},
"community|arabic_mmlu:college_biology|0": {
"acc_norm": 0.3819444444444444,
"acc_norm_stderr": 0.040629907841466674
},
"community|arabic_mmlu:college_chemistry|0": {
"acc_norm": 0.25,
"acc_norm_stderr": 0.04351941398892446
},
"community|arabic_mmlu:college_computer_science|0": {
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"community|arabic_mmlu:college_mathematics|0": {
"acc_norm": 0.26,
"acc_norm_stderr": 0.044084400227680794
},
"community|arabic_mmlu:college_medicine|0": {
"acc_norm": 0.32947976878612717,
"acc_norm_stderr": 0.03583901754736412
},
"community|arabic_mmlu:college_physics|0": {
"acc_norm": 0.27450980392156865,
"acc_norm_stderr": 0.044405219061793254
},
"community|arabic_mmlu:computer_security|0": {
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"community|arabic_mmlu:conceptual_physics|0": {
"acc_norm": 0.34893617021276596,
"acc_norm_stderr": 0.031158522131357756
},
"community|arabic_mmlu:econometrics|0": {
"acc_norm": 0.3508771929824561,
"acc_norm_stderr": 0.044895393502706986
},
"community|arabic_mmlu:electrical_engineering|0": {
"acc_norm": 0.46206896551724136,
"acc_norm_stderr": 0.041546596717075474
},
"community|arabic_mmlu:elementary_mathematics|0": {
"acc_norm": 0.3333333333333333,
"acc_norm_stderr": 0.024278568024307706
},
"community|arabic_mmlu:formal_logic|0": {
"acc_norm": 0.31746031746031744,
"acc_norm_stderr": 0.041634530313028585
},
"community|arabic_mmlu:global_facts|0": {
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"community|arabic_mmlu:high_school_biology|0": {
"acc_norm": 0.3903225806451613,
"acc_norm_stderr": 0.027751256636969576
},
"community|arabic_mmlu:high_school_chemistry|0": {
"acc_norm": 0.3645320197044335,
"acc_norm_stderr": 0.0338640574606209
},
"community|arabic_mmlu:high_school_computer_science|0": {
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"community|arabic_mmlu:high_school_european_history|0": {
"acc_norm": 0.23636363636363636,
"acc_norm_stderr": 0.03317505930009179
},
"community|arabic_mmlu:high_school_geography|0": {
"acc_norm": 0.3838383838383838,
"acc_norm_stderr": 0.03464881675016338
},
"community|arabic_mmlu:high_school_government_and_politics|0": {
"acc_norm": 0.38860103626943004,
"acc_norm_stderr": 0.03517739796373134
},
"community|arabic_mmlu:high_school_macroeconomics|0": {
"acc_norm": 0.37435897435897436,
"acc_norm_stderr": 0.024537591572830503
},
"community|arabic_mmlu:high_school_mathematics|0": {
"acc_norm": 0.2777777777777778,
"acc_norm_stderr": 0.027309140588230175
},
"community|arabic_mmlu:high_school_microeconomics|0": {
"acc_norm": 0.3319327731092437,
"acc_norm_stderr": 0.030588697013783663
},
"community|arabic_mmlu:high_school_physics|0": {
"acc_norm": 0.31125827814569534,
"acc_norm_stderr": 0.03780445850526731
},
"community|arabic_mmlu:high_school_psychology|0": {
"acc_norm": 0.381651376146789,
"acc_norm_stderr": 0.020828148517022606
},
"community|arabic_mmlu:high_school_statistics|0": {
"acc_norm": 0.24537037037037038,
"acc_norm_stderr": 0.029346665094372937
},
"community|arabic_mmlu:high_school_us_history|0": {
"acc_norm": 0.27450980392156865,
"acc_norm_stderr": 0.031321798030832904
},
"community|arabic_mmlu:high_school_world_history|0": {
"acc_norm": 0.34177215189873417,
"acc_norm_stderr": 0.030874537537553617
},
"community|arabic_mmlu:human_aging|0": {
"acc_norm": 0.3991031390134529,
"acc_norm_stderr": 0.03286745312567961
},
"community|arabic_mmlu:human_sexuality|0": {
"acc_norm": 0.4198473282442748,
"acc_norm_stderr": 0.04328577215262972
},
"community|arabic_mmlu:international_law|0": {
"acc_norm": 0.5785123966942148,
"acc_norm_stderr": 0.04507732278775087
},
"community|arabic_mmlu:jurisprudence|0": {
"acc_norm": 0.46296296296296297,
"acc_norm_stderr": 0.04820403072760627
},
"community|arabic_mmlu:logical_fallacies|0": {
"acc_norm": 0.4723926380368098,
"acc_norm_stderr": 0.039223782906109894
},
"community|arabic_mmlu:machine_learning|0": {
"acc_norm": 0.3482142857142857,
"acc_norm_stderr": 0.04521829902833586
},
"community|arabic_mmlu:management|0": {
"acc_norm": 0.4368932038834951,
"acc_norm_stderr": 0.04911147107365777
},
"community|arabic_mmlu:marketing|0": {
"acc_norm": 0.5683760683760684,
"acc_norm_stderr": 0.0324483553531149
},
"community|arabic_mmlu:medical_genetics|0": {
"acc_norm": 0.43,
"acc_norm_stderr": 0.04975698519562428
},
"community|arabic_mmlu:miscellaneous|0": {
"acc_norm": 0.4623243933588761,
"acc_norm_stderr": 0.017829131764287184
},
"community|arabic_mmlu:moral_disputes|0": {
"acc_norm": 0.407514450867052,
"acc_norm_stderr": 0.026454578146931505
},
"community|arabic_mmlu:moral_scenarios|0": {
"acc_norm": 0.23798882681564246,
"acc_norm_stderr": 0.014242630070574915
},
"community|arabic_mmlu:nutrition|0": {
"acc_norm": 0.46405228758169936,
"acc_norm_stderr": 0.028555827516528787
},
"community|arabic_mmlu:philosophy|0": {
"acc_norm": 0.4212218649517685,
"acc_norm_stderr": 0.028043399858210635
},
"community|arabic_mmlu:prehistory|0": {
"acc_norm": 0.4104938271604938,
"acc_norm_stderr": 0.027371350925124764
},
"community|arabic_mmlu:professional_accounting|0": {
"acc_norm": 0.2907801418439716,
"acc_norm_stderr": 0.027090664368353178
},
"community|arabic_mmlu:professional_law|0": {
"acc_norm": 0.3109517601043025,
"acc_norm_stderr": 0.011822252917799205
},
"community|arabic_mmlu:professional_medicine|0": {
"acc_norm": 0.21691176470588236,
"acc_norm_stderr": 0.02503584522771127
},
"community|arabic_mmlu:professional_psychology|0": {
"acc_norm": 0.36764705882352944,
"acc_norm_stderr": 0.019506291693954847
},
"community|arabic_mmlu:public_relations|0": {
"acc_norm": 0.39090909090909093,
"acc_norm_stderr": 0.04673752333670237
},
"community|arabic_mmlu:security_studies|0": {
"acc_norm": 0.4326530612244898,
"acc_norm_stderr": 0.031717528240626645
},
"community|arabic_mmlu:sociology|0": {
"acc_norm": 0.5621890547263682,
"acc_norm_stderr": 0.035080801121998406
},
"community|arabic_mmlu:us_foreign_policy|0": {
"acc_norm": 0.67,
"acc_norm_stderr": 0.04725815626252607
},
"community|arabic_mmlu:virology|0": {
"acc_norm": 0.41566265060240964,
"acc_norm_stderr": 0.03836722176598052
},
"community|arabic_mmlu:world_religions|0": {
"acc_norm": 0.4327485380116959,
"acc_norm_stderr": 0.03799978644370608
},
"community|arc_challenge_okapi_ar|0": {
"acc_norm": 0.36982758620689654,
"acc_norm_stderr": 0.01418037210859747
},
"community|arc_easy_ar|0": {
"acc_norm": 0.41455160744500846,
"acc_norm_stderr": 0.010134486532149578
},
"community|boolq_ar|0": {
"acc_norm": 0.6220858895705521,
"acc_norm_stderr": 0.00849336032152894
},
"community|copa_ext_ar|0": {
"acc_norm": 0.5666666666666667,
"acc_norm_stderr": 0.05252667118728808
},
"community|hellaswag_okapi_ar|0": {
"acc_norm": 0.26616508559590013,
"acc_norm_stderr": 0.004615195054138359
},
"community|openbook_qa_ext_ar|0": {
"acc_norm": 0.4383838383838384,
"acc_norm_stderr": 0.02232459513248414
},
"community|piqa_ar|0": {
"acc_norm": 0.5575559192580469,
"acc_norm_stderr": 0.011604078962074162
},
"community|race_ar|0": {
"acc_norm": 0.3590992087644553,
"acc_norm_stderr": 0.006833878896866116
},
"community|sciq_ar|0": {
"acc_norm": 0.4562814070351759,
"acc_norm_stderr": 0.015798297434857358
},
"community|toxigen_ar|0": {
"acc_norm": 0.4320855614973262,
"acc_norm_stderr": 0.01620887578524445
},
"lighteval|xstory_cloze:ar|0": {
"acc": 0.5956320317670417,
"acc_stderr": 0.012629580396570928
},
"community|acva:_average|0": {
"acc_norm": 0.45897910079456206,
"acc_norm_stderr": 0.04763314008202572
},
"community|alghafa:_average|0": {
"acc_norm": 0.454600416994282,
"acc_norm_stderr": 0.02268116512425296
},
"community|arabic_mmlu:_average|0": {
"acc_norm": 0.3834369097890124,
"acc_norm_stderr": 0.03575749811075187
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
lingvenvist/more_a_h_2.csv | lingvenvist | "2024-05-27T14:24:33Z" | 0 | 0 | [
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:13:41Z" | ---
dataset_info:
features:
- name: sentences
dtype: string
- name: tokens
sequence: string
- name: anim_tags
sequence:
class_label:
names:
'0': N
'1': A
'2': H
- name: target-indexes
sequence: int64
splits:
- name: train
num_bytes: 14219555.597162277
num_examples: 38623
- name: test
num_bytes: 2217106.2740564435
num_examples: 5872
- name: validation
num_bytes: 1879539.3533294506
num_examples: 5143
download_size: 8476322
dataset_size: 18316201.224548172
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
---
|
saluslab/human-machine-interactions | saluslab | "2024-06-29T19:38:47Z" | 0 | 1 | [
"task_categories:video-classification",
"task_categories:time-series-forecasting",
"task_categories:other",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:100K<n<1M",
"modality:image",
"region:us",
"human action recognition",
"skeleton-based human action recognition",
"joint skeletons",
"human interaction",
"cyber-physical-social systems",
"digital twins"
] | [
"video-classification",
"time-series-forecasting",
"other"
] | "2024-05-27T14:14:43Z" | ---
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: Human-Machine Interactions with a Wire Arc Additive Manufacturing Machine
size_categories:
- 100K<n<1M
source_datasets:
- original
tags:
- human action recognition
- skeleton-based human action recognition
- joint skeletons
- human interaction
- cyber-physical-social systems
- digital twins
task_categories:
- video-classification
- time-series-forecasting
- other
task_ids: []
---
# Dataset Card for this Human-Machine Interaction Dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Overview](#dataset-overview)
- [Summary of Data](#summary-of-data)
- [Motivation for this Dataset](#motivation-for-this-dataset)
- [Supported Tasks](#supported-tasks)
- [Languages](#languages)
- [Data Contents](#data-contents)
- [Data Frame](#data-frame)
- [Data Collection](#data-collection)
- [Machine of Focus and Facility](#machine-of-focus-and-facility)
- [Sensor and Data Modality](#sensor-and-data-modality)
- [A Note on Privacy](#a-note-on-privacy)
- [Additional Information and Analysis Techniques](#additional-information-and-analysis-techniques)
- [Action List](#action-list)
- [Skeleton Features](#skeleton-features)
- [Machine Learning Techniques](#machine-learning-techniques)
- [Acknowledgements](#acknowledgements)
- [Dataset Curators](#dataset-curation)
- [Funding and Support](#funding-and-support)
- [Citation](#citation)
## Dataset Overview
This dataset contains a collection of observed interactions between humans and an advanced manufacturing machine, specifically a Wire Arc Additive Manufacuturing (WAAM) machine. The motivations for collecting this dataset, the contents of this dataset, and some ideas for how to analyze and use this dataset can be found below.
Additionally, the paper introducing this dataset is undergoing review for publication to the American Society of Mechanical Engineers(ASME)’s Journal of Mechanical Design (JMD) special issue: “Cultivating Datasets for Engineering Design”. If accepted, the paper will be referenced here.
### Motivation for this Dataset
The engineering design process for any solution or product is essential to ensure quality results and standards. However, this process can be very tedious and require many re-iterations, especially if it involves manufacturing a product. If engineers and designers are designing a product to be manufactured, but are disconnected from the realities of their available manufacturing capabilities, there can be many redesign iterations stemming from this misunderstanding between design specifications and production / supply chain abilities. Design for Manufacturing (DfM) is a style of design that, relying on accurate simulation and modeling of available manufacturing processes, takes into account the product manufacturing when designing products such that the design reiteration inefficiency is improved. To improve the transparency between manufacturing and design, establishing methods to understand and quantify the various steps in the manufacturing process is crucial. Within this effort, and in manufacturing, one of the most difficult aspects to understand and quantify is the interactions of humans and machinery. While manufacturing is undergoing immense change due to automation technologies and robotics, humans still play a central role in operations, however their behaviors / actions and how it influences the manufacturing process is poorly understood. This dataset attempts to support the understanding of humans in manufacturing by observing realistic interactions between humans and an advanced manufacturing machine.
### Supported Tasks
- `video-classification`: Using the series of provided frames of depth images and joint skeletons, machine learning techniques can be used to classify these by human actions.
### Languages
English
## Data Contents
This dataset comprises 3.87 hours of footage (209,230 frames of data at 15 FPS) representing a total of 1228 interactions captured over 6 months.
The depth images were captured from the Microsoft Azure Kinect DK sensor in NFOV mode (More can be found on the [Azure Kinect Hardware Specs Website](https://learn.microsoft.com/en-us/azure/kinect-dk/hardware-specification) )and skeletons extracted of the humans in each frame were extracted using the Azure Kinect Body Tracking SDK (found [here](https://microsoft.github.io/Azure-Kinect-Body-Tracking/release/1.1.x/index.html) ).
### Data Frame
Each frame contains the following data points and labels:
* image: A 320x288 16-bit grayscale .png file of the depth image captured. This depth image is either from the outer machine perspective or the inner perspective according to the view label.
* frame(#): An integer (from 0 - 209230) representing a unique frame identifier number. The frames are numbered in chronological order.
* skeleton: An array of 32 3D coordinates. Each skeleton array captures 32 joints on the human body within the frame according to the Microsoft Azure Kinect Body Tracking SDK (linked above). For more information about the indexing of each joint, see this [Azure Kinect Joint Skeleton Webpage](https://learn.microsoft.com/en-us/azure/kinect-dk/body-joints).
* action_label: A label of which action the current frame is capturing. A list of all the label actions can be found below.
* location_label: A label of where on the machine the human is performing the interaction in the current frame.
* user_label: A label of the unique user ID given to the person in the frame. There are a total of 4 users (numbered 0 - 3). This order of user id is also the frequency with which they use the machine - 0 being the most frequent and 3 being the least.
* view_label: A label of which sensor perspective best captures the action in the frame (0 for outer perspective and 1 for inner).
* action_number: A label (0 - 1227) describing which of the total 1228 actions a particular frame is a part of. The data originally consisted of 1228 depth video clips of each action from its start to finish and all these videos were later split into individual frames. Since analyzing human actions usually needs temporal context, the action number allows for the grouping and ordering (in conjunction with the frame number or timestamp label) of all frames that comprise of a complete action.
* datetime: A timestamp of when this frame was captured. This allows for ordering of frames and actions as well as seeing how long was waited in between adjacent actions. This also allows for the splitting of experimental sessions between days. The context of the ordering of actions as well as which may occur at the beginning or end of a day is very useful.
## Data Collection
### Machine of Focus and Facility
The machine being interacted with in this dataset is the Lincoln Electric Sculptprint RND Wire Arc Additive Manufacturing (WAAM) machine. The WAAM machine is a large-format metal 3D printer housed in a 2.2m x 4.1m x 2.3 m (LxWxH) chamber that includes a robotic welder arm that deposits molten metal filament upon a specially configured build plate in a layered fashion. We chose this machine as a starting point because it exemplifies a wide variety of different human interactions. Actions range from very direct, hands-on actions like grinding down the metal build plate or refitting parts on the build plate to more indirect hands-off actions like calibrating the robot arm with a joystick or using the digital control panel.
Additionally, the machine we studied was housed at Mill19, a manufacturing and robotics research facility run by the Manufacturing Future Institute (MFI) at Carnegie Mellon University. More about this machine and facility can be found at [MFI's page about the WAAM](https://engineering.cmu.edu/mfi/facilities/equipment-details/lincoln-electric-sculptprint-rnd.html).
### Sensor and Data Modality
For our data collection, we used 2 Microsoft Azure Kinect DK cameras (Linked again [here](https://learn.microsoft.com/en-us/azure/kinect-dk/hardware-specification) for convenience). Due to the WAAM machine having points of interaction both inside its welding chamber and outside, we installed 2 Azure Kinect sensors to observe human interactions, 1 captures the ‘outer perspective’ and the other the ‘inner perspective’. While the Azure Kinect captures many modalities of data, we chose to focus on depth images (in near-field-of-view ’NFOV’ mode) and human joint skeletons. These were extracted at a rate of 1/15 frames per second.
### A Note on Privacy
The choice to focus on just depth and joint skeletons was made in order to preserve the privacy of users being sensed. This is very important to maintain when observing humans in a largely shared environment. This is also important in industry or any public infrastructure settings, thus if we can show that meaningful knowledge can be learned using privacy preserving technologies, more wide-spread use of these technologies can be used safely.
## Additional Information and Analysis Techniques
### Action List
A complete list of actions and a brief description include:
* using_control_panel : Interfacing with machine start/stop controls and digital screen used for visualizing build files and configuring machine parameters.
* using_flexpendant_mounted : Flexpendant being used in its control mode for loading build parameters and viewing machine output logs.
* using_flexpendant_mobile : Flexpendant being used in its machine operation mode for moving the robotic arm with the attached joystick.
* inspecting_buildplate : Performing light build plate modifications and inspections before or after a build.
* preparing_buildplate : Clearing or moving build plate to set up next build.
* refit_buildplate : Completely switching out the build plate configuration for a new project.
* grinding_buildplate : Grinding down the new build plate to expose conductive metal and level surface.
* toggle_lights : Turn the internal WAAM light on/off.
* open_door : Opening the WAAM door.
* close_door : Closing the WAAM door.
* turning_gas_knobs : Turning on/off shielding gas.
* adjusting_tool : Installing or modifying new/existing sensors on the robotic welder arm.
* wiring : Installing or adjusting wiring of tool sensors.
* donning_ppe : Users putting on personal protective equipment.
* doffing_ppe : Users taking off personal protective equipment.
* observing : Simply looking around or watching WAAM activity.
* walking : Simply walking around the WAAM.
### Skeleton Features
The skeleton data provided in each frame consists of an array of 32 joint coordinates in 3D space (x,y,z). The units of each coordinate value are in millimeters and the origin is the respective Kinect sensor capturing the particular frame (more on the coordinate system can be found on [the Azure Kinect webpage on the sensor coordinate system](https://learn.microsoft.com/en-us/azure/kinect-dk/coordinate-systems) and the [Body Tracking SDK’s webpage on joints](https://learn.microsoft.com/en-us/azure/kinect-dk/body-joints)).
While analysis techniques can be used on these ‘raw’ coordinate, there are many hand-picked features that can be extracted from these coordinates. Some basic and popular examples include:
* Joint Coordinate Normalization: The coordinates from the skeletons can be normalized with respect to each other. Additionally, another technique can be to choose a single joint in the center of the body to be the ‘origin’ coordinate, then re-calculate the coordinates of every other joint in relation to this central one.
* Joint Velocities: Calculated by the difference in a joint’s coordinates between frames (each frame is 1/15 of a second apart)
* Joint Angles: Calculate the angle created at a specific joint by adjacent limbs by performing some trigonometric calculations using the vectors from the joint of focus and its adjacent joints.
* Joint Distances: Pick 2 joints of interest and derive the distance between them using some basic geometric calculation.
### Machine Learning Techniques
Human action recognition often utilizes deep learning techniques to analyze and identify patterns in human actions. This is due to some deep learning techniques having great ability to analyze data both temporally and spatially. Some popular deep learning models include:
* Long-Short Term Memory (LSTM) : This deep learning model is a type of recurrent neural network (RNN) specifically targeted to avoid the vanishing gradient problem and tailored to temporal / sequential data with invariance to large or small gaps in important information distributed through the sequence.
* Convolutional Neural Network (CNN) : A powerful image-based model that can extract visual features from complex imagery.
* Graph Neural Networks (GCN) : A convolutional model performed over a defined / specialized graph network as opposed to an array of pixels. A specific example of this is the Spatial-Temporal GCN (STGCN), which is popularly used among skeleton-based human action recognition.
* Autoencoding : An unsupervised learning technique that can be used to learn sets of patterns and features shared by data. This can be particularly powerful for clustering data and quantifying differences between particular actions. This is also powerful in reducing data dimensionality - being able to represent the data using a smaller set of features than originally.
## Acknowledgements
### Dataset Curators
This dataset was collected by John Martins with the guidance of Katherine Flanigan and Christopher McComb
The corresponding paper was written by John Martins, Katherine Flanigan, and Chrisopher McComb
### Funding and Support
We thank Carnegie Mellon’s Manufacturing Futures Institute for graciously funding and supporting the endeavors to collect this data. We also want to thank Mill19 for granting access to their facilities and allowing us to install sensors. Lastly, we would like to thank the users of the WAAM machine for allowing us to collect data on their uses of the machine over the 6 month data collection period.
### Citation
As mentioned before, the paper introducing this dataset is undergoing review for publication to the American Society of Mechanical Engineers(ASME)’s Journal of Mechanical Design (JMD) special issue: “Cultivating Datasets for Engineering Design”. If accepted, the paper will be referenced here.
|
Zual/chessGPT | Zual | "2024-08-04T15:50:58Z" | 0 | 0 | [
"task_categories:text-generation",
"language:fr",
"license:mit",
"region:us"
] | [
"text-generation"
] | "2024-05-27T14:16:28Z" | ---
license: mit
task_categories:
- text-generation
language:
- fr
---
Here is some datasets that contains "noisy" chess games. We define the noise as a probability of playing a random (yet legal) chess move. For example, a chess game with 5% of noise is a chess game between Stockfish and himself when each move have 5% of chance to be random. |
Null-NaN/ss_test_org_ships_0 | Null-NaN | "2024-05-27T15:08:07Z" | 0 | 0 | [
"size_categories:n<1K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:16:39Z" | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 10427248.0
num_examples: 180
download_size: 9213189
dataset_size: 10427248.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
fresvyx/alpaca2-imam-ganteng | fresvyx | "2024-05-27T14:17:41Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:17:40Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 1351672
num_examples: 1000
download_size: 712329
dataset_size: 1351672
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
damerajee/small_clean_llava-instruct-mix | damerajee | "2024-05-27T14:25:27Z" | 0 | 0 | [
"size_categories:10K<n<100K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:18:44Z" | ---
dataset_info:
features:
- name: image
dtype: image
- name: conversations
dtype: string
- name: texts
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 8283699598.0
num_examples: 50000
download_size: 8207810675
dataset_size: 8283699598.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
bpalacios/ttgphismall | bpalacios | "2024-05-29T13:24:41Z" | 0 | 0 | [
"license:mit",
"size_categories:n<1K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:20:52Z" | ---
license: mit
---
|
roshikhan3021/netbrix-dataset | roshikhan3021 | "2024-05-27T14:28:34Z" | 0 | 0 | [
"license:mit",
"region:us"
] | null | "2024-05-27T14:28:34Z" | ---
license: mit
---
|
asahi417/seamless-align-enA-jaA | asahi417 | "2024-05-28T16:11:38Z" | 0 | 0 | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:33:43Z" | ---
dataset_info:
- config_name: subset_1
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 392397221.989
num_examples: 2081
download_size: 386957004
dataset_size: 392397221.989
- config_name: subset_10
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 351659087.73
num_examples: 1965
download_size: 347647106
dataset_size: 351659087.73
- config_name: subset_100
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 347439311.634
num_examples: 1763
download_size: 344710645
dataset_size: 347439311.634
- config_name: subset_101
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 365547481.5
num_examples: 1875
download_size: 362661933
dataset_size: 365547481.5
- config_name: subset_102
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381968578.736
num_examples: 1881
download_size: 378806119
dataset_size: 381968578.736
- config_name: subset_103
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377107099.288
num_examples: 1892
download_size: 376129169
dataset_size: 377107099.288
- config_name: subset_104
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381521507.888
num_examples: 1906
download_size: 373259505
dataset_size: 381521507.888
- config_name: subset_105
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 368079639.417
num_examples: 1883
download_size: 369775684
dataset_size: 368079639.417
- config_name: subset_106
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 372391250.272
num_examples: 1892
download_size: 371305914
dataset_size: 372391250.272
- config_name: subset_107
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 367981287.206
num_examples: 1858
download_size: 367316048
dataset_size: 367981287.206
- config_name: subset_108
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 370223944.467
num_examples: 1841
download_size: 372346370
dataset_size: 370223944.467
- config_name: subset_109
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 357015475.43
num_examples: 1785
download_size: 352298722
dataset_size: 357015475.43
- config_name: subset_11
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 315461317.835
num_examples: 1785
download_size: 317212663
dataset_size: 315461317.835
- config_name: subset_110
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 385144074.155
num_examples: 1915
download_size: 379037748
dataset_size: 385144074.155
- config_name: subset_111
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 374935612.104
num_examples: 1892
download_size: 372239748
dataset_size: 374935612.104
- config_name: subset_112
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 387721101.719
num_examples: 1927
download_size: 383839213
dataset_size: 387721101.719
- config_name: subset_113
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 379212576.24
num_examples: 1934
download_size: 378453943
dataset_size: 379212576.24
- config_name: subset_114
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 384159658.67
num_examples: 1955
download_size: 384669279
dataset_size: 384159658.67
- config_name: subset_115
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377452879.389
num_examples: 1909
download_size: 376371193
dataset_size: 377452879.389
- config_name: subset_116
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 391109792.769
num_examples: 1919
download_size: 383604460
dataset_size: 391109792.769
- config_name: subset_117
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381047288.968
num_examples: 1904
download_size: 376450557
dataset_size: 381047288.968
- config_name: subset_118
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 382181426.2
num_examples: 1920
download_size: 385299598
dataset_size: 382181426.2
- config_name: subset_119
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 378101700.56
num_examples: 1874
download_size: 376758439
dataset_size: 378101700.56
- config_name: subset_12
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 358314567.44
num_examples: 1927
download_size: 352456885
dataset_size: 358314567.44
- config_name: subset_120
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 359954090.328
num_examples: 1784
download_size: 356979013
dataset_size: 359954090.328
- config_name: subset_121
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 376331279.186
num_examples: 1902
download_size: 380547371
dataset_size: 376331279.186
- config_name: subset_122
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369654334.356
num_examples: 1862
download_size: 371179800
dataset_size: 369654334.356
- config_name: subset_123
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 388541568.145
num_examples: 1929
download_size: 389026218
dataset_size: 388541568.145
- config_name: subset_124
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 379776241.785
num_examples: 1895
download_size: 378850414
dataset_size: 379776241.785
- config_name: subset_125
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 389122249.73
num_examples: 1938
download_size: 384996217
dataset_size: 389122249.73
- config_name: subset_126
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 379184588.31
num_examples: 1914
download_size: 373563947
dataset_size: 379184588.31
- config_name: subset_127
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 378141523.803
num_examples: 1907
download_size: 383375289
dataset_size: 378141523.803
- config_name: subset_128
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377769554.88
num_examples: 1895
download_size: 376653550
dataset_size: 377769554.88
- config_name: subset_129
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 353562633.516
num_examples: 1756
download_size: 354226686
dataset_size: 353562633.516
- config_name: subset_13
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 317069015.599
num_examples: 1777
download_size: 321144002
dataset_size: 317069015.599
- config_name: subset_130
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 370915893.668
num_examples: 1839
download_size: 371889303
dataset_size: 370915893.668
- config_name: subset_131
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 375004158.552
num_examples: 1888
download_size: 380782590
dataset_size: 375004158.552
- config_name: subset_132
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 388826866.976
num_examples: 1928
download_size: 382856675
dataset_size: 388826866.976
- config_name: subset_133
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 372116703.19
num_examples: 1894
download_size: 372237148
dataset_size: 372116703.19
- config_name: subset_134
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 386208157.937
num_examples: 1917
download_size: 383730732
dataset_size: 386208157.937
- config_name: subset_135
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381640691.498
num_examples: 1899
download_size: 380239839
dataset_size: 381640691.498
- config_name: subset_136
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 378631953.776
num_examples: 1888
download_size: 375946111
dataset_size: 378631953.776
- config_name: subset_137
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 374309454.612
num_examples: 1876
download_size: 373714310
dataset_size: 374309454.612
- config_name: subset_138
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 371147813.535
num_examples: 1871
download_size: 371796840
dataset_size: 371147813.535
- config_name: subset_139
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 366916855.865
num_examples: 1861
download_size: 368992793
dataset_size: 366916855.865
- config_name: subset_14
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 315585865.88
num_examples: 1741
download_size: 315277855
dataset_size: 315585865.88
- config_name: subset_140
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 363171291.466
num_examples: 1773
download_size: 358358262
dataset_size: 363171291.466
- config_name: subset_141
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 383956900.416
num_examples: 1872
download_size: 380114135
dataset_size: 383956900.416
- config_name: subset_142
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381078393.54
num_examples: 1906
download_size: 380218832
dataset_size: 381078393.54
- config_name: subset_143
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 380967934.34
num_examples: 1901
download_size: 379622210
dataset_size: 380967934.34
- config_name: subset_144
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 284053361.18
num_examples: 1391
download_size: 281375275
dataset_size: 284053361.18
- config_name: subset_15
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 345703994.68
num_examples: 1920
download_size: 347443074
dataset_size: 345703994.68
- config_name: subset_16
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 331502387.256
num_examples: 1874
download_size: 330665924
dataset_size: 331502387.256
- config_name: subset_17
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 345364118.622
num_examples: 1894
download_size: 345895501
dataset_size: 345364118.622
- config_name: subset_18
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 349524837.675
num_examples: 1955
download_size: 357408084
dataset_size: 349524837.675
- config_name: subset_19
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 346525218.4
num_examples: 1920
download_size: 345890982
dataset_size: 346525218.4
- config_name: subset_2
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 362488104.758
num_examples: 1934
download_size: 354865280
dataset_size: 362488104.758
- config_name: subset_20
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 350939026.25
num_examples: 1885
download_size: 341990731
dataset_size: 350939026.25
- config_name: subset_21
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 341215066.124
num_examples: 1774
download_size: 331849670
dataset_size: 341215066.124
- config_name: subset_22
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 336975532.536
num_examples: 1861
download_size: 335041433
dataset_size: 336975532.536
- config_name: subset_23
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 328915586.396
num_examples: 1794
download_size: 328763242
dataset_size: 328915586.396
- config_name: subset_24
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 332737609.168
num_examples: 1762
download_size: 325215649
dataset_size: 332737609.168
- config_name: subset_25
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 358862142.102
num_examples: 1907
download_size: 362106233
dataset_size: 358862142.102
- config_name: subset_26
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 358705148.232
num_examples: 1948
download_size: 353341914
dataset_size: 358705148.232
- config_name: subset_27
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 355566098.624
num_examples: 1928
download_size: 353149576
dataset_size: 355566098.624
- config_name: subset_28
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 365815404.452
num_examples: 1922
download_size: 356156160
dataset_size: 365815404.452
- config_name: subset_29
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 354934591.488
num_examples: 1952
download_size: 354608609
dataset_size: 354934591.488
- config_name: subset_3
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 346798563.768
num_examples: 1904
download_size: 343495987
dataset_size: 346798563.768
- config_name: subset_30
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 361155095.104
num_examples: 1907
download_size: 354721798
dataset_size: 361155095.104
- config_name: subset_31
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 335059745.876
num_examples: 1814
download_size: 340653641
dataset_size: 335059745.876
- config_name: subset_32
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 337790342.508
num_examples: 1804
download_size: 337683645
dataset_size: 337790342.508
- config_name: subset_33
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 334395079.204
num_examples: 1766
download_size: 333195229
dataset_size: 334395079.204
- config_name: subset_34
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 352353817.407
num_examples: 1897
download_size: 353893909
dataset_size: 352353817.407
- config_name: subset_35
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 354852096.8
num_examples: 1935
download_size: 354770966
dataset_size: 354852096.8
- config_name: subset_36
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 344032713.228
num_examples: 1868
download_size: 348221349
dataset_size: 344032713.228
- config_name: subset_37
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 355957197.391
num_examples: 1893
download_size: 353589260
dataset_size: 355957197.391
- config_name: subset_38
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 359951388.335
num_examples: 1901
download_size: 359991079
dataset_size: 359951388.335
- config_name: subset_39
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 355950399.686
num_examples: 1906
download_size: 351954997
dataset_size: 355950399.686
- config_name: subset_4
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 324875597.44
num_examples: 1840
download_size: 323033218
dataset_size: 324875597.44
- config_name: subset_40
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 359980567.238
num_examples: 1938
download_size: 361203498
dataset_size: 359980567.238
- config_name: subset_41
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 341491079.89
num_examples: 1795
download_size: 342598966
dataset_size: 341491079.89
- config_name: subset_42
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 337050840.36
num_examples: 1810
download_size: 338982181
dataset_size: 337050840.36
- config_name: subset_43
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 333078752.306
num_examples: 1762
download_size: 331973425
dataset_size: 333078752.306
- config_name: subset_44
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 354837353.808
num_examples: 1836
download_size: 352414746
dataset_size: 354837353.808
- config_name: subset_45
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 355504571.626
num_examples: 1897
download_size: 351898298
dataset_size: 355504571.626
- config_name: subset_46
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 366453524.485
num_examples: 1899
download_size: 361219728
dataset_size: 366453524.485
- config_name: subset_47
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369537229.91
num_examples: 1910
download_size: 366818569
dataset_size: 369537229.91
- config_name: subset_48
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 371055917.565
num_examples: 1921
download_size: 364934935
dataset_size: 371055917.565
- config_name: subset_49
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 365111049.931
num_examples: 1883
download_size: 363378366
dataset_size: 365111049.931
- config_name: subset_5
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 359687039.651
num_examples: 1997
download_size: 355215716
dataset_size: 359687039.651
- config_name: subset_50
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 363903197.66
num_examples: 1956
download_size: 369802089
dataset_size: 363903197.66
- config_name: subset_51
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 349528411.223
num_examples: 1767
download_size: 345586795
dataset_size: 349528411.223
- config_name: subset_52
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 350742328.126
num_examples: 1787
download_size: 347735026
dataset_size: 350742328.126
- config_name: subset_53
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 355375693.046
num_examples: 1854
download_size: 358497900
dataset_size: 355375693.046
- config_name: subset_54
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 331900210.526
num_examples: 1731
download_size: 335241695
dataset_size: 331900210.526
- config_name: subset_55
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 358310697.212
num_examples: 1874
download_size: 356550085
dataset_size: 358310697.212
- config_name: subset_56
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 370320570.7
num_examples: 1900
download_size: 368953320
dataset_size: 370320570.7
- config_name: subset_57
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369177867.17
num_examples: 1930
download_size: 365431010
dataset_size: 369177867.17
- config_name: subset_58
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 364750512.24
num_examples: 1915
download_size: 359038523
dataset_size: 364750512.24
- config_name: subset_59
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 366063836.56
num_examples: 1896
download_size: 361919269
dataset_size: 366063836.56
- config_name: subset_6
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 330620046.596
num_examples: 1814
download_size: 324933334
dataset_size: 330620046.596
- config_name: subset_60
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 362027807.292
num_examples: 1919
download_size: 368443865
dataset_size: 362027807.292
- config_name: subset_61
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 336572343.386
num_examples: 1743
download_size: 336203973
dataset_size: 336572343.386
- config_name: subset_62
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 347496680.375
num_examples: 1795
download_size: 344109877
dataset_size: 347496680.375
- config_name: subset_63
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 352974912.662
num_examples: 1798
download_size: 350775013
dataset_size: 352974912.662
- config_name: subset_64
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 353464515.368
num_examples: 1817
download_size: 352635014
dataset_size: 353464515.368
- config_name: subset_65
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 363826523.188
num_examples: 1884
download_size: 363596840
dataset_size: 363826523.188
- config_name: subset_66
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 370086286.518
num_examples: 1894
download_size: 366106457
dataset_size: 370086286.518
- config_name: subset_67
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 367206754.248
num_examples: 1883
download_size: 363308659
dataset_size: 367206754.248
- config_name: subset_68
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369958948.708
num_examples: 1916
download_size: 375430648
dataset_size: 369958948.708
- config_name: subset_69
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377933959.326
num_examples: 1922
download_size: 371490261
dataset_size: 377933959.326
- config_name: subset_7
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 330330927.696
num_examples: 1836
download_size: 329514575
dataset_size: 330330927.696
- config_name: subset_70
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 372167954.944
num_examples: 1908
download_size: 367229781
dataset_size: 372167954.944
- config_name: subset_71
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 340415056.848
num_examples: 1748
download_size: 342450661
dataset_size: 340415056.848
- config_name: subset_72
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 378986780.672
num_examples: 1894
download_size: 374832652
dataset_size: 378986780.672
- config_name: subset_73
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 340998735.385
num_examples: 1743
download_size: 339125356
dataset_size: 340998735.385
- config_name: subset_74
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 366140124.688
num_examples: 1832
download_size: 359991384
dataset_size: 366140124.688
- config_name: subset_75
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 360268108.16
num_examples: 1868
download_size: 367867795
dataset_size: 360268108.16
- config_name: subset_76
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 365777697.252
num_examples: 1919
download_size: 370998271
dataset_size: 365777697.252
- config_name: subset_77
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 367151012.651
num_examples: 1907
download_size: 370795072
dataset_size: 367151012.651
- config_name: subset_78
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 367935265.25
num_examples: 1875
download_size: 368403671
dataset_size: 367935265.25
- config_name: subset_79
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 370145543.78
num_examples: 1905
download_size: 365886501
dataset_size: 370145543.78
- config_name: subset_8
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 361935515.97
num_examples: 2010
download_size: 353248114
dataset_size: 361935515.97
- config_name: subset_80
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 368484664.482
num_examples: 1886
download_size: 363208555
dataset_size: 368484664.482
- config_name: subset_81
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 382681091.404
num_examples: 1922
download_size: 378494301
dataset_size: 382681091.404
- config_name: subset_82
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 376125305.856
num_examples: 1912
download_size: 376672124
dataset_size: 376125305.856
- config_name: subset_83
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 371577857.09
num_examples: 1893
download_size: 369316183
dataset_size: 371577857.09
- config_name: subset_84
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369560463.322
num_examples: 1874
download_size: 365140195
dataset_size: 369560463.322
- config_name: subset_85
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 364358029.998
num_examples: 1889
download_size: 364548198
dataset_size: 364358029.998
- config_name: subset_86
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 376636073.672
num_examples: 1872
download_size: 373150870
dataset_size: 376636073.672
- config_name: subset_87
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 362562530.995
num_examples: 1905
download_size: 369354649
dataset_size: 362562530.995
- config_name: subset_88
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 381751130.869
num_examples: 1909
download_size: 373678648
dataset_size: 381751130.869
- config_name: subset_89
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 371633741.0
num_examples: 1895
download_size: 372501566
dataset_size: 371633741.0
- config_name: subset_9
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 348422943.515
num_examples: 1985
download_size: 351519803
dataset_size: 348422943.515
- config_name: subset_90
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 373825088.18
num_examples: 1924
download_size: 375226691
dataset_size: 373825088.18
- config_name: subset_91
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 373896143.252
num_examples: 1922
download_size: 374160814
dataset_size: 373896143.252
- config_name: subset_92
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 364351588.28
num_examples: 1890
download_size: 365888274
dataset_size: 364351588.28
- config_name: subset_93
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 387866261.842
num_examples: 1881
download_size: 375615708
dataset_size: 387866261.842
- config_name: subset_94
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377305622.574
num_examples: 1907
download_size: 373264809
dataset_size: 377305622.574
- config_name: subset_95
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 369064503.5
num_examples: 1875
download_size: 367451772
dataset_size: 369064503.5
- config_name: subset_96
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 377780781.221
num_examples: 1903
download_size: 378226431
dataset_size: 377780781.221
- config_name: subset_97
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 373154202.246
num_examples: 1906
download_size: 376439653
dataset_size: 373154202.246
- config_name: subset_98
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 368477992.163
num_examples: 1911
download_size: 374903560
dataset_size: 368477992.163
- config_name: subset_99
features:
- name: enA.audio
dtype: audio
- name: jaA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 380696639.606
num_examples: 1907
download_size: 380352674
dataset_size: 380696639.606
- config_name: subset_test
features:
- name: jaA.audio
dtype: audio
- name: enA.audio
dtype: audio
- name: line_no
dtype: int64
- name: enA.id
dtype: string
- name: enA.url
dtype: string
- name: enA.duration_start
dtype: int64
- name: enA.duration_end
dtype: int64
- name: enA.laser_score
dtype: float64
- name: jaA.id
dtype: string
- name: jaA.url
dtype: string
- name: jaA.duration_start
dtype: int64
- name: jaA.duration_end
dtype: int64
- name: jaA.laser_score
dtype: float64
splits:
- name: train
num_bytes: 1530085.0
num_examples: 8
download_size: 1506623
dataset_size: 1530085.0
configs:
- config_name: subset_1
data_files:
- split: train
path: subset_1/train-*
- config_name: subset_10
data_files:
- split: train
path: subset_10/train-*
- config_name: subset_100
data_files:
- split: train
path: subset_100/train-*
- config_name: subset_101
data_files:
- split: train
path: subset_101/train-*
- config_name: subset_102
data_files:
- split: train
path: subset_102/train-*
- config_name: subset_103
data_files:
- split: train
path: subset_103/train-*
- config_name: subset_104
data_files:
- split: train
path: subset_104/train-*
- config_name: subset_105
data_files:
- split: train
path: subset_105/train-*
- config_name: subset_106
data_files:
- split: train
path: subset_106/train-*
- config_name: subset_107
data_files:
- split: train
path: subset_107/train-*
- config_name: subset_108
data_files:
- split: train
path: subset_108/train-*
- config_name: subset_109
data_files:
- split: train
path: subset_109/train-*
- config_name: subset_11
data_files:
- split: train
path: subset_11/train-*
- config_name: subset_110
data_files:
- split: train
path: subset_110/train-*
- config_name: subset_111
data_files:
- split: train
path: subset_111/train-*
- config_name: subset_112
data_files:
- split: train
path: subset_112/train-*
- config_name: subset_113
data_files:
- split: train
path: subset_113/train-*
- config_name: subset_114
data_files:
- split: train
path: subset_114/train-*
- config_name: subset_115
data_files:
- split: train
path: subset_115/train-*
- config_name: subset_116
data_files:
- split: train
path: subset_116/train-*
- config_name: subset_117
data_files:
- split: train
path: subset_117/train-*
- config_name: subset_118
data_files:
- split: train
path: subset_118/train-*
- config_name: subset_119
data_files:
- split: train
path: subset_119/train-*
- config_name: subset_12
data_files:
- split: train
path: subset_12/train-*
- config_name: subset_120
data_files:
- split: train
path: subset_120/train-*
- config_name: subset_121
data_files:
- split: train
path: subset_121/train-*
- config_name: subset_122
data_files:
- split: train
path: subset_122/train-*
- config_name: subset_123
data_files:
- split: train
path: subset_123/train-*
- config_name: subset_124
data_files:
- split: train
path: subset_124/train-*
- config_name: subset_125
data_files:
- split: train
path: subset_125/train-*
- config_name: subset_126
data_files:
- split: train
path: subset_126/train-*
- config_name: subset_127
data_files:
- split: train
path: subset_127/train-*
- config_name: subset_128
data_files:
- split: train
path: subset_128/train-*
- config_name: subset_129
data_files:
- split: train
path: subset_129/train-*
- config_name: subset_13
data_files:
- split: train
path: subset_13/train-*
- config_name: subset_130
data_files:
- split: train
path: subset_130/train-*
- config_name: subset_131
data_files:
- split: train
path: subset_131/train-*
- config_name: subset_132
data_files:
- split: train
path: subset_132/train-*
- config_name: subset_133
data_files:
- split: train
path: subset_133/train-*
- config_name: subset_134
data_files:
- split: train
path: subset_134/train-*
- config_name: subset_135
data_files:
- split: train
path: subset_135/train-*
- config_name: subset_136
data_files:
- split: train
path: subset_136/train-*
- config_name: subset_137
data_files:
- split: train
path: subset_137/train-*
- config_name: subset_138
data_files:
- split: train
path: subset_138/train-*
- config_name: subset_139
data_files:
- split: train
path: subset_139/train-*
- config_name: subset_14
data_files:
- split: train
path: subset_14/train-*
- config_name: subset_140
data_files:
- split: train
path: subset_140/train-*
- config_name: subset_141
data_files:
- split: train
path: subset_141/train-*
- config_name: subset_142
data_files:
- split: train
path: subset_142/train-*
- config_name: subset_143
data_files:
- split: train
path: subset_143/train-*
- config_name: subset_144
data_files:
- split: train
path: subset_144/train-*
- config_name: subset_15
data_files:
- split: train
path: subset_15/train-*
- config_name: subset_16
data_files:
- split: train
path: subset_16/train-*
- config_name: subset_17
data_files:
- split: train
path: subset_17/train-*
- config_name: subset_18
data_files:
- split: train
path: subset_18/train-*
- config_name: subset_19
data_files:
- split: train
path: subset_19/train-*
- config_name: subset_2
data_files:
- split: train
path: subset_2/train-*
- config_name: subset_20
data_files:
- split: train
path: subset_20/train-*
- config_name: subset_21
data_files:
- split: train
path: subset_21/train-*
- config_name: subset_22
data_files:
- split: train
path: subset_22/train-*
- config_name: subset_23
data_files:
- split: train
path: subset_23/train-*
- config_name: subset_24
data_files:
- split: train
path: subset_24/train-*
- config_name: subset_25
data_files:
- split: train
path: subset_25/train-*
- config_name: subset_26
data_files:
- split: train
path: subset_26/train-*
- config_name: subset_27
data_files:
- split: train
path: subset_27/train-*
- config_name: subset_28
data_files:
- split: train
path: subset_28/train-*
- config_name: subset_29
data_files:
- split: train
path: subset_29/train-*
- config_name: subset_3
data_files:
- split: train
path: subset_3/train-*
- config_name: subset_30
data_files:
- split: train
path: subset_30/train-*
- config_name: subset_31
data_files:
- split: train
path: subset_31/train-*
- config_name: subset_32
data_files:
- split: train
path: subset_32/train-*
- config_name: subset_33
data_files:
- split: train
path: subset_33/train-*
- config_name: subset_34
data_files:
- split: train
path: subset_34/train-*
- config_name: subset_35
data_files:
- split: train
path: subset_35/train-*
- config_name: subset_36
data_files:
- split: train
path: subset_36/train-*
- config_name: subset_37
data_files:
- split: train
path: subset_37/train-*
- config_name: subset_38
data_files:
- split: train
path: subset_38/train-*
- config_name: subset_39
data_files:
- split: train
path: subset_39/train-*
- config_name: subset_4
data_files:
- split: train
path: subset_4/train-*
- config_name: subset_40
data_files:
- split: train
path: subset_40/train-*
- config_name: subset_41
data_files:
- split: train
path: subset_41/train-*
- config_name: subset_42
data_files:
- split: train
path: subset_42/train-*
- config_name: subset_43
data_files:
- split: train
path: subset_43/train-*
- config_name: subset_44
data_files:
- split: train
path: subset_44/train-*
- config_name: subset_45
data_files:
- split: train
path: subset_45/train-*
- config_name: subset_46
data_files:
- split: train
path: subset_46/train-*
- config_name: subset_47
data_files:
- split: train
path: subset_47/train-*
- config_name: subset_48
data_files:
- split: train
path: subset_48/train-*
- config_name: subset_49
data_files:
- split: train
path: subset_49/train-*
- config_name: subset_5
data_files:
- split: train
path: subset_5/train-*
- config_name: subset_50
data_files:
- split: train
path: subset_50/train-*
- config_name: subset_51
data_files:
- split: train
path: subset_51/train-*
- config_name: subset_52
data_files:
- split: train
path: subset_52/train-*
- config_name: subset_53
data_files:
- split: train
path: subset_53/train-*
- config_name: subset_54
data_files:
- split: train
path: subset_54/train-*
- config_name: subset_55
data_files:
- split: train
path: subset_55/train-*
- config_name: subset_56
data_files:
- split: train
path: subset_56/train-*
- config_name: subset_57
data_files:
- split: train
path: subset_57/train-*
- config_name: subset_58
data_files:
- split: train
path: subset_58/train-*
- config_name: subset_59
data_files:
- split: train
path: subset_59/train-*
- config_name: subset_6
data_files:
- split: train
path: subset_6/train-*
- config_name: subset_60
data_files:
- split: train
path: subset_60/train-*
- config_name: subset_61
data_files:
- split: train
path: subset_61/train-*
- config_name: subset_62
data_files:
- split: train
path: subset_62/train-*
- config_name: subset_63
data_files:
- split: train
path: subset_63/train-*
- config_name: subset_64
data_files:
- split: train
path: subset_64/train-*
- config_name: subset_65
data_files:
- split: train
path: subset_65/train-*
- config_name: subset_66
data_files:
- split: train
path: subset_66/train-*
- config_name: subset_67
data_files:
- split: train
path: subset_67/train-*
- config_name: subset_68
data_files:
- split: train
path: subset_68/train-*
- config_name: subset_69
data_files:
- split: train
path: subset_69/train-*
- config_name: subset_7
data_files:
- split: train
path: subset_7/train-*
- config_name: subset_70
data_files:
- split: train
path: subset_70/train-*
- config_name: subset_71
data_files:
- split: train
path: subset_71/train-*
- config_name: subset_72
data_files:
- split: train
path: subset_72/train-*
- config_name: subset_73
data_files:
- split: train
path: subset_73/train-*
- config_name: subset_74
data_files:
- split: train
path: subset_74/train-*
- config_name: subset_75
data_files:
- split: train
path: subset_75/train-*
- config_name: subset_76
data_files:
- split: train
path: subset_76/train-*
- config_name: subset_77
data_files:
- split: train
path: subset_77/train-*
- config_name: subset_78
data_files:
- split: train
path: subset_78/train-*
- config_name: subset_79
data_files:
- split: train
path: subset_79/train-*
- config_name: subset_8
data_files:
- split: train
path: subset_8/train-*
- config_name: subset_80
data_files:
- split: train
path: subset_80/train-*
- config_name: subset_81
data_files:
- split: train
path: subset_81/train-*
- config_name: subset_82
data_files:
- split: train
path: subset_82/train-*
- config_name: subset_83
data_files:
- split: train
path: subset_83/train-*
- config_name: subset_84
data_files:
- split: train
path: subset_84/train-*
- config_name: subset_85
data_files:
- split: train
path: subset_85/train-*
- config_name: subset_86
data_files:
- split: train
path: subset_86/train-*
- config_name: subset_87
data_files:
- split: train
path: subset_87/train-*
- config_name: subset_88
data_files:
- split: train
path: subset_88/train-*
- config_name: subset_89
data_files:
- split: train
path: subset_89/train-*
- config_name: subset_9
data_files:
- split: train
path: subset_9/train-*
- config_name: subset_90
data_files:
- split: train
path: subset_90/train-*
- config_name: subset_91
data_files:
- split: train
path: subset_91/train-*
- config_name: subset_92
data_files:
- split: train
path: subset_92/train-*
- config_name: subset_93
data_files:
- split: train
path: subset_93/train-*
- config_name: subset_94
data_files:
- split: train
path: subset_94/train-*
- config_name: subset_95
data_files:
- split: train
path: subset_95/train-*
- config_name: subset_96
data_files:
- split: train
path: subset_96/train-*
- config_name: subset_97
data_files:
- split: train
path: subset_97/train-*
- config_name: subset_98
data_files:
- split: train
path: subset_98/train-*
- config_name: subset_99
data_files:
- split: train
path: subset_99/train-*
- config_name: subset_test
data_files:
- split: train
path: subset_test/train-*
---
|
jlbaker361/fashion | jlbaker361 | "2024-05-27T14:38:43Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:38:40Z" | ---
dataset_info:
features:
- name: subject
dtype: string
- name: splash
dtype: image
splits:
- name: train
num_bytes: 88258039.0
num_examples: 2032
download_size: 87513588
dataset_size: 88258039.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
fresvyx/indo-llama2 | fresvyx | "2024-05-27T14:44:45Z" | 0 | 0 | [
"language:id",
"size_categories:1K<n<10K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:43:35Z" | ---
language:
- id
--- |
OALL/details_Artples__L-MChat-Small | OALL | "2024-05-27T14:43:58Z" | 0 | 0 | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:43:40Z" | ---
pretty_name: Evaluation run of Artples/L-MChat-Small
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Artples/L-MChat-Small](https://huggingface.co/Artples/L-MChat-Small).\n\nThe\
\ dataset is composed of 136 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.\n\nTo load the details from a run, you can for instance do the following:\n\
```python\nfrom datasets import load_dataset\ndata = load_dataset(\"OALL/details_Artples__L-MChat-Small\"\
,\n\t\"lighteval_xstory_cloze_ar_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2024-05-27T14:39:45.128547](https://huggingface.co/datasets/OALL/details_Artples__L-MChat-Small/blob/main/results_2024-05-27T14-39-45.128547.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_norm\": 0.3996877363610559,\n\
\ \"acc_norm_stderr\": 0.0363328445153769,\n \"acc\": 0.47187293183322304,\n\
\ \"acc_stderr\": 0.012846749995797692\n },\n \"community|acva:Algeria|0\"\
: {\n \"acc_norm\": 0.48717948717948717,\n \"acc_norm_stderr\": 0.03588610523192216\n\
\ },\n \"community|acva:Ancient_Egypt|0\": {\n \"acc_norm\": 0.9015873015873016,\n\
\ \"acc_norm_stderr\": 0.01680988100419675\n },\n \"community|acva:Arab_Empire|0\"\
: {\n \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118634\n\
\ },\n \"community|acva:Arabic_Architecture|0\": {\n \"acc_norm\":\
\ 0.5333333333333333,\n \"acc_norm_stderr\": 0.03581804596782233\n },\n\
\ \"community|acva:Arabic_Art|0\": {\n \"acc_norm\": 0.6512820512820513,\n\
\ \"acc_norm_stderr\": 0.034215338466705415\n },\n \"community|acva:Arabic_Astronomy|0\"\
: {\n \"acc_norm\": 0.5282051282051282,\n \"acc_norm_stderr\": 0.035840746749208334\n\
\ },\n \"community|acva:Arabic_Calligraphy|0\": {\n \"acc_norm\": 0.5137254901960784,\n\
\ \"acc_norm_stderr\": 0.0313609674469424\n },\n \"community|acva:Arabic_Ceremony|0\"\
: {\n \"acc_norm\": 0.4864864864864865,\n \"acc_norm_stderr\": 0.03684702401944814\n\
\ },\n \"community|acva:Arabic_Clothing|0\": {\n \"acc_norm\": 0.5025641025641026,\n\
\ \"acc_norm_stderr\": 0.035897435897435895\n },\n \"community|acva:Arabic_Culture|0\"\
: {\n \"acc_norm\": 0.7435897435897436,\n \"acc_norm_stderr\": 0.03134970994274493\n\
\ },\n \"community|acva:Arabic_Food|0\": {\n \"acc_norm\": 0.558974358974359,\n\
\ \"acc_norm_stderr\": 0.0356473293185358\n },\n \"community|acva:Arabic_Funeral|0\"\
: {\n \"acc_norm\": 0.5263157894736842,\n \"acc_norm_stderr\": 0.05149958471474543\n\
\ },\n \"community|acva:Arabic_Geography|0\": {\n \"acc_norm\": 0.41379310344827586,\n\
\ \"acc_norm_stderr\": 0.04104269211806232\n },\n \"community|acva:Arabic_History|0\"\
: {\n \"acc_norm\": 0.6820512820512821,\n \"acc_norm_stderr\": 0.03343383454355787\n\
\ },\n \"community|acva:Arabic_Language_Origin|0\": {\n \"acc_norm\"\
: 0.4842105263157895,\n \"acc_norm_stderr\": 0.05154534179593067\n },\n\
\ \"community|acva:Arabic_Literature|0\": {\n \"acc_norm\": 0.5310344827586206,\n\
\ \"acc_norm_stderr\": 0.04158632762097828\n },\n \"community|acva:Arabic_Math|0\"\
: {\n \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.03298070870085618\n\
\ },\n \"community|acva:Arabic_Medicine|0\": {\n \"acc_norm\": 0.5103448275862069,\n\
\ \"acc_norm_stderr\": 0.04165774775728763\n },\n \"community|acva:Arabic_Music|0\"\
: {\n \"acc_norm\": 0.7769784172661871,\n \"acc_norm_stderr\": 0.03543548499561939\n\
\ },\n \"community|acva:Arabic_Ornament|0\": {\n \"acc_norm\": 0.5333333333333333,\n\
\ \"acc_norm_stderr\": 0.03581804596782233\n },\n \"community|acva:Arabic_Philosophy|0\"\
: {\n \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.04154659671707548\n\
\ },\n \"community|acva:Arabic_Physics_and_Chemistry|0\": {\n \"acc_norm\"\
: 0.5076923076923077,\n \"acc_norm_stderr\": 0.03589365940635213\n },\n\
\ \"community|acva:Arabic_Wedding|0\": {\n \"acc_norm\": 0.6,\n \
\ \"acc_norm_stderr\": 0.035172622905632896\n },\n \"community|acva:Bahrain|0\"\
: {\n \"acc_norm\": 0.6888888888888889,\n \"acc_norm_stderr\": 0.06979205927323111\n\
\ },\n \"community|acva:Comoros|0\": {\n \"acc_norm\": 0.6222222222222222,\n\
\ \"acc_norm_stderr\": 0.07309112127323451\n },\n \"community|acva:Egypt_modern|0\"\
: {\n \"acc_norm\": 0.6736842105263158,\n \"acc_norm_stderr\": 0.04835966701461423\n\
\ },\n \"community|acva:InfluenceFromAncientEgypt|0\": {\n \"acc_norm\"\
: 0.39487179487179486,\n \"acc_norm_stderr\": 0.035095456022620375\n },\n\
\ \"community|acva:InfluenceFromByzantium|0\": {\n \"acc_norm\": 0.2827586206896552,\n\
\ \"acc_norm_stderr\": 0.03752833958003337\n },\n \"community|acva:InfluenceFromChina|0\"\
: {\n \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.03384487217112065\n\
\ },\n \"community|acva:InfluenceFromGreece|0\": {\n \"acc_norm\":\
\ 0.36923076923076925,\n \"acc_norm_stderr\": 0.034648411418637566\n },\n\
\ \"community|acva:InfluenceFromIslam|0\": {\n \"acc_norm\": 0.6896551724137931,\n\
\ \"acc_norm_stderr\": 0.03855289616378947\n },\n \"community|acva:InfluenceFromPersia|0\"\
: {\n \"acc_norm\": 0.3028571428571429,\n \"acc_norm_stderr\": 0.03483414676585985\n\
\ },\n \"community|acva:InfluenceFromRome|0\": {\n \"acc_norm\": 0.4307692307692308,\n\
\ \"acc_norm_stderr\": 0.035552132520587594\n },\n \"community|acva:Iraq|0\"\
: {\n \"acc_norm\": 0.5176470588235295,\n \"acc_norm_stderr\": 0.05452048340661897\n\
\ },\n \"community|acva:Islam_Education|0\": {\n \"acc_norm\": 0.558974358974359,\n\
\ \"acc_norm_stderr\": 0.03564732931853579\n },\n \"community|acva:Islam_branches_and_schools|0\"\
: {\n \"acc_norm\": 0.5028571428571429,\n \"acc_norm_stderr\": 0.037904283318347436\n\
\ },\n \"community|acva:Islamic_law_system|0\": {\n \"acc_norm\": 0.5948717948717949,\n\
\ \"acc_norm_stderr\": 0.03524577495610961\n },\n \"community|acva:Jordan|0\"\
: {\n \"acc_norm\": 0.6444444444444445,\n \"acc_norm_stderr\": 0.07216392363431012\n\
\ },\n \"community|acva:Kuwait|0\": {\n \"acc_norm\": 0.6888888888888889,\n\
\ \"acc_norm_stderr\": 0.06979205927323111\n },\n \"community|acva:Lebanon|0\"\
: {\n \"acc_norm\": 0.7333333333333333,\n \"acc_norm_stderr\": 0.06666666666666668\n\
\ },\n \"community|acva:Libya|0\": {\n \"acc_norm\": 0.5333333333333333,\n\
\ \"acc_norm_stderr\": 0.0752101433090355\n },\n \"community|acva:Mauritania|0\"\
: {\n \"acc_norm\": 0.5333333333333333,\n \"acc_norm_stderr\": 0.0752101433090355\n\
\ },\n \"community|acva:Mesopotamia_civilization|0\": {\n \"acc_norm\"\
: 0.49032258064516127,\n \"acc_norm_stderr\": 0.04028360076525542\n },\n\
\ \"community|acva:Morocco|0\": {\n \"acc_norm\": 0.7555555555555555,\n\
\ \"acc_norm_stderr\": 0.06478835438717\n },\n \"community|acva:Oman|0\"\
: {\n \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.06030226891555273\n\
\ },\n \"community|acva:Palestine|0\": {\n \"acc_norm\": 0.7411764705882353,\n\
\ \"acc_norm_stderr\": 0.04778846120374094\n },\n \"community|acva:Qatar|0\"\
: {\n \"acc_norm\": 0.5777777777777777,\n \"acc_norm_stderr\": 0.07446027270295806\n\
\ },\n \"community|acva:Saudi_Arabia|0\": {\n \"acc_norm\": 0.6717948717948717,\n\
\ \"acc_norm_stderr\": 0.03371243782413707\n },\n \"community|acva:Somalia|0\"\
: {\n \"acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.07491109582924915\n\
\ },\n \"community|acva:Sudan|0\": {\n \"acc_norm\": 0.6444444444444445,\n\
\ \"acc_norm_stderr\": 0.07216392363431012\n },\n \"community|acva:Syria|0\"\
: {\n \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.07106690545187012\n\
\ },\n \"community|acva:Tunisia|0\": {\n \"acc_norm\": 0.6444444444444445,\n\
\ \"acc_norm_stderr\": 0.07216392363431011\n },\n \"community|acva:United_Arab_Emirates|0\"\
: {\n \"acc_norm\": 0.7529411764705882,\n \"acc_norm_stderr\": 0.047058823529411785\n\
\ },\n \"community|acva:Yemen|0\": {\n \"acc_norm\": 0.6,\n \
\ \"acc_norm_stderr\": 0.16329931618554522\n },\n \"community|acva:communication|0\"\
: {\n \"acc_norm\": 0.5879120879120879,\n \"acc_norm_stderr\": 0.0258343667152563\n\
\ },\n \"community|acva:computer_and_phone|0\": {\n \"acc_norm\": 0.5389830508474577,\n\
\ \"acc_norm_stderr\": 0.0290718276412662\n },\n \"community|acva:daily_life|0\"\
: {\n \"acc_norm\": 0.7270029673590505,\n \"acc_norm_stderr\": 0.024303980960050656\n\
\ },\n \"community|acva:entertainment|0\": {\n \"acc_norm\": 0.711864406779661,\n\
\ \"acc_norm_stderr\": 0.026413346524541644\n },\n \"community|alghafa:mcq_exams_test_ar|0\"\
: {\n \"acc_norm\": 0.2513464991023339,\n \"acc_norm_stderr\": 0.01839668001069939\n\
\ },\n \"community|alghafa:meta_ar_dialects|0\": {\n \"acc_norm\":\
\ 0.24411492122335496,\n \"acc_norm_stderr\": 0.005848837806074586\n },\n\
\ \"community|alghafa:meta_ar_msa|0\": {\n \"acc_norm\": 0.24692737430167597,\n\
\ \"acc_norm_stderr\": 0.014422292204808836\n },\n \"community|alghafa:multiple_choice_facts_truefalse_balanced_task|0\"\
: {\n \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.05807730170189531\n\
\ },\n \"community|alghafa:multiple_choice_grounded_statement_soqal_task|0\"\
: {\n \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.03622779862191887\n\
\ },\n \"community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0\"\
: {\n \"acc_norm\": 0.24666666666666667,\n \"acc_norm_stderr\": 0.03531471376356937\n\
\ },\n \"community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0\"\
: {\n \"acc_norm\": 0.499812382739212,\n \"acc_norm_stderr\": 0.005592267043694276\n\
\ },\n \"community|alghafa:multiple_choice_rating_sentiment_task|0\": {\n\
\ \"acc_norm\": 0.3402835696413678,\n \"acc_norm_stderr\": 0.006119849906257789\n\
\ },\n \"community|alghafa:multiple_choice_sentiment_task|0\": {\n \
\ \"acc_norm\": 0.33372093023255817,\n \"acc_norm_stderr\": 0.011373178876838192\n\
\ },\n \"community|arabic_exams|0\": {\n \"acc_norm\": 0.2383612662942272,\n\
\ \"acc_norm_stderr\": 0.01840390396129298\n },\n \"community|arabic_mmlu:abstract_algebra|0\"\
: {\n \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n\
\ },\n \"community|arabic_mmlu:anatomy|0\": {\n \"acc_norm\": 0.18518518518518517,\n\
\ \"acc_norm_stderr\": 0.03355677216313142\n },\n \"community|arabic_mmlu:astronomy|0\"\
: {\n \"acc_norm\": 0.18421052631578946,\n \"acc_norm_stderr\": 0.0315469804508223\n\
\ },\n \"community|arabic_mmlu:business_ethics|0\": {\n \"acc_norm\"\
: 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"community|arabic_mmlu:clinical_knowledge|0\"\
: {\n \"acc_norm\": 0.21509433962264152,\n \"acc_norm_stderr\": 0.02528839450289137\n\
\ },\n \"community|arabic_mmlu:college_biology|0\": {\n \"acc_norm\"\
: 0.25,\n \"acc_norm_stderr\": 0.03621034121889507\n },\n \"community|arabic_mmlu:college_chemistry|0\"\
: {\n \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.039427724440366234\n\
\ },\n \"community|arabic_mmlu:college_computer_science|0\": {\n \"\
acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \
\ \"community|arabic_mmlu:college_mathematics|0\": {\n \"acc_norm\": 0.24,\n\
\ \"acc_norm_stderr\": 0.042923469599092816\n },\n \"community|arabic_mmlu:college_medicine|0\"\
: {\n \"acc_norm\": 0.2138728323699422,\n \"acc_norm_stderr\": 0.031265112061730445\n\
\ },\n \"community|arabic_mmlu:college_physics|0\": {\n \"acc_norm\"\
: 0.22549019607843138,\n \"acc_norm_stderr\": 0.041583075330832865\n },\n\
\ \"community|arabic_mmlu:computer_security|0\": {\n \"acc_norm\": 0.27,\n\
\ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"community|arabic_mmlu:conceptual_physics|0\"\
: {\n \"acc_norm\": 0.2723404255319149,\n \"acc_norm_stderr\": 0.029101290698386698\n\
\ },\n \"community|arabic_mmlu:econometrics|0\": {\n \"acc_norm\":\
\ 0.2719298245614035,\n \"acc_norm_stderr\": 0.04185774424022056\n },\n\
\ \"community|arabic_mmlu:electrical_engineering|0\": {\n \"acc_norm\"\
: 0.25517241379310346,\n \"acc_norm_stderr\": 0.03632984052707842\n },\n\
\ \"community|arabic_mmlu:elementary_mathematics|0\": {\n \"acc_norm\"\
: 0.21164021164021163,\n \"acc_norm_stderr\": 0.021037331505262886\n },\n\
\ \"community|arabic_mmlu:formal_logic|0\": {\n \"acc_norm\": 0.2619047619047619,\n\
\ \"acc_norm_stderr\": 0.03932537680392872\n },\n \"community|arabic_mmlu:global_facts|0\"\
: {\n \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.039427724440366234\n\
\ },\n \"community|arabic_mmlu:high_school_biology|0\": {\n \"acc_norm\"\
: 0.18064516129032257,\n \"acc_norm_stderr\": 0.021886178567172548\n },\n\
\ \"community|arabic_mmlu:high_school_chemistry|0\": {\n \"acc_norm\"\
: 0.1724137931034483,\n \"acc_norm_stderr\": 0.026577672183036572\n },\n\
\ \"community|arabic_mmlu:high_school_computer_science|0\": {\n \"acc_norm\"\
: 0.22,\n \"acc_norm_stderr\": 0.041633319989322716\n },\n \"community|arabic_mmlu:high_school_european_history|0\"\
: {\n \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\
\ },\n \"community|arabic_mmlu:high_school_geography|0\": {\n \"acc_norm\"\
: 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n },\n\
\ \"community|arabic_mmlu:high_school_government_and_politics|0\": {\n \
\ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\
\ },\n \"community|arabic_mmlu:high_school_macroeconomics|0\": {\n \
\ \"acc_norm\": 0.19743589743589743,\n \"acc_norm_stderr\": 0.020182646968674844\n\
\ },\n \"community|arabic_mmlu:high_school_mathematics|0\": {\n \"\
acc_norm\": 0.22592592592592592,\n \"acc_norm_stderr\": 0.02549753263960955\n\
\ },\n \"community|arabic_mmlu:high_school_microeconomics|0\": {\n \
\ \"acc_norm\": 0.21428571428571427,\n \"acc_norm_stderr\": 0.026653531596715494\n\
\ },\n \"community|arabic_mmlu:high_school_physics|0\": {\n \"acc_norm\"\
: 0.2052980132450331,\n \"acc_norm_stderr\": 0.03297986648473836\n },\n\
\ \"community|arabic_mmlu:high_school_psychology|0\": {\n \"acc_norm\"\
: 0.1889908256880734,\n \"acc_norm_stderr\": 0.01678548115920364\n },\n\
\ \"community|arabic_mmlu:high_school_statistics|0\": {\n \"acc_norm\"\
: 0.1574074074074074,\n \"acc_norm_stderr\": 0.024837173518242387\n },\n\
\ \"community|arabic_mmlu:high_school_us_history|0\": {\n \"acc_norm\"\
: 0.25,\n \"acc_norm_stderr\": 0.03039153369274154\n },\n \"community|arabic_mmlu:high_school_world_history|0\"\
: {\n \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\
\ },\n \"community|arabic_mmlu:human_aging|0\": {\n \"acc_norm\": 0.29596412556053814,\n\
\ \"acc_norm_stderr\": 0.030636591348699813\n },\n \"community|arabic_mmlu:human_sexuality|0\"\
: {\n \"acc_norm\": 0.25190839694656486,\n \"acc_norm_stderr\": 0.03807387116306086\n\
\ },\n \"community|arabic_mmlu:international_law|0\": {\n \"acc_norm\"\
: 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n },\n\
\ \"community|arabic_mmlu:jurisprudence|0\": {\n \"acc_norm\": 0.26851851851851855,\n\
\ \"acc_norm_stderr\": 0.04284467968052192\n },\n \"community|arabic_mmlu:logical_fallacies|0\"\
: {\n \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\
\ },\n \"community|arabic_mmlu:machine_learning|0\": {\n \"acc_norm\"\
: 0.32142857142857145,\n \"acc_norm_stderr\": 0.04432804055291519\n },\n\
\ \"community|arabic_mmlu:management|0\": {\n \"acc_norm\": 0.17475728155339806,\n\
\ \"acc_norm_stderr\": 0.037601780060266224\n },\n \"community|arabic_mmlu:marketing|0\"\
: {\n \"acc_norm\": 0.3034188034188034,\n \"acc_norm_stderr\": 0.03011821010694267\n\
\ },\n \"community|arabic_mmlu:medical_genetics|0\": {\n \"acc_norm\"\
: 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"community|arabic_mmlu:miscellaneous|0\"\
: {\n \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.015302380123542089\n\
\ },\n \"community|arabic_mmlu:moral_disputes|0\": {\n \"acc_norm\"\
: 0.2514450867052023,\n \"acc_norm_stderr\": 0.02335736578587404\n },\n\
\ \"community|arabic_mmlu:moral_scenarios|0\": {\n \"acc_norm\": 0.23798882681564246,\n\
\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"community|arabic_mmlu:nutrition|0\"\
: {\n \"acc_norm\": 0.23202614379084968,\n \"acc_norm_stderr\": 0.02417084087934101\n\
\ },\n \"community|arabic_mmlu:philosophy|0\": {\n \"acc_norm\": 0.1864951768488746,\n\
\ \"acc_norm_stderr\": 0.02212243977248078\n },\n \"community|arabic_mmlu:prehistory|0\"\
: {\n \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.02289916291844581\n\
\ },\n \"community|arabic_mmlu:professional_accounting|0\": {\n \"\
acc_norm\": 0.24822695035460993,\n \"acc_norm_stderr\": 0.025770015644290396\n\
\ },\n \"community|arabic_mmlu:professional_law|0\": {\n \"acc_norm\"\
: 0.24511082138200782,\n \"acc_norm_stderr\": 0.010986307870045517\n },\n\
\ \"community|arabic_mmlu:professional_medicine|0\": {\n \"acc_norm\"\
: 0.19117647058823528,\n \"acc_norm_stderr\": 0.02388688192244034\n },\n\
\ \"community|arabic_mmlu:professional_psychology|0\": {\n \"acc_norm\"\
: 0.2549019607843137,\n \"acc_norm_stderr\": 0.017630827375148383\n },\n\
\ \"community|arabic_mmlu:public_relations|0\": {\n \"acc_norm\": 0.22727272727272727,\n\
\ \"acc_norm_stderr\": 0.04013964554072775\n },\n \"community|arabic_mmlu:security_studies|0\"\
: {\n \"acc_norm\": 0.18775510204081633,\n \"acc_norm_stderr\": 0.02500025603954621\n\
\ },\n \"community|arabic_mmlu:sociology|0\": {\n \"acc_norm\": 0.24378109452736318,\n\
\ \"acc_norm_stderr\": 0.03036049015401465\n },\n \"community|arabic_mmlu:us_foreign_policy|0\"\
: {\n \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n\
\ },\n \"community|arabic_mmlu:virology|0\": {\n \"acc_norm\": 0.28313253012048195,\n\
\ \"acc_norm_stderr\": 0.03507295431370518\n },\n \"community|arabic_mmlu:world_religions|0\"\
: {\n \"acc_norm\": 0.3216374269005848,\n \"acc_norm_stderr\": 0.03582529442573122\n\
\ },\n \"community|arc_challenge_okapi_ar|0\": {\n \"acc_norm\": 0.2525862068965517,\n\
\ \"acc_norm_stderr\": 0.012762732057795888\n },\n \"community|arc_easy_ar|0\"\
: {\n \"acc_norm\": 0.2593062605752961,\n \"acc_norm_stderr\": 0.00901558634852351\n\
\ },\n \"community|boolq_ar|0\": {\n \"acc_norm\": 0.40950920245398775,\n\
\ \"acc_norm_stderr\": 0.008613828474130074\n },\n \"community|copa_ext_ar|0\"\
: {\n \"acc_norm\": 0.4888888888888889,\n \"acc_norm_stderr\": 0.05298680599073449\n\
\ },\n \"community|hellaswag_okapi_ar|0\": {\n \"acc_norm\": 0.24882782684549123,\n\
\ \"acc_norm_stderr\": 0.004514758778737428\n },\n \"community|openbook_qa_ext_ar|0\"\
: {\n \"acc_norm\": 0.3656565656565657,\n \"acc_norm_stderr\": 0.021668828786750326\n\
\ },\n \"community|piqa_ar|0\": {\n \"acc_norm\": 0.5040916530278232,\n\
\ \"acc_norm_stderr\": 0.011681341688982008\n },\n \"community|race_ar|0\"\
: {\n \"acc_norm\": 0.2803814161087442,\n \"acc_norm_stderr\": 0.006398680832644407\n\
\ },\n \"community|sciq_ar|0\": {\n \"acc_norm\": 0.3085427135678392,\n\
\ \"acc_norm_stderr\": 0.0146503207768712\n },\n \"community|toxigen_ar|0\"\
: {\n \"acc_norm\": 0.4320855614973262,\n \"acc_norm_stderr\": 0.01620887578524445\n\
\ },\n \"lighteval|xstory_cloze:ar|0\": {\n \"acc\": 0.47187293183322304,\n\
\ \"acc_stderr\": 0.012846749995797692\n },\n \"community|acva:_average|0\"\
: {\n \"acc_norm\": 0.5823110081794227,\n \"acc_norm_stderr\": 0.04701755519626288\n\
\ },\n \"community|alghafa:_average|0\": {\n \"acc_norm\": 0.3277265567304262,\n\
\ \"acc_norm_stderr\": 0.021263657770639627\n },\n \"community|arabic_mmlu:_average|0\"\
: {\n \"acc_norm\": 0.23589525196402603,\n \"acc_norm_stderr\": 0.03174802148728372\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Artples/L-MChat-Small
configs:
- config_name: community_acva_Algeria_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Algeria|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Algeria|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Ancient_Egypt_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Ancient_Egypt|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Ancient_Egypt|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arab_Empire_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arab_Empire|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arab_Empire|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Architecture_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Architecture|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Architecture|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Art_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Art|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Art|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Astronomy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Astronomy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Astronomy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Calligraphy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Calligraphy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Calligraphy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Ceremony_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Ceremony|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Ceremony|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Clothing_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Clothing|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Clothing|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Culture_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Culture|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Culture|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Food_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Food|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Food|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Funeral_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Funeral|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Funeral|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Geography_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Geography|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Geography|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_History_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_History|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_History|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Language_Origin_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Language_Origin|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Language_Origin|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Literature_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Literature|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Literature|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Math_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Math|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Math|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Medicine_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Medicine|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Medicine|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Music_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Music|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Music|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Ornament_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Ornament|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Ornament|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Philosophy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Philosophy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Philosophy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Physics_and_Chemistry_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Physics_and_Chemistry|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Physics_and_Chemistry|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Arabic_Wedding_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Arabic_Wedding|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Arabic_Wedding|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Bahrain_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Bahrain|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Bahrain|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Comoros_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Comoros|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Comoros|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Egypt_modern_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Egypt_modern|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Egypt_modern|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromAncientEgypt_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromAncientEgypt|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromAncientEgypt|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromByzantium_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromByzantium|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromByzantium|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromChina_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromChina|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromChina|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromGreece_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromGreece|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromGreece|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromIslam_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromIslam|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromIslam|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromPersia_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromPersia|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromPersia|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_InfluenceFromRome_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:InfluenceFromRome|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:InfluenceFromRome|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Iraq_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Iraq|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Iraq|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Islam_Education_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Islam_Education|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Islam_Education|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Islam_branches_and_schools_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Islam_branches_and_schools|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Islam_branches_and_schools|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Islamic_law_system_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Islamic_law_system|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Islamic_law_system|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Jordan_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Jordan|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Jordan|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Kuwait_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Kuwait|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Kuwait|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Lebanon_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Lebanon|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Lebanon|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Libya_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Libya|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Libya|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Mauritania_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Mauritania|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Mauritania|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Mesopotamia_civilization_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Mesopotamia_civilization|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Mesopotamia_civilization|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Morocco_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Morocco|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Morocco|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Oman_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Oman|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Oman|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Palestine_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Palestine|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Palestine|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Qatar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Qatar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Qatar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Saudi_Arabia_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Saudi_Arabia|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Saudi_Arabia|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Somalia_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Somalia|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Somalia|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Sudan_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Sudan|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Sudan|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Syria_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Syria|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Syria|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Tunisia_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Tunisia|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Tunisia|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_United_Arab_Emirates_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:United_Arab_Emirates|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:United_Arab_Emirates|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_Yemen_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:Yemen|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:Yemen|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_communication_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:communication|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:communication|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_computer_and_phone_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:computer_and_phone|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:computer_and_phone|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_daily_life_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:daily_life|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:daily_life|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_acva_entertainment_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|acva:entertainment|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|acva:entertainment|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_mcq_exams_test_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:mcq_exams_test_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:mcq_exams_test_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_meta_ar_dialects_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:meta_ar_dialects|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:meta_ar_dialects|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_meta_ar_msa_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:meta_ar_msa|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:meta_ar_msa|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_facts_truefalse_balanced_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_facts_truefalse_balanced_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_facts_truefalse_balanced_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_grounded_statement_soqal_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_soqal_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_soqal_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_rating_sentiment_no_neutral_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_rating_sentiment_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_rating_sentiment_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_alghafa_multiple_choice_sentiment_task_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|alghafa:multiple_choice_sentiment_task|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|alghafa:multiple_choice_sentiment_task|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_exams_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_exams|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_exams|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_abstract_algebra_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:abstract_algebra|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:abstract_algebra|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_anatomy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:anatomy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:anatomy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_astronomy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:astronomy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:astronomy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_business_ethics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:business_ethics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:business_ethics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_clinical_knowledge_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:clinical_knowledge|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:clinical_knowledge|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_biology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_biology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_biology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_chemistry_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_chemistry|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_chemistry|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_computer_science_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_computer_science|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_computer_science|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_mathematics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_medicine_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_medicine|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_medicine|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_college_physics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:college_physics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:college_physics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_computer_security_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:computer_security|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:computer_security|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_conceptual_physics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:conceptual_physics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:conceptual_physics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_econometrics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:econometrics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:econometrics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_electrical_engineering_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:electrical_engineering|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:electrical_engineering|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_elementary_mathematics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:elementary_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:elementary_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_formal_logic_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:formal_logic|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:formal_logic|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_global_facts_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:global_facts|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:global_facts|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_biology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_biology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_biology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_chemistry_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_chemistry|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_chemistry|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_computer_science_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_computer_science|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_computer_science|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_european_history_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_european_history|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_european_history|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_geography_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_geography|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_geography|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_government_and_politics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_government_and_politics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_government_and_politics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_macroeconomics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_macroeconomics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_macroeconomics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_mathematics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_mathematics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_microeconomics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_microeconomics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_microeconomics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_physics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_physics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_physics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_psychology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_psychology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_psychology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_statistics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_statistics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_statistics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_us_history_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_us_history|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_us_history|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_high_school_world_history_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:high_school_world_history|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:high_school_world_history|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_human_aging_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:human_aging|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:human_aging|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_human_sexuality_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:human_sexuality|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:human_sexuality|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_international_law_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:international_law|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:international_law|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_jurisprudence_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:jurisprudence|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:jurisprudence|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_logical_fallacies_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:logical_fallacies|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:logical_fallacies|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_machine_learning_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:machine_learning|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:machine_learning|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_management_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:management|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:management|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_marketing_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:marketing|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:marketing|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_medical_genetics_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:medical_genetics|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:medical_genetics|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_miscellaneous_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:miscellaneous|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:miscellaneous|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_moral_disputes_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:moral_disputes|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:moral_disputes|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_moral_scenarios_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:moral_scenarios|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:moral_scenarios|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_nutrition_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:nutrition|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:nutrition|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_philosophy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:philosophy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:philosophy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_prehistory_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:prehistory|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:prehistory|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_professional_accounting_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:professional_accounting|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_accounting|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_professional_law_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:professional_law|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_law|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_professional_medicine_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:professional_medicine|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_medicine|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_professional_psychology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:professional_psychology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:professional_psychology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_public_relations_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:public_relations|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:public_relations|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_security_studies_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:security_studies|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:security_studies|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_sociology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:sociology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:sociology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_us_foreign_policy_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:us_foreign_policy|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:us_foreign_policy|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_virology_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:virology|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:virology|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arabic_mmlu_world_religions_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arabic_mmlu:world_religions|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arabic_mmlu:world_religions|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arc_challenge_okapi_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arc_challenge_okapi_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arc_challenge_okapi_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_arc_easy_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|arc_easy_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|arc_easy_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_boolq_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|boolq_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|boolq_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_copa_ext_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|copa_ext_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|copa_ext_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_hellaswag_okapi_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|hellaswag_okapi_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|hellaswag_okapi_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_openbook_qa_ext_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|openbook_qa_ext_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|openbook_qa_ext_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_piqa_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|piqa_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|piqa_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_race_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|race_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|race_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_sciq_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|sciq_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|sciq_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: community_toxigen_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_community|toxigen_ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_community|toxigen_ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: lighteval_xstory_cloze_ar_0
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- '**/details_lighteval|xstory_cloze:ar|0_2024-05-27T14-39-45.128547.parquet'
- split: latest
path:
- '**/details_lighteval|xstory_cloze:ar|0_2024-05-27T14-39-45.128547.parquet'
- config_name: results
data_files:
- split: 2024_05_27T14_39_45.128547
path:
- results_2024-05-27T14-39-45.128547.parquet
- split: latest
path:
- results_2024-05-27T14-39-45.128547.parquet
---
# Dataset Card for Evaluation run of Artples/L-MChat-Small
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Artples/L-MChat-Small](https://huggingface.co/Artples/L-MChat-Small).
The dataset is composed of 136 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.
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("OALL/details_Artples__L-MChat-Small",
"lighteval_xstory_cloze_ar_0",
split="train")
```
## Latest results
These are the [latest results from run 2024-05-27T14:39:45.128547](https://huggingface.co/datasets/OALL/details_Artples__L-MChat-Small/blob/main/results_2024-05-27T14-39-45.128547.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_norm": 0.3996877363610559,
"acc_norm_stderr": 0.0363328445153769,
"acc": 0.47187293183322304,
"acc_stderr": 0.012846749995797692
},
"community|acva:Algeria|0": {
"acc_norm": 0.48717948717948717,
"acc_norm_stderr": 0.03588610523192216
},
"community|acva:Ancient_Egypt|0": {
"acc_norm": 0.9015873015873016,
"acc_norm_stderr": 0.01680988100419675
},
"community|acva:Arab_Empire|0": {
"acc_norm": 0.690566037735849,
"acc_norm_stderr": 0.028450154794118634
},
"community|acva:Arabic_Architecture|0": {
"acc_norm": 0.5333333333333333,
"acc_norm_stderr": 0.03581804596782233
},
"community|acva:Arabic_Art|0": {
"acc_norm": 0.6512820512820513,
"acc_norm_stderr": 0.034215338466705415
},
"community|acva:Arabic_Astronomy|0": {
"acc_norm": 0.5282051282051282,
"acc_norm_stderr": 0.035840746749208334
},
"community|acva:Arabic_Calligraphy|0": {
"acc_norm": 0.5137254901960784,
"acc_norm_stderr": 0.0313609674469424
},
"community|acva:Arabic_Ceremony|0": {
"acc_norm": 0.4864864864864865,
"acc_norm_stderr": 0.03684702401944814
},
"community|acva:Arabic_Clothing|0": {
"acc_norm": 0.5025641025641026,
"acc_norm_stderr": 0.035897435897435895
},
"community|acva:Arabic_Culture|0": {
"acc_norm": 0.7435897435897436,
"acc_norm_stderr": 0.03134970994274493
},
"community|acva:Arabic_Food|0": {
"acc_norm": 0.558974358974359,
"acc_norm_stderr": 0.0356473293185358
},
"community|acva:Arabic_Funeral|0": {
"acc_norm": 0.5263157894736842,
"acc_norm_stderr": 0.05149958471474543
},
"community|acva:Arabic_Geography|0": {
"acc_norm": 0.41379310344827586,
"acc_norm_stderr": 0.04104269211806232
},
"community|acva:Arabic_History|0": {
"acc_norm": 0.6820512820512821,
"acc_norm_stderr": 0.03343383454355787
},
"community|acva:Arabic_Language_Origin|0": {
"acc_norm": 0.4842105263157895,
"acc_norm_stderr": 0.05154534179593067
},
"community|acva:Arabic_Literature|0": {
"acc_norm": 0.5310344827586206,
"acc_norm_stderr": 0.04158632762097828
},
"community|acva:Arabic_Math|0": {
"acc_norm": 0.6974358974358974,
"acc_norm_stderr": 0.03298070870085618
},
"community|acva:Arabic_Medicine|0": {
"acc_norm": 0.5103448275862069,
"acc_norm_stderr": 0.04165774775728763
},
"community|acva:Arabic_Music|0": {
"acc_norm": 0.7769784172661871,
"acc_norm_stderr": 0.03543548499561939
},
"community|acva:Arabic_Ornament|0": {
"acc_norm": 0.5333333333333333,
"acc_norm_stderr": 0.03581804596782233
},
"community|acva:Arabic_Philosophy|0": {
"acc_norm": 0.46206896551724136,
"acc_norm_stderr": 0.04154659671707548
},
"community|acva:Arabic_Physics_and_Chemistry|0": {
"acc_norm": 0.5076923076923077,
"acc_norm_stderr": 0.03589365940635213
},
"community|acva:Arabic_Wedding|0": {
"acc_norm": 0.6,
"acc_norm_stderr": 0.035172622905632896
},
"community|acva:Bahrain|0": {
"acc_norm": 0.6888888888888889,
"acc_norm_stderr": 0.06979205927323111
},
"community|acva:Comoros|0": {
"acc_norm": 0.6222222222222222,
"acc_norm_stderr": 0.07309112127323451
},
"community|acva:Egypt_modern|0": {
"acc_norm": 0.6736842105263158,
"acc_norm_stderr": 0.04835966701461423
},
"community|acva:InfluenceFromAncientEgypt|0": {
"acc_norm": 0.39487179487179486,
"acc_norm_stderr": 0.035095456022620375
},
"community|acva:InfluenceFromByzantium|0": {
"acc_norm": 0.2827586206896552,
"acc_norm_stderr": 0.03752833958003337
},
"community|acva:InfluenceFromChina|0": {
"acc_norm": 0.3333333333333333,
"acc_norm_stderr": 0.03384487217112065
},
"community|acva:InfluenceFromGreece|0": {
"acc_norm": 0.36923076923076925,
"acc_norm_stderr": 0.034648411418637566
},
"community|acva:InfluenceFromIslam|0": {
"acc_norm": 0.6896551724137931,
"acc_norm_stderr": 0.03855289616378947
},
"community|acva:InfluenceFromPersia|0": {
"acc_norm": 0.3028571428571429,
"acc_norm_stderr": 0.03483414676585985
},
"community|acva:InfluenceFromRome|0": {
"acc_norm": 0.4307692307692308,
"acc_norm_stderr": 0.035552132520587594
},
"community|acva:Iraq|0": {
"acc_norm": 0.5176470588235295,
"acc_norm_stderr": 0.05452048340661897
},
"community|acva:Islam_Education|0": {
"acc_norm": 0.558974358974359,
"acc_norm_stderr": 0.03564732931853579
},
"community|acva:Islam_branches_and_schools|0": {
"acc_norm": 0.5028571428571429,
"acc_norm_stderr": 0.037904283318347436
},
"community|acva:Islamic_law_system|0": {
"acc_norm": 0.5948717948717949,
"acc_norm_stderr": 0.03524577495610961
},
"community|acva:Jordan|0": {
"acc_norm": 0.6444444444444445,
"acc_norm_stderr": 0.07216392363431012
},
"community|acva:Kuwait|0": {
"acc_norm": 0.6888888888888889,
"acc_norm_stderr": 0.06979205927323111
},
"community|acva:Lebanon|0": {
"acc_norm": 0.7333333333333333,
"acc_norm_stderr": 0.06666666666666668
},
"community|acva:Libya|0": {
"acc_norm": 0.5333333333333333,
"acc_norm_stderr": 0.0752101433090355
},
"community|acva:Mauritania|0": {
"acc_norm": 0.5333333333333333,
"acc_norm_stderr": 0.0752101433090355
},
"community|acva:Mesopotamia_civilization|0": {
"acc_norm": 0.49032258064516127,
"acc_norm_stderr": 0.04028360076525542
},
"community|acva:Morocco|0": {
"acc_norm": 0.7555555555555555,
"acc_norm_stderr": 0.06478835438717
},
"community|acva:Oman|0": {
"acc_norm": 0.8,
"acc_norm_stderr": 0.06030226891555273
},
"community|acva:Palestine|0": {
"acc_norm": 0.7411764705882353,
"acc_norm_stderr": 0.04778846120374094
},
"community|acva:Qatar|0": {
"acc_norm": 0.5777777777777777,
"acc_norm_stderr": 0.07446027270295806
},
"community|acva:Saudi_Arabia|0": {
"acc_norm": 0.6717948717948717,
"acc_norm_stderr": 0.03371243782413707
},
"community|acva:Somalia|0": {
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.07491109582924915
},
"community|acva:Sudan|0": {
"acc_norm": 0.6444444444444445,
"acc_norm_stderr": 0.07216392363431012
},
"community|acva:Syria|0": {
"acc_norm": 0.6666666666666666,
"acc_norm_stderr": 0.07106690545187012
},
"community|acva:Tunisia|0": {
"acc_norm": 0.6444444444444445,
"acc_norm_stderr": 0.07216392363431011
},
"community|acva:United_Arab_Emirates|0": {
"acc_norm": 0.7529411764705882,
"acc_norm_stderr": 0.047058823529411785
},
"community|acva:Yemen|0": {
"acc_norm": 0.6,
"acc_norm_stderr": 0.16329931618554522
},
"community|acva:communication|0": {
"acc_norm": 0.5879120879120879,
"acc_norm_stderr": 0.0258343667152563
},
"community|acva:computer_and_phone|0": {
"acc_norm": 0.5389830508474577,
"acc_norm_stderr": 0.0290718276412662
},
"community|acva:daily_life|0": {
"acc_norm": 0.7270029673590505,
"acc_norm_stderr": 0.024303980960050656
},
"community|acva:entertainment|0": {
"acc_norm": 0.711864406779661,
"acc_norm_stderr": 0.026413346524541644
},
"community|alghafa:mcq_exams_test_ar|0": {
"acc_norm": 0.2513464991023339,
"acc_norm_stderr": 0.01839668001069939
},
"community|alghafa:meta_ar_dialects|0": {
"acc_norm": 0.24411492122335496,
"acc_norm_stderr": 0.005848837806074586
},
"community|alghafa:meta_ar_msa|0": {
"acc_norm": 0.24692737430167597,
"acc_norm_stderr": 0.014422292204808836
},
"community|alghafa:multiple_choice_facts_truefalse_balanced_task|0": {
"acc_norm": 0.52,
"acc_norm_stderr": 0.05807730170189531
},
"community|alghafa:multiple_choice_grounded_statement_soqal_task|0": {
"acc_norm": 0.26666666666666666,
"acc_norm_stderr": 0.03622779862191887
},
"community|alghafa:multiple_choice_grounded_statement_xglue_mlqa_task|0": {
"acc_norm": 0.24666666666666667,
"acc_norm_stderr": 0.03531471376356937
},
"community|alghafa:multiple_choice_rating_sentiment_no_neutral_task|0": {
"acc_norm": 0.499812382739212,
"acc_norm_stderr": 0.005592267043694276
},
"community|alghafa:multiple_choice_rating_sentiment_task|0": {
"acc_norm": 0.3402835696413678,
"acc_norm_stderr": 0.006119849906257789
},
"community|alghafa:multiple_choice_sentiment_task|0": {
"acc_norm": 0.33372093023255817,
"acc_norm_stderr": 0.011373178876838192
},
"community|arabic_exams|0": {
"acc_norm": 0.2383612662942272,
"acc_norm_stderr": 0.01840390396129298
},
"community|arabic_mmlu:abstract_algebra|0": {
"acc_norm": 0.29,
"acc_norm_stderr": 0.045604802157206845
},
"community|arabic_mmlu:anatomy|0": {
"acc_norm": 0.18518518518518517,
"acc_norm_stderr": 0.03355677216313142
},
"community|arabic_mmlu:astronomy|0": {
"acc_norm": 0.18421052631578946,
"acc_norm_stderr": 0.0315469804508223
},
"community|arabic_mmlu:business_ethics|0": {
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"community|arabic_mmlu:clinical_knowledge|0": {
"acc_norm": 0.21509433962264152,
"acc_norm_stderr": 0.02528839450289137
},
"community|arabic_mmlu:college_biology|0": {
"acc_norm": 0.25,
"acc_norm_stderr": 0.03621034121889507
},
"community|arabic_mmlu:college_chemistry|0": {
"acc_norm": 0.19,
"acc_norm_stderr": 0.039427724440366234
},
"community|arabic_mmlu:college_computer_science|0": {
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"community|arabic_mmlu:college_mathematics|0": {
"acc_norm": 0.24,
"acc_norm_stderr": 0.042923469599092816
},
"community|arabic_mmlu:college_medicine|0": {
"acc_norm": 0.2138728323699422,
"acc_norm_stderr": 0.031265112061730445
},
"community|arabic_mmlu:college_physics|0": {
"acc_norm": 0.22549019607843138,
"acc_norm_stderr": 0.041583075330832865
},
"community|arabic_mmlu:computer_security|0": {
"acc_norm": 0.27,
"acc_norm_stderr": 0.0446196043338474
},
"community|arabic_mmlu:conceptual_physics|0": {
"acc_norm": 0.2723404255319149,
"acc_norm_stderr": 0.029101290698386698
},
"community|arabic_mmlu:econometrics|0": {
"acc_norm": 0.2719298245614035,
"acc_norm_stderr": 0.04185774424022056
},
"community|arabic_mmlu:electrical_engineering|0": {
"acc_norm": 0.25517241379310346,
"acc_norm_stderr": 0.03632984052707842
},
"community|arabic_mmlu:elementary_mathematics|0": {
"acc_norm": 0.21164021164021163,
"acc_norm_stderr": 0.021037331505262886
},
"community|arabic_mmlu:formal_logic|0": {
"acc_norm": 0.2619047619047619,
"acc_norm_stderr": 0.03932537680392872
},
"community|arabic_mmlu:global_facts|0": {
"acc_norm": 0.19,
"acc_norm_stderr": 0.039427724440366234
},
"community|arabic_mmlu:high_school_biology|0": {
"acc_norm": 0.18064516129032257,
"acc_norm_stderr": 0.021886178567172548
},
"community|arabic_mmlu:high_school_chemistry|0": {
"acc_norm": 0.1724137931034483,
"acc_norm_stderr": 0.026577672183036572
},
"community|arabic_mmlu:high_school_computer_science|0": {
"acc_norm": 0.22,
"acc_norm_stderr": 0.041633319989322716
},
"community|arabic_mmlu:high_school_european_history|0": {
"acc_norm": 0.21818181818181817,
"acc_norm_stderr": 0.03225078108306289
},
"community|arabic_mmlu:high_school_geography|0": {
"acc_norm": 0.17676767676767677,
"acc_norm_stderr": 0.027178752639044915
},
"community|arabic_mmlu:high_school_government_and_politics|0": {
"acc_norm": 0.19689119170984457,
"acc_norm_stderr": 0.028697873971860664
},
"community|arabic_mmlu:high_school_macroeconomics|0": {
"acc_norm": 0.19743589743589743,
"acc_norm_stderr": 0.020182646968674844
},
"community|arabic_mmlu:high_school_mathematics|0": {
"acc_norm": 0.22592592592592592,
"acc_norm_stderr": 0.02549753263960955
},
"community|arabic_mmlu:high_school_microeconomics|0": {
"acc_norm": 0.21428571428571427,
"acc_norm_stderr": 0.026653531596715494
},
"community|arabic_mmlu:high_school_physics|0": {
"acc_norm": 0.2052980132450331,
"acc_norm_stderr": 0.03297986648473836
},
"community|arabic_mmlu:high_school_psychology|0": {
"acc_norm": 0.1889908256880734,
"acc_norm_stderr": 0.01678548115920364
},
"community|arabic_mmlu:high_school_statistics|0": {
"acc_norm": 0.1574074074074074,
"acc_norm_stderr": 0.024837173518242387
},
"community|arabic_mmlu:high_school_us_history|0": {
"acc_norm": 0.25,
"acc_norm_stderr": 0.03039153369274154
},
"community|arabic_mmlu:high_school_world_history|0": {
"acc_norm": 0.270042194092827,
"acc_norm_stderr": 0.028900721906293426
},
"community|arabic_mmlu:human_aging|0": {
"acc_norm": 0.29596412556053814,
"acc_norm_stderr": 0.030636591348699813
},
"community|arabic_mmlu:human_sexuality|0": {
"acc_norm": 0.25190839694656486,
"acc_norm_stderr": 0.03807387116306086
},
"community|arabic_mmlu:international_law|0": {
"acc_norm": 0.2396694214876033,
"acc_norm_stderr": 0.03896878985070417
},
"community|arabic_mmlu:jurisprudence|0": {
"acc_norm": 0.26851851851851855,
"acc_norm_stderr": 0.04284467968052192
},
"community|arabic_mmlu:logical_fallacies|0": {
"acc_norm": 0.22085889570552147,
"acc_norm_stderr": 0.032591773927421776
},
"community|arabic_mmlu:machine_learning|0": {
"acc_norm": 0.32142857142857145,
"acc_norm_stderr": 0.04432804055291519
},
"community|arabic_mmlu:management|0": {
"acc_norm": 0.17475728155339806,
"acc_norm_stderr": 0.037601780060266224
},
"community|arabic_mmlu:marketing|0": {
"acc_norm": 0.3034188034188034,
"acc_norm_stderr": 0.03011821010694267
},
"community|arabic_mmlu:medical_genetics|0": {
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"community|arabic_mmlu:miscellaneous|0": {
"acc_norm": 0.2413793103448276,
"acc_norm_stderr": 0.015302380123542089
},
"community|arabic_mmlu:moral_disputes|0": {
"acc_norm": 0.2514450867052023,
"acc_norm_stderr": 0.02335736578587404
},
"community|arabic_mmlu:moral_scenarios|0": {
"acc_norm": 0.23798882681564246,
"acc_norm_stderr": 0.014242630070574915
},
"community|arabic_mmlu:nutrition|0": {
"acc_norm": 0.23202614379084968,
"acc_norm_stderr": 0.02417084087934101
},
"community|arabic_mmlu:philosophy|0": {
"acc_norm": 0.1864951768488746,
"acc_norm_stderr": 0.02212243977248078
},
"community|arabic_mmlu:prehistory|0": {
"acc_norm": 0.21604938271604937,
"acc_norm_stderr": 0.02289916291844581
},
"community|arabic_mmlu:professional_accounting|0": {
"acc_norm": 0.24822695035460993,
"acc_norm_stderr": 0.025770015644290396
},
"community|arabic_mmlu:professional_law|0": {
"acc_norm": 0.24511082138200782,
"acc_norm_stderr": 0.010986307870045517
},
"community|arabic_mmlu:professional_medicine|0": {
"acc_norm": 0.19117647058823528,
"acc_norm_stderr": 0.02388688192244034
},
"community|arabic_mmlu:professional_psychology|0": {
"acc_norm": 0.2549019607843137,
"acc_norm_stderr": 0.017630827375148383
},
"community|arabic_mmlu:public_relations|0": {
"acc_norm": 0.22727272727272727,
"acc_norm_stderr": 0.04013964554072775
},
"community|arabic_mmlu:security_studies|0": {
"acc_norm": 0.18775510204081633,
"acc_norm_stderr": 0.02500025603954621
},
"community|arabic_mmlu:sociology|0": {
"acc_norm": 0.24378109452736318,
"acc_norm_stderr": 0.03036049015401465
},
"community|arabic_mmlu:us_foreign_policy|0": {
"acc_norm": 0.28,
"acc_norm_stderr": 0.045126085985421276
},
"community|arabic_mmlu:virology|0": {
"acc_norm": 0.28313253012048195,
"acc_norm_stderr": 0.03507295431370518
},
"community|arabic_mmlu:world_religions|0": {
"acc_norm": 0.3216374269005848,
"acc_norm_stderr": 0.03582529442573122
},
"community|arc_challenge_okapi_ar|0": {
"acc_norm": 0.2525862068965517,
"acc_norm_stderr": 0.012762732057795888
},
"community|arc_easy_ar|0": {
"acc_norm": 0.2593062605752961,
"acc_norm_stderr": 0.00901558634852351
},
"community|boolq_ar|0": {
"acc_norm": 0.40950920245398775,
"acc_norm_stderr": 0.008613828474130074
},
"community|copa_ext_ar|0": {
"acc_norm": 0.4888888888888889,
"acc_norm_stderr": 0.05298680599073449
},
"community|hellaswag_okapi_ar|0": {
"acc_norm": 0.24882782684549123,
"acc_norm_stderr": 0.004514758778737428
},
"community|openbook_qa_ext_ar|0": {
"acc_norm": 0.3656565656565657,
"acc_norm_stderr": 0.021668828786750326
},
"community|piqa_ar|0": {
"acc_norm": 0.5040916530278232,
"acc_norm_stderr": 0.011681341688982008
},
"community|race_ar|0": {
"acc_norm": 0.2803814161087442,
"acc_norm_stderr": 0.006398680832644407
},
"community|sciq_ar|0": {
"acc_norm": 0.3085427135678392,
"acc_norm_stderr": 0.0146503207768712
},
"community|toxigen_ar|0": {
"acc_norm": 0.4320855614973262,
"acc_norm_stderr": 0.01620887578524445
},
"lighteval|xstory_cloze:ar|0": {
"acc": 0.47187293183322304,
"acc_stderr": 0.012846749995797692
},
"community|acva:_average|0": {
"acc_norm": 0.5823110081794227,
"acc_norm_stderr": 0.04701755519626288
},
"community|alghafa:_average|0": {
"acc_norm": 0.3277265567304262,
"acc_norm_stderr": 0.021263657770639627
},
"community|arabic_mmlu:_average|0": {
"acc_norm": 0.23589525196402603,
"acc_norm_stderr": 0.03174802148728372
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
haixuantao/wrist_gripper | haixuantao | "2024-05-27T14:54:37Z" | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | "2024-05-27T14:50:42Z" | ---
license: apache-2.0
dataset_info:
features:
- name: index
dtype: int64
- name: observation.images.cam_right_wrist
dtype: video_frame
- name: observation.velocity
sequence: float32
length: 14
- name: observation.images.cam_high
dtype: video_frame
- name: observation.state
sequence: float32
length: 14
- name: observation.images.cam_left_wrist
dtype: video_frame
- name: observation.effort
sequence: float32
length: 14
- name: action
sequence: float32
length: 14
- name: episode_index
dtype: int64
- name: observation.images.cam_low
dtype: video_frame
- name: frame_index
dtype: int64
- name: next.done
dtype: bool
- name: timestamp
dtype: float32
splits:
- name: train
num_bytes: 6243840
num_examples: 12288
download_size: 730984
dataset_size: 6243840
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
ibivibiv/summary_instruct | ibivibiv | "2024-05-27T14:52:42Z" | 0 | 0 | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:51:45Z" | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 925781633
num_examples: 320939
- name: validation
num_bytes: 51556561
num_examples: 17935
- name: test
num_bytes: 51517414
num_examples: 17830
download_size: 649422645
dataset_size: 1028855608
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
alexandreteles/confessio_fraternitatis_multiturn | alexandreteles | "2024-05-27T14:59:13Z" | 0 | 0 | [
"task_categories:text-generation",
"language:en",
"license:c-uda",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/2327",
"region:us",
"spirituality",
"occultism",
"esoterism"
] | [
"text-generation"
] | "2024-05-27T14:52:56Z" | ---
license: c-uda
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 121531
num_examples: 66
download_size: 35719
dataset_size: 121531
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-generation
language:
- en
tags:
- spirituality
- occultism
- esoterism
size_categories:
- n<1K
pretty_name: Confessio Fraternitatis (multiturn)
---
# Confessio Fraternitatis Multiturn Conversation Dataset
## Overview
This dataset consists of structured multiturn conversations modeled around the esoteric and philosophical themes of the "Confessio Fraternitatis." The text, known for its deep allegorical content, serves as the foundation for generating dialogues that involve rigorous inquiry into the occult and philosophical.
## Objective
The primary objective of this dataset is to facilitate the development and testing of AI models specialized in understanding and generating responses grounded in esoteric philosophy. By providing a rich set of dialogues based on the "Confessio Fraternitatis," the dataset aims to promote deeper intellectual engagement with historic philosophical texts and their contemporary relevance in esoteric studies.
## Access
The dataset is available under the [c-uda](https://github.com/microsoft/Computational-Use-of-Data-Agreement/blob/master/C-UDA-1.0.md) license, intended for educational and research purposes..
## Contribution
Contributions to the dataset are welcome, especially those that expand the depth and range of philosophical inquiries. |
rakshya34/filtered_voice_english_v1.1_tag_5k | rakshya34 | "2024-05-27T14:53:37Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:53:36Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
- name: text_description
dtype: string
splits:
- name: train
num_bytes: 3124403
num_examples: 5000
download_size: 1151539
dataset_size: 3124403
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
anomievision/filename-meta | anomievision | "2024-06-04T16:10:33Z" | 0 | 1 | [
"language:en",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:54:03Z" | ---
language:
- en
license: cc-by-4.0
---
# ProjectM Datasets
*This respository contains custom datasets, tailered for the [ProjectM](https://github.com/projectM-visualizer/projectm) community.*
### Datasets
- 4000-preset-filename-prompts
- Name
- Authors
- Prompt
- Results |
rakshya34/filtered_voice_english_v1.2_tag_5k | rakshya34 | "2024-05-27T14:55:00Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:54:59Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
- name: text_description
dtype: string
splits:
- name: train
num_bytes: 3138513
num_examples: 5000
download_size: 1174684
dataset_size: 3138513
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.10_tag_5k | rakshya34 | "2024-05-31T13:40:17Z" | 0 | 0 | [
"language:en",
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:56:41Z" | ---
language:
- en
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
- name: text_description
dtype: string
splits:
- name: train
num_bytes: 3151169
num_examples: 5000
download_size: 1172392
dataset_size: 3151169
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.11_tag_5k | rakshya34 | "2024-05-27T14:58:05Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:58:04Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
- name: text_description
dtype: string
splits:
- name: train
num_bytes: 3152736
num_examples: 5000
download_size: 1171259
dataset_size: 3152736
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
rakshya34/filtered_voice_english_v1.12_tag_5k | rakshya34 | "2024-05-27T14:59:27Z" | 0 | 0 | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | null | "2024-05-27T14:59:26Z" | ---
dataset_info:
features:
- name: path
dtype: string
- name: text
dtype: string
- name: normalized_text
dtype: string
- name: utterance_pitch_mean
dtype: float32
- name: utterance_pitch_std
dtype: float32
- name: snr
dtype: float64
- name: c50
dtype: float64
- name: speaking_rate
dtype: string
- name: phonemes
dtype: string
- name: noise
dtype: string
- name: reverberation
dtype: string
- name: speech_monotony
dtype: string
- name: text_description
dtype: string
splits:
- name: train
num_bytes: 3148031
num_examples: 5000
download_size: 1167308
dataset_size: 3148031
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|