id stringlengths 2 115 | author stringlengths 2 42 ⌀ | last_modified timestamp[us, tz=UTC] | downloads int64 0 8.87M | likes int64 0 3.84k | paperswithcode_id stringlengths 2 45 ⌀ | tags list | lastModified timestamp[us, tz=UTC] | createdAt stringlengths 24 24 | key stringclasses 1 value | created timestamp[us] | card stringlengths 1 1.01M | embedding list | library_name stringclasses 21 values | pipeline_tag stringclasses 27 values | mask_token null | card_data null | widget_data null | model_index null | config null | transformers_info null | spaces null | safetensors null | transformersInfo null | modelId stringlengths 5 111 ⌀ | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arbml/WDC | arbml | 2022-10-25T22:52:32Z | 15 | 0 | null | [
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colombidan/Myface | colombidan | 2022-10-25T23:38:11Z | 15 | 0 | null | [
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monideep2255/sv_corpora_parliament_processed | monideep2255 | 2022-10-26T01:14:43Z | 15 | 0 | null | [
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bing-yan/USPTO | bing-yan | 2022-10-26T01:34:34Z | 15 | 0 | null | [
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autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot-mathema-acb860-1886064279 | autoevaluate | 2022-10-26T04:15:41Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-26T04:15:41Z | 2022-10-26T04:12:25.000Z | 2022-10-26T04:12:25 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot
eval_info:
task: text_zero_shot_classification
model: facebook/opt-1.3b
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot
dataset_config: mathemakitten--winobias_antistereotype_test_cot
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-1.3b
* Dataset: mathemakitten/winobias_antistereotype_test_cot
* Config: mathemakitten--winobias_antistereotype_test_cot
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. | [
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autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot-mathema-acb860-1886064281 | autoevaluate | 2022-10-26T04:38:02Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-26T04:38:02Z | 2022-10-26T04:12:26.000Z | 2022-10-26T04:12:26 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot
eval_info:
task: text_zero_shot_classification
model: facebook/opt-13b
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot
dataset_config: mathemakitten--winobias_antistereotype_test_cot
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: mathemakitten/winobias_antistereotype_test_cot
* Config: mathemakitten--winobias_antistereotype_test_cot
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-14b0f6-1886164287 | autoevaluate | 2022-10-26T04:42:02Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-26T04:42:02Z | 2022-10-26T04:39:00.000Z | 2022-10-26T04:39:00 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- lener_br
eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-base-finetuned-lener_br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-base-finetuned-lener_br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-14b0f6-1886164288 | autoevaluate | 2022-10-26T04:43:01Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-26T04:43:01Z | 2022-10-26T04:39:05.000Z | 2022-10-26T04:39:05 | ---
type: predictions
tags:
- autotrain
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-d57983-1886264290 | autoevaluate | 2022-10-26T04:40:35Z | 15 | 0 | null | [
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"evaluation",
"region:us"
] | 2022-10-26T04:40:35Z | 2022-10-26T04:39:17.000Z | 2022-10-26T04:39:17 | ---
type: predictions
tags:
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: validation
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-bd0c63-1886364292 | autoevaluate | 2022-10-26T04:40:50Z | 15 | 0 | null | [
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"evaluation",
"region:us"
] | 2022-10-26T04:40:50Z | 2022-10-26T04:39:29.000Z | 2022-10-26T04:39:29 | ---
type: predictions
tags:
- autotrain
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-large-finetuned-lener_br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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Jaren/KJSLAPP_DATA | Jaren | 2022-10-28T18:01:55Z | 15 | 0 | null | [
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Ygeth/miCara | Ygeth | 2022-10-26T11:35:42Z | 15 | 0 | null | [
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qmaruf/goodreads-rating | qmaruf | 2022-10-26T23:12:48Z | 15 | 1 | null | [
"region:us"
] | 2022-10-26T23:12:48Z | 2022-10-26T12:55:33.000Z | 2022-10-26T12:55:33 | Entry not found | [
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tglcourse/latent_lsun_church_256px | tglcourse | 2022-10-28T07:57:35Z | 15 | 0 | null | [
"region:us"
] | 2022-10-28T07:57:35Z | 2022-10-28T07:45:35.000Z | 2022-10-28T07:45:35 | ---
dataset_info:
features:
- name: label
dtype:
class_label:
names:
0: '0'
1: '1'
2: '2'
3: '3'
4: '4'
5: '5'
6: '6'
7: '7'
8: '8'
9: '9'
10: a
11: b
12: c
13: d
14: e
15: f
- name: latent
sequence:
sequence:
sequence: float32
splits:
- name: test
num_bytes: 106824288
num_examples: 6312
- name: train
num_bytes: 2029441460
num_examples: 119915
download_size: 2082210019
dataset_size: 2136265748
---
# Dataset Card for "latent_lsun_church_256px"
This is derived from https://huggingface.co/datasets/tglcourse/lsun_church_train
Each image is cropped to 256px square and encoded to a 4x32x32 latent representation using the same VAE as that employed by Stable Diffusion
Decoding
```python
from diffusers import AutoencoderKL
from datasets import load_dataset
from PIL import Image
import numpy as np
import torch
# load the dataset
dataset = load_dataset('tglcourse/latent_lsun_church_256px')
# Load the VAE (requires access - see repo model card for info)
vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae")
latent = torch.tensor([dataset['train'][0]['latent']]) # To tensor (bs, 4, 32, 32)
latent = (1 / 0.18215) * latent # Scale to match SD implementation
with torch.no_grad():
image = vae.decode(latent).sample[0] # Decode
image = (image / 2 + 0.5).clamp(0, 1) # To (0, 1)
image = image.detach().cpu().permute(1, 2, 0).numpy() # To numpy, channels lsat
image = (image * 255).round().astype("uint8") # (0, 255) and type uint8
image = Image.fromarray(image) # To PIL
image # The resulting PIL image
```
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zoheb/sketch-scene | zoheb | 2022-10-30T10:07:48Z | 15 | 15 | null | [
"task_categories:text-to-image",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:n<10K",
"source_datasets:FS-COCO",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-10-30T10:07:48Z | 2022-10-29T18:15:58.000Z | 2022-10-29T18:15:58 | ---
license: cc-by-nc-sa-4.0
language:
- en
language_creators:
- machine-generated
multilinguality:
- monolingual
pretty_name: 'Sketch Scene Descriptions'
size_categories:
- n<10K
source_datasets:
- FS-COCO
tags: []
task_categories:
- text-to-image
task_ids: []
---
# Dataset Card for Sketch Scene Descriptions
_Dataset used to train [Sketch Scene text to image model]()_
We advance sketch research to scenes with the first dataset of freehand scene sketches, FS-COCO. With practical applications in mind, we collect sketches that convey well scene content but can be sketched within a few minutes by a person with any sketching skills. Our dataset comprises around 10,000 freehand scene vector sketches with per-point space-time information by 100 non-expert individuals, offering both object- and scene-level abstraction. Each sketch is augmented with its text description.
For each row, the dataset contains `image` and `text` keys. `image` is a varying size PIL jpeg, and `text` is the accompanying text caption. Only a train split is provided.
## Citation
If you use this dataset, please cite it as:
```
@inproceedings{fscoco,
title={FS-COCO: Towards Understanding of Freehand Sketches of Common Objects in Context.}
author={Chowdhury, Pinaki Nath and Sain, Aneeshan and Bhunia, Ayan Kumar and Xiang, Tao and Gryaditskaya, Yulia and Song, Yi-Zhe},
booktitle={ECCV},
year={2022}
}
``` | [
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no3/pistachio-vibrant-venture | no3 | 2022-11-02T06:41:13Z | 15 | 0 | null | [
"region:us"
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-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
annabelng/nymemes | annabelng | 2022-11-02T08:02:09Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T08:02:09Z | 2022-11-02T07:59:23.000Z | 2022-11-02T07:59:23 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 3760740114.362
num_examples: 32933
download_size: 4007130292
dataset_size: 3760740114.362
---
# Dataset Card for "nymemes"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ebrigham/nl_banking_intents | ebrigham | 2022-11-02T09:54:45Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T09:54:45Z | 2022-11-02T09:27:41.000Z | 2022-11-02T09:27:41 | Entry not found | [
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lmvasque/coh-metrix-esp | lmvasque | 2022-11-11T17:44:04Z | 15 | 0 | null | [
"license:cc-by-sa-4.0",
"region:us"
] | 2022-11-11T17:44:04Z | 2022-11-02T10:43:02.000Z | 2022-11-02T10:43:02 | ---
license: cc-by-sa-4.0
---
## About this dataset
The dataset Coh-Metrix-Esp (Cuentos) [(Quispesaravia et al., 2016)](https://aclanthology.org/L16-1745/) is a collection of 100 documents consisting of 50 children fables (“simple” texts) and 50 stories for adults (“complex” texts) scrapped from the web. If you use this data, please credit the original website and our work as well (see citations below).
## Citation
If you use our splits in your research, please cite our work: "[A Benchmark for Neural Readability Assessment of Texts in Spanish](https://drive.google.com/file/d/1KdwvqrjX8MWYRDGBKeHmiR1NCzDcVizo/view?usp=share_link)".
```
@inproceedings{vasquez-rodriguez-etal-2022-benchmarking,
title = "A Benchmark for Neural Readability Assessment of Texts in Spanish",
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
Cuenca-Jim{\'\e}nez, Pedro-Manuel and
Morales-Esquivel, Sergio Esteban and
Alva-Manchego, Fernando",
booktitle = "Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), EMNLP 2022",
month = dec,
year = "2022",
}
```
#### Coh-Metrix-Esp (Cuentos)
```
@inproceedings{quispesaravia-etal-2016-coh,
title = "{C}oh-{M}etrix-{E}sp: A Complexity Analysis Tool for Documents Written in {S}panish",
author = "Quispesaravia, Andre and
Perez, Walter and
Sobrevilla Cabezudo, Marco and
Alva-Manchego, Fernando",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1745",
pages = "4694--4698",
}
```
You can also find more details about the project in our [GitHub](https://github.com/lmvasque/readability-es-benchmark). | [
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lmvasque/hablacultura | lmvasque | 2022-11-11T17:42:13Z | 15 | 0 | null | [
"license:cc-by-4.0",
"region:us"
] | 2022-11-11T17:42:13Z | 2022-11-02T10:44:43.000Z | 2022-11-02T10:44:43 | ---
license: cc-by-4.0
---
## About this dataset
This dataset was collected from [HablaCultura.com](https://hablacultura.com/) a website with resources for Spanish students, labeled by instructors following the [Common European Framework of Reference for Languages (CEFR)](https://www.coe.int/en/web/common-european-framework-reference-languages). We have scraped the freely available articles from its original [website](https://hablacultura.com/) to make it available to the community. If you use this data, please credit the original [website](https://hablacultura.com/) and our work as well.
## Citation
If you use our splits in your research, please cite our work: "[A Benchmark for Neural Readability Assessment of Texts in Spanish](https://drive.google.com/file/d/1KdwvqrjX8MWYRDGBKeHmiR1NCzDcVizo/view?usp=share_link)".
```
@inproceedings{vasquez-rodriguez-etal-2022-benchmarking,
title = "A Benchmark for Neural Readability Assessment of Texts in Spanish",
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
Cuenca-Jim{\'\e}nez, Pedro-Manuel and
Morales-Esquivel, Sergio Esteban and
Alva-Manchego, Fernando",
booktitle = "Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), EMNLP 2022",
month = dec,
year = "2022",
}
```
You can also find more details about the project in our [GitHub](https://github.com/lmvasque/readability-es-benchmark). | [
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0.43815657496452... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
lmvasque/kwiziq | lmvasque | 2022-11-11T17:40:47Z | 15 | 0 | null | [
"license:cc-by-4.0",
"region:us"
] | 2022-11-11T17:40:47Z | 2022-11-02T10:45:55.000Z | 2022-11-02T10:45:55 | ---
license: cc-by-4.0
---
## About this dataset
This dataset was collected from [kwiziq.com](https://www.kwiziq.com/), a website dedicated to aid Spanish learning through automated methods. It also provides articles in different CEFR-based levels. We have scraped the freely available articles from its original [website](https://www.kwiziq.com/) to make it available to the community. If you use this data, please credit the original [website]((https://www.kwiziq.com/) and our work as well.
## Citation
If you use our splits in your research, please cite our work: "[A Benchmark for Neural Readability Assessment of Texts in Spanish](https://drive.google.com/file/d/1KdwvqrjX8MWYRDGBKeHmiR1NCzDcVizo/view?usp=share_link)".
```
@inproceedings{vasquez-rodriguez-etal-2022-benchmarking,
title = "A Benchmark for Neural Readability Assessment of Texts in Spanish",
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
Cuenca-Jim{\'\e}nez, Pedro-Manuel and
Morales-Esquivel, Sergio Esteban and
Alva-Manchego, Fernando",
booktitle = "Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), EMNLP 2022",
month = dec,
year = "2022",
}
```
You can also find more details about the project in our [GitHub](https://github.com/lmvasque/readability-es-benchmark).
| [
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g30rv17ys/customdbv1 | g30rv17ys | 2022-11-02T11:19:11Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T11:19:11Z | 2022-11-02T11:19:04.000Z | 2022-11-02T11:19:04 | Entry not found | [
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ghomasHudson/muld_Character_Archetype_Classification | ghomasHudson | 2022-11-02T11:22:52Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T11:22:52Z | 2022-11-02T11:22:31.000Z | 2022-11-02T11:22:31 | Entry not found | [
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0.5715674161911011,
-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
lewtun/audio-test-push | lewtun | 2022-11-02T11:36:48Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T11:36:48Z | 2022-11-02T11:36:14.000Z | 2022-11-02T11:36:14 | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: song_id
dtype: int64
- name: genre_id
dtype: int64
- name: genre
dtype: string
splits:
- name: test
num_bytes: 3994705.0
num_examples: 10
- name: train
num_bytes: 3738678.0
num_examples: 10
download_size: 7730848
dataset_size: 7733383.0
---
# Dataset Card for "audio-test-push"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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LuisPerezVazquez/LuisImages | LuisPerezVazquez | 2022-11-02T12:20:44Z | 15 | 0 | null | [
"region:us"
] | 2022-11-02T12:20:44Z | 2022-11-02T12:15:00.000Z | 2022-11-02T12:15:00 | Entry not found | [
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0.5715675354003906,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
fkdosilovic/docee-event-classification | fkdosilovic | 2022-11-03T21:39:31Z | 15 | 0 | null | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"wiki",
"news",
"event-detection",
"region:us"
] | 2022-11-03T21:39:31Z | 2022-11-03T20:30:39.000Z | 2022-11-03T20:30:39 | ---
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: DocEE
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- wiki
- news
- event-detection
task_categories:
- text-classification
task_ids:
- multi-class-classification
---
# Dataset Card for DocEE Dataset
## Dataset Description
- **Homepage:**
- **Repository:** [DocEE Dataset repository](https://github.com/tongmeihan1995/docee)
- **Paper:** [DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction](https://aclanthology.org/2022.naacl-main.291/)
### Dataset Summary
DocEE dataset is an English-language dataset containing more than 27k news and Wikipedia articles. Dataset is primarily annotated and collected for large-scale document-level event extraction.
### Data Fields
- `title`: TODO
- `text`: TODO
- `event_type`: TODO
- `date`: TODO
- `metadata`: TODO
**Note: this repo contains only event detection portion of the dataset.**
### Data Splits
The dataset has 2 splits: _train_ and _test_. Train split contains 21949 documents while test split contains 5536 documents. In total, dataset contains 27485 documents classified into 59 event types.
#### Differences from the original split(s)
Originally, the dataset is split into three splits: train, validation and test. For the purposes of this repository, original splits were joined back together and divided into train and test splits while making sure that splits were stratified across document sources (news and wiki) and event types.
Originally, the `title` column additionally contained information from `date` and `metadata` columns. They are now separated into three columns: `date`, `metadata` and `title`. | [
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0.0381597... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
lmqg/qa_harvesting_from_wikipedia | lmqg | 2022-11-05T03:19:40Z | 15 | 3 | null | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"multilinguality:monolingual",
"size_categories:1M<",
"source_datasets:extended|wikipedia",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-11-05T03:19:40Z | 2022-11-04T06:30:51.000Z | 2022-11-04T06:30:51 | ---
license: cc-by-4.0
pretty_name: Harvesting QA paris from Wikipedia.
language: en
multilinguality: monolingual
size_categories: 1M<
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for "lmqg/qa_harvesting_from_wikipedia"
## Dataset Description
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
- **Paper:** [https://aclanthology.org/P18-1177/](https://aclanthology.org/P18-1177/)
- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
### Dataset Summary
This is the QA dataset collected by [Harvesting Paragraph-level Question-Answer Pairs from Wikipedia](https://aclanthology.org/P18-1177) (Du & Cardie, ACL 2018).
### Supported Tasks and Leaderboards
* `question-answering`
### Languages
English (en)
## Dataset Structure
### Data Fields
The data fields are the same among all splits.
#### plain_text
- `id`: a `string` feature of id
- `title`: a `string` feature of title of the paragraph
- `context`: a `string` feature of paragraph
- `question`: a `string` feature of question
- `answers`: a `json` feature of answers
### Data Splits
|train |validation|test |
|--------:|---------:|-------:|
|1,204,925| 30,293| 24,473|
## Citation Information
```
@inproceedings{du-cardie-2018-harvesting,
title = "Harvesting Paragraph-level Question-Answer Pairs from {W}ikipedia",
author = "Du, Xinya and
Cardie, Claire",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-1177",
doi = "10.18653/v1/P18-1177",
pages = "1907--1917",
abstract = "We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence. We propose a neural network approach that incorporates coreference knowledge via a novel gating mechanism. As compared to models that only take into account sentence-level information (Heilman and Smith, 2010; Du et al., 2017; Zhou et al., 2017), we find that the linguistic knowledge introduced by the coreference representation aids question generation significantly, producing models that outperform the current state-of-the-art. We apply our system (composed of an answer span extraction system and the passage-level QG system) to the 10,000 top ranking Wikipedia articles and create a corpus of over one million question-answer pairs. We provide qualitative analysis for the this large-scale generated corpus from Wikipedia.",
}
``` | [
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0.3410730063915252... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-futin__guess-vi-4200fb-2012366609 | autoevaluate | 2022-11-07T09:54:16Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-07T09:54:16Z | 2022-11-07T09:30:31.000Z | 2022-11-07T09:30:31 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/guess
eval_info:
task: text_zero_shot_classification
model: facebook/opt-125m
metrics: []
dataset_name: futin/guess
dataset_config: vi
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/guess
* Config: vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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katossky/multi-domain-sentiment-books | katossky | 2022-11-12T00:33:47Z | 15 | 0 | null | [
"license:unknown",
"region:us"
] | 2022-11-12T00:33:47Z | 2022-11-11T22:25:29.000Z | 2022-11-11T22:25:29 | ---
license: unknown
---
| [
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ndorr16/ToyTruck | ndorr16 | 2022-11-11T23:08:16Z | 15 | 0 | null | [
"license:gpl-3.0",
"region:us"
] | 2022-11-11T23:08:16Z | 2022-11-11T23:04:58.000Z | 2022-11-11T23:04:58 | ---
license: gpl-3.0
---
| [
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-0.0478255338966846... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Jellywibble/dalio-conversations-hackathon-dataset | Jellywibble | 2022-11-12T23:35:14Z | 15 | 0 | null | [
"region:us"
] | 2022-11-12T23:35:14Z | 2022-11-12T05:47:33.000Z | 2022-11-12T05:47:33 | ---
dataset_info:
features:
- name: input_text
dtype: string
- name: scores
dtype: int64
splits:
- name: train
num_bytes: 5026
num_examples: 8
download_size: 8422
dataset_size: 5026
---
# Dataset Card for "dalio-conversations-hackathon-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.2818642556667328,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bgstud/libri-mini-proc-whisper | bgstud | 2022-11-12T10:53:24Z | 15 | 0 | null | [
"region:us"
] | 2022-11-12T10:53:24Z | 2022-11-12T10:35:21.000Z | 2022-11-12T10:35:21 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: Acronym Identification Dataset
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- token-classification-other-acronym-identification
train-eval-index:
- col_mapping:
labels: tags
tokens: tokens
config: default
splits:
eval_split: test
task: token-classification
task_id: entity_extraction---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
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Akshata/Compliance_1_0 | Akshata | 2022-11-12T13:19:03Z | 15 | 0 | null | [
"region:us"
] | 2022-11-12T13:19:03Z | 2022-11-12T13:17:37.000Z | 2022-11-12T13:17:37 | Entry not found | [
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Akshata/MASSIVE | Akshata | 2022-11-12T14:05:18Z | 15 | 0 | null | [
"region:us"
] | 2022-11-12T14:05:18Z | 2022-11-12T14:04:52.000Z | 2022-11-12T14:04:52 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
galman33/gal_yair_8300_100x100 | galman33 | 2022-11-19T22:41:56Z | 15 | 0 | null | [
"region:us"
] | 2022-11-19T22:41:56Z | 2022-11-12T15:26:13.000Z | 2022-11-12T15:26:13 | ---
dataset_info:
features:
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dtype: image
splits:
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num_bytes: 142004157.0
num_examples: 8300
download_size: 141994031
dataset_size: 142004157.0
---
# Dataset Card for "yair_gal_small_resized"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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ysjay/processed_bert_dataset | ysjay | 2022-11-12T16:02:58Z | 15 | 0 | null | [
"region:us"
] | 2022-11-12T16:02:58Z | 2022-11-12T16:02:45.000Z | 2022-11-12T16:02:45 | ---
dataset_info:
features:
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sequence: int32
- name: token_type_ids
sequence: int8
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sequence: int8
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dtype: int64
splits:
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num_bytes: 70985500
num_examples: 2000
download_size: 18506503
dataset_size: 70985500
---
# Dataset Card for "processed_bert_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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jjackass59660/scyther | jjackass59660 | 2022-11-12T16:29:19Z | 15 | 0 | null | [
"license:other",
"region:us"
] | 2022-11-12T16:29:19Z | 2022-11-12T16:23:11.000Z | 2022-11-12T16:23:11 | ---
license: other
---
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ndorr16/RockingDuck | ndorr16 | 2022-11-12T23:52:47Z | 15 | 0 | null | [
"license:gpl-3.0",
"region:us"
] | 2022-11-12T23:52:47Z | 2022-11-12T23:48:24.000Z | 2022-11-12T23:48:24 | ---
license: gpl-3.0
---
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asadisaghar/amazon-shoe-reviews | asadisaghar | 2022-11-13T12:24:01Z | 15 | 0 | null | [
"region:us"
] | 2022-11-13T12:24:01Z | 2022-11-13T12:23:40.000Z | 2022-11-13T12:23:40 | ---
dataset_info:
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num_examples: 10000
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num_bytes: 16847665.2
num_examples: 90000
download_size: 10939033
dataset_size: 18719628.0
---
# Dataset Card for "amazon-shoe-reviews"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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dlproject/msp_train_hubert | dlproject | 2022-11-13T12:50:12Z | 15 | 0 | null | [
"region:us"
] | 2022-11-13T12:50:12Z | 2022-11-13T12:44:32.000Z | 2022-11-13T12:44:32 | ---
dataset_info:
features:
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sequence:
sequence:
sequence: float32
- name: labels
dtype: int64
splits:
- name: train
num_bytes: 10872804940
num_examples: 29939
download_size: 9851597205
dataset_size: 10872804940
---
# Dataset Card for "msp_train_hubert"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.4866400361061096,
0.048943109810352325,
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bigbio/cas | bigbio | 2022-12-22T15:44:18Z | 15 | 0 | null | [
"multilinguality:monolingual",
"language:fr",
"license:other",
"region:us"
] | 2022-12-22T15:44:18Z | 2022-11-13T22:07:35.000Z | 2022-11-13T22:07:35 |
---
language:
- fr
bigbio_language:
- French
license: other
multilinguality: monolingual
bigbio_license_shortname: DUA
pretty_name: CAS
homepage: https://clementdalloux.fr/?page_id=28
bigbio_pubmed: False
bigbio_public: False
bigbio_tasks:
- TEXT_CLASSIFICATION
---
# Dataset Card for CAS
## Dataset Description
- **Homepage:** https://clementdalloux.fr/?page_id=28
- **Pubmed:** False
- **Public:** False
- **Tasks:** TXTCLASS
We manually annotated two corpora from the biomedical field. The ESSAI corpus contains clinical trial protocols in French. They were mainly obtained from the National Cancer Institute The typical protocol consists of two parts: the summary of the trial, which indicates the purpose of the trial and the methods applied; and a detailed description of the trial with the inclusion and exclusion criteria. The CAS corpus contains clinical cases published in scientific literature and training material. They are published in different journals from French-speaking countries (France, Belgium, Switzerland, Canada, African countries, tropical countries) and are related to various medical specialties (cardiology, urology, oncology, obstetrics, pulmonology, gastro-enterology). The purpose of clinical cases is to describe clinical situations of patients. Hence, their content is close to the content of clinical narratives (description of diagnoses, treatments or procedures, evolution, family history, expected audience, etc.). In clinical cases, the negation is frequently used for describing the patient signs, symptoms, and diagnosis. Speculation is present as well but less frequently.
This version only contain the annotated CAS corpus
## Citation Information
```
@inproceedings{grabar-etal-2018-cas,
title = {{CAS}: {F}rench Corpus with Clinical Cases},
author = {Grabar, Natalia and Claveau, Vincent and Dalloux, Cl{'e}ment},
year = 2018,
month = oct,
booktitle = {
Proceedings of the Ninth International Workshop on Health Text Mining and
Information Analysis
},
publisher = {Association for Computational Linguistics},
address = {Brussels, Belgium},
pages = {122--128},
doi = {10.18653/v1/W18-5614},
url = {https://aclanthology.org/W18-5614},
abstract = {
Textual corpora are extremely important for various NLP applications as
they provide information necessary for creating, setting and testing these
applications and the corresponding tools. They are also crucial for
designing reliable methods and reproducible results. Yet, in some areas,
such as the medical area, due to confidentiality or to ethical reasons, it
is complicated and even impossible to access textual data representative of
those produced in these areas. We propose the CAS corpus built with
clinical cases, such as they are reported in the published scientific
literature in French. We describe this corpus, currently containing over
397,000 word occurrences, and the existing linguistic and semantic
annotations.
}
}
```
| [
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0.4314641654491424... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/jnlpba | bigbio | 2022-12-22T15:44:48Z | 15 | 1 | null | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-3.0",
"region:us"
] | 2022-12-22T15:44:48Z | 2022-11-13T22:09:04.000Z | 2022-11-13T22:09:04 |
---
language:
- en
bigbio_language:
- English
license: cc-by-3.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_3p0
pretty_name: JNLPBA
homepage: http://www.geniaproject.org/shared-tasks/bionlp-jnlpba-shared-task-2004
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
---
# Dataset Card for JNLPBA
## Dataset Description
- **Homepage:** http://www.geniaproject.org/shared-tasks/bionlp-jnlpba-shared-task-2004
- **Pubmed:** True
- **Public:** True
- **Tasks:** NER
NER For Bio-Entities
## Citation Information
```
@inproceedings{collier-kim-2004-introduction,
title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}",
author = "Collier, Nigel and Kim, Jin-Dong",
booktitle = "Proceedings of the International Joint Workshop
on Natural Language Processing in Biomedicine and its Applications
({NLPBA}/{B}io{NLP})",
month = aug # " 28th and 29th", year = "2004",
address = "Geneva, Switzerland",
publisher = "COLING",
url = "https://aclanthology.org/W04-1213",
pages = "73--78",
}
```
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0.596779704093933... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/meddialog | bigbio | 2022-12-22T15:45:13Z | 15 | 6 | null | [
"multilinguality:multilingual",
"language:en",
"language:zh",
"license:unknown",
"arxiv:2004.03329",
"region:us"
] | 2022-12-22T15:45:13Z | 2022-11-13T22:09:25.000Z | 2022-11-13T22:09:25 |
---
language:
- en
- zh
bigbio_language:
- English
- Chinese
license: unknown
multilinguality: multilingual
bigbio_license_shortname: UNKNOWN
pretty_name: MedDialog
homepage: https://github.com/UCSD-AI4H/Medical-Dialogue-System
bigbio_pubmed: False
bigbio_public: True
bigbio_tasks:
- TEXT_CLASSIFICATION
---
# Dataset Card for MedDialog
## Dataset Description
- **Homepage:** https://github.com/UCSD-AI4H/Medical-Dialogue-System
- **Pubmed:** False
- **Public:** True
- **Tasks:** TXTCLASS
The MedDialog dataset (English) contains conversations (in English) between doctors and patients.It has 0.26 million dialogues. The data is continuously growing and more dialogues will be added. The raw dialogues are from healthcaremagic.com and icliniq.com.
All copyrights of the data belong to healthcaremagic.com and icliniq.com.
## Citation Information
```
@article{DBLP:journals/corr/abs-2004-03329,
author = {Shu Chen and
Zeqian Ju and
Xiangyu Dong and
Hongchao Fang and
Sicheng Wang and
Yue Yang and
Jiaqi Zeng and
Ruisi Zhang and
Ruoyu Zhang and
Meng Zhou and
Penghui Zhu and
Pengtao Xie},
title = {MedDialog: {A} Large-scale Medical Dialogue Dataset},
journal = {CoRR},
volume = {abs/2004.03329},
year = {2020},
url = {https://arxiv.org/abs/2004.03329},
eprinttype = {arXiv},
eprint = {2004.03329},
biburl = {https://dblp.org/rec/journals/corr/abs-2004-03329.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
```
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0.245009705424308... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/muchmore | bigbio | 2022-12-22T15:45:43Z | 15 | 0 | null | [
"multilinguality:multilingual",
"language:en",
"language:de",
"license:unknown",
"region:us"
] | 2022-12-22T15:45:43Z | 2022-11-13T22:10:14.000Z | 2022-11-13T22:10:14 |
---
language:
- en
- de
bigbio_language:
- English
- German
license: unknown
multilinguality: multilingual
bigbio_license_shortname: UNKNOWN
pretty_name: MuchMore
homepage: https://muchmore.dfki.de/resources1.htm
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- TRANSLATION
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
- RELATION_EXTRACTION
---
# Dataset Card for MuchMore
## Dataset Description
- **Homepage:** https://muchmore.dfki.de/resources1.htm
- **Pubmed:** True
- **Public:** True
- **Tasks:** TRANSL,NER,NED,RE
The corpus used in the MuchMore project is a parallel corpus of English-German scientific
medical abstracts obtained from the Springer Link web site. The corpus consists
approximately of 1 million tokens for each language. Abstracts are from 41 medical
journals, each of which constitutes a relatively homogeneous medical sub-domain (e.g.
Neurology, Radiology, etc.). The corpus of downloaded HTML documents is normalized in
various ways, in order to produce a clean, plain text version, consisting of a title, abstract
and keywords. Additionally, the corpus was aligned on the sentence level.
Automatic (!) annotation includes: Part-of-Speech; Morphology (inflection and
decomposition); Chunks; Semantic Classes (UMLS: Unified Medical Language System,
MeSH: Medical Subject Headings, EuroWordNet); Semantic Relations from UMLS.
## Citation Information
```
@inproceedings{buitelaar2003multi,
title={A multi-layered, xml-based approach to the integration of linguistic and semantic annotations},
author={Buitelaar, Paul and Declerck, Thierry and Sacaleanu, Bogdan and Vintar, { {S}}pela and Raileanu, Diana and Crispi, Claudia},
booktitle={Proceedings of EACL 2003 Workshop on Language Technology and the Semantic Web (NLPXML'03), Budapest, Hungary},
year={2003}
}
```
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0.589872062206268... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Murple/ksponspeech | Murple | 2022-11-14T02:41:37Z | 15 | 4 | null | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ko",
"region:us"
] | 2022-11-14T02:41:37Z | 2022-11-14T01:58:12.000Z | 2022-11-14T01:58:12 | ---
annotations_creators:
- expert-generated
language:
- ko
language_creators:
- crowdsourced
license: []
multilinguality:
- monolingual
pretty_name: KsponSpeech
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---
# Dataset Card for KsponSpeech
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [AIHub](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=123)
- **Repository:**
- **Paper:** [KsponSpeech](https://www.mdpi.com/2076-3417/10/19/6936)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This corpus contains 969 h of general open-domain dialog utterances, spoken by about 2000 native Korean speakers in a clean environment. All data were constructed by recording the dialogue of two people freely conversing on a variety of topics and manually transcribing the utterances. The transcription provides a dual transcription consisting of orthography and pronunciation, and disfluency tags for spontaneity of speech, such as filler words, repeated words, and word fragments. This paper also presents the baseline performance of an end-to-end speech recognition model trained with KsponSpeech. In addition, we investigated the performance of standard end-to-end architectures and the number of sub-word units suitable for Korean. We investigated issues that should be considered in spontaneous speech recognition in Korean. KsponSpeech is publicly available on an open data hub site of the Korea government.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Korean
## Dataset Structure
### Data Instances
```json
{
'id': 'KsponSpeech_E00001',
'audio': {'path': None,
'array': array([0.0010376 , 0.00085449, 0.00097656, ..., 0.00250244, 0.0022583 ,
0.00253296]),
'sampling_rate': 16000},
'text': '어 일단은 억지로 과장해서 이렇게 하는 것보다 진실된 마음으로 이걸 어떻게 전달할 수 있을까 공감을 시킬 수 있을까 해서 좀'
}
```
### Data Fields
- audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
- text: the transcription of the audio file.
- id: unique id of the data sample.
### Data Splits
| | Train | Valid | eval.clean | eval.other |
| ----- | ------ | ----- | ---- | ---- |
| #samples | 620000 | 2545 | 3000 | 3000 |
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```bibtex
@Article{app10196936,
AUTHOR = {Bang, Jeong-Uk and Yun, Seung and Kim, Seung-Hi and Choi, Mu-Yeol and Lee, Min-Kyu and Kim, Yeo-Jeong and Kim, Dong-Hyun and Park, Jun and Lee, Young-Jik and Kim, Sang-Hun},
TITLE = {KsponSpeech: Korean Spontaneous Speech Corpus for Automatic Speech Recognition},
JOURNAL = {Applied Sciences},
VOLUME = {10},
YEAR = {2020},
NUMBER = {19},
ARTICLE-NUMBER = {6936},
URL = {https://www.mdpi.com/2076-3417/10/19/6936},
ISSN = {2076-3417},
ABSTRACT = {This paper introduces a large-scale spontaneous speech corpus of Korean, named KsponSpeech. This corpus contains 969 h of general open-domain dialog utterances, spoken by about 2000 native Korean speakers in a clean environment. All data were constructed by recording the dialogue of two people freely conversing on a variety of topics and manually transcribing the utterances. The transcription provides a dual transcription consisting of orthography and pronunciation, and disfluency tags for spontaneity of speech, such as filler words, repeated words, and word fragments. This paper also presents the baseline performance of an end-to-end speech recognition model trained with KsponSpeech. In addition, we investigated the performance of standard end-to-end architectures and the number of sub-word units suitable for Korean. We investigated issues that should be considered in spontaneous speech recognition in Korean. KsponSpeech is publicly available on an open data hub site of the Korea government.},
DOI = {10.3390/app10196936}
}
```
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Nikutka/L1_scraped_korpus_pelny | Nikutka | 2022-11-19T17:15:54Z | 15 | 0 | null | [
"region:us"
] | 2022-11-19T17:15:54Z | 2022-11-19T16:50:52.000Z | 2022-11-19T16:50:52 | ---
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---
# Dataset Card for "L1_scraped_korpus_pelny"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Nikutka/L1_poleval_korpus_pelny | Nikutka | 2022-11-19T16:51:39Z | 15 | 0 | null | [
"region:us"
] | 2022-11-19T16:51:39Z | 2022-11-19T16:51:32.000Z | 2022-11-19T16:51:32 | ---
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---
# Dataset Card for "L1_poleval_korpus_pelny"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Nikutka/L1_poleval_korpus_wzorcowy | Nikutka | 2022-11-19T16:52:02Z | 15 | 0 | null | [
"region:us"
] | 2022-11-19T16:52:02Z | 2022-11-19T16:51:55.000Z | 2022-11-19T16:51:55 | ---
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download_size: 18165
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---
# Dataset Card for "L1_poleval_korpus_wzorcowy"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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galman33/gal_yair_8300_100x100_fixed | galman33 | 2022-11-26T13:15:23Z | 15 | 0 | null | [
"region:us"
] | 2022-11-26T13:15:23Z | 2022-11-19T22:43:01.000Z | 2022-11-19T22:43:01 | ---
dataset_info:
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dtype: image
splits:
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num_bytes: 142019429.5
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download_size: 141877783
dataset_size: 142019429.5
---
# Dataset Card for "gal_yair_8300_100x100_fixed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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hounst/whitn | hounst | 2022-11-20T01:18:07Z | 15 | 0 | null | [
"license:cc",
"region:us"
] | 2022-11-20T01:18:07Z | 2022-11-20T00:55:52.000Z | 2022-11-20T00:55:52 | ---
license: cc
---
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Tomaszek12/Seba-model | Tomaszek12 | 2022-11-20T12:28:45Z | 15 | 0 | null | [
"region:us"
] | 2022-11-20T12:28:45Z | 2022-11-20T12:27:42.000Z | 2022-11-20T12:27:42 | Entry not found | [
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shahidul034/text_summarization_dataset5 | shahidul034 | 2022-11-20T13:07:26Z | 15 | 0 | null | [
"region:us"
] | 2022-11-20T13:07:26Z | 2022-11-20T13:07:21.000Z | 2022-11-20T13:07:21 | ---
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dataset_size: 144216578
---
# Dataset Card for "text_summarization_dataset5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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shahidul034/text_summarization_dataset6 | shahidul034 | 2022-11-20T13:08:33Z | 15 | 0 | null | [
"region:us"
] | 2022-11-20T13:08:33Z | 2022-11-20T13:08:28.000Z | 2022-11-20T13:08:28 | ---
dataset_info:
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---
# Dataset Card for "text_summarization_dataset6"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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autoevaluate/autoeval-staging-eval-project-304eb14a-d97c-4ab5-a495-bcda04ee4f5c-2927 | autoevaluate | 2022-11-20T13:14:26Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-20T13:14:26Z | 2022-11-20T13:13:49.000Z | 2022-11-20T13:13:49 | ---
type: predictions
tags:
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- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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SergiiGurbych/Sent_anal_ukr_multi_manual | SergiiGurbych | 2022-11-20T19:15:23Z | 15 | 0 | null | [
"region:us"
] | 2022-11-20T19:15:23Z | 2022-11-20T19:04:37.000Z | 2022-11-20T19:04:37 | This dataset is the extension of the existing dataset Sent_anal_ukr_manual (which was made for binary classification). It includes negative (0), positive (1) and neutral (2) sentences, labeled manually. Part of sentences were taken from the book "Francesca. The Queen of Trajectories" by Dorje Batuu (Andriy Vasyliev), a modern Ukrainian author. | [
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0.31832864880561... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-7f2fc5f3-83ca-46d6-b659-8dd44f75eacd-3028 | autoevaluate | 2022-11-20T19:36:34Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-20T19:36:34Z | 2022-11-20T19:35:53.000Z | 2022-11-20T19:35:53 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-eval-conll2003-conll2003-962530-2172769890 | autoevaluate | 2022-11-20T22:37:01Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-20T22:37:01Z | 2022-11-20T22:35:45.000Z | 2022-11-20T22:35:45 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- conll2003
eval_info:
task: entity_extraction
model: classtest/berttest2
metrics: []
dataset_name: conll2003
dataset_config: conll2003
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: classtest/berttest2
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@classtest](https://huggingface.co/classtest) for evaluating this model. | [
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osanseviero/yannic_test2 | osanseviero | 2022-11-22T06:54:05Z | 15 | 1 | null | [
"task_categories:automatic-speech-recognition",
"whisper",
"whispering",
"large",
"region:us"
] | 2022-11-22T06:54:05Z | 2022-11-21T03:23:00.000Z | 2022-11-21T03:23:00 | ---
task_categories:
- automatic-speech-recognition
dataset_info:
features:
- name: CHANNEL_NAME
dtype: string
- name: URL
dtype: string
- name: TITLE
dtype: string
- name: DESCRIPTION
dtype: string
- name: TRANSCRIPTION
dtype: string
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dtype: string
splits:
- name: train
num_bytes: 22634324
num_examples: 260
download_size: 10407175
dataset_size: 22634324
tags:
- whisper
- whispering
- large
---
# Dataset Card for "yannic_test2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269957 | autoevaluate | 2022-11-21T07:46:38Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:46:38Z | 2022-11-21T05:08:33.000Z | 2022-11-21T05:08:33 | ---
type: predictions
tags:
- autotrain
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datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-7b1
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-7b1
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269958 | autoevaluate | 2022-11-21T05:48:24Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:48:24Z | 2022-11-21T05:08:33.000Z | 2022-11-21T05:08:33 | ---
type: predictions
tags:
- autotrain
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datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-1b7
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-1b7
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269959 | autoevaluate | 2022-11-21T05:38:51Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:38:51Z | 2022-11-21T05:14:05.000Z | 2022-11-21T05:14:05 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-1b1
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-1b1
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269960 | autoevaluate | 2022-11-21T05:39:13Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:39:13Z | 2022-11-21T05:14:39.000Z | 2022-11-21T05:14:39 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-560m
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-560m
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569971 | autoevaluate | 2022-11-21T11:48:55Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:48:55Z | 2022-11-21T06:03:29.000Z | 2022-11-21T06:03:29 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-13b
metrics: []
dataset_name: futin/feed
dataset_config: top_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: futin/feed
* Config: top_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569972 | autoevaluate | 2022-11-21T09:24:28Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:24:28Z | 2022-11-21T06:09:45.000Z | 2022-11-21T06:09:45 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-6.7b
metrics: []
dataset_name: futin/feed
dataset_config: top_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: top_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669977 | autoevaluate | 2022-11-22T02:38:23Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-22T02:38:23Z | 2022-11-21T07:15:24.000Z | 2022-11-21T07:15:24 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-66b
metrics: []
dataset_name: futin/feed
dataset_config: sen_vi
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669978 | autoevaluate | 2022-11-21T15:42:35Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T15:42:35Z | 2022-11-21T07:20:53.000Z | 2022-11-21T07:20:53 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-30b
metrics: []
dataset_name: futin/feed
dataset_config: sen_vi
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769988 | autoevaluate | 2022-11-21T11:32:30Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:32:30Z | 2022-11-21T09:19:19.000Z | 2022-11-21T09:19:19 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-6.7b
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769989 | autoevaluate | 2022-11-21T09:42:14Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:42:14Z | 2022-11-21T09:32:41.000Z | 2022-11-21T09:32:41 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-350m
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-350m
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769990 | autoevaluate | 2022-11-21T10:30:32Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:30:32Z | 2022-11-21T09:50:16.000Z | 2022-11-21T09:50:16 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-2.7b
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-2.7b
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769992 | autoevaluate | 2022-11-21T10:30:40Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:30:40Z | 2022-11-21T10:25:57.000Z | 2022-11-21T10:25:57 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/feed
eval_info:
task: text_zero_shot_classification
model: facebook/opt-125m
metrics: []
dataset_name: futin/feed
dataset_config: sen_en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/feed
* Config: sen_en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-50a56796-db2d-4349-bf75-388efb52b967-3634 | autoevaluate | 2022-11-21T10:34:05Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:34:05Z | 2022-11-21T10:33:29.000Z | 2022-11-21T10:33:29 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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polinaeterna/test_push_default | polinaeterna | 2022-11-21T11:05:37Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T11:05:37Z | 2022-11-21T10:40:26.000Z | 2022-11-21T10:40:26 | ---
dataset_info:
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splits:
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download_size: 854
dataset_size: 162
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features:
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dtype: int64
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splits:
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num_bytes: 74
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num_examples: 6
download_size: 0
dataset_size: 162
---
# Dataset Card for "test_push_default"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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autoevaluate/autoeval-staging-eval-project-48057538-ec1b-4e18-ac2b-35070fb8202e-3735 | autoevaluate | 2022-11-21T10:45:25Z | 15 | 0 | null | [
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"evaluation",
"region:us"
] | 2022-11-21T10:45:25Z | 2022-11-21T10:44:49.000Z | 2022-11-21T10:44:49 | ---
type: predictions
tags:
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datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-be841b2c-fd99-4cdf-be00-1a826c9f1b02-4038 | autoevaluate | 2022-11-21T11:12:59Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:12:59Z | 2022-11-21T11:12:23.000Z | 2022-11-21T11:12:23 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-0919d128-ac07-4f9a-b929-706957da9f2e-4341 | autoevaluate | 2022-11-21T11:31:50Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:31:50Z | 2022-11-21T11:31:02.000Z | 2022-11-21T11:31:02 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-8abfadbc-69e6-47d0-afdc-f5859c5e0d16-4442 | autoevaluate | 2022-11-21T11:38:08Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:38:08Z | 2022-11-21T11:37:25.000Z | 2022-11-21T11:37:25 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-688c59a8-44a3-4de2-8b30-d3e76d3addf5-4543 | autoevaluate | 2022-11-21T12:42:01Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:42:01Z | 2022-11-21T12:41:17.000Z | 2022-11-21T12:41:17 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-5a4fda18-6304-4b90-86c0-99202bfbe1e9-4644 | autoevaluate | 2022-11-21T12:46:22Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:46:22Z | 2022-11-21T12:45:40.000Z | 2022-11-21T12:45:40 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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-0.25194665789604187,
0.2500534653663635,
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-4144bd7b-94bf-4e9e-87a5-f722d28cd7cd-4745 | autoevaluate | 2022-11-21T12:59:31Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:59:31Z | 2022-11-21T12:58:49.000Z | 2022-11-21T12:58:49 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
-0.4580225646495819,
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0.2500534653663635,
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-636a44ed-fa98-4717-b181-b742a86b03be-4846 | autoevaluate | 2022-11-21T13:02:29Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:02:29Z | 2022-11-21T13:01:47.000Z | 2022-11-21T13:01:47 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.2500534653663635,
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0.02388732135295868,
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DTU54DL/commo-test1k-whisper-proc | DTU54DL | 2022-11-21T13:30:24Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T13:30:24Z | 2022-11-21T13:08:42.000Z | 2022-11-21T13:08:42 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: Acronym Identification Dataset
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- token-classification-other-acronym-identification
train-eval-index:
- col_mapping:
labels: tags
tokens: tokens
config: default
splits:
eval_split: test
task: token-classification
task_id: entity_extraction---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
| [
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autoevaluate/autoeval-staging-eval-project-2302ec60-cb56-482a-8d70-ce549b14fd54-5149 | autoevaluate | 2022-11-21T13:14:43Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:14:43Z | 2022-11-21T13:14:01.000Z | 2022-11-21T13:14:01 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-318525f4-cdf7-4888-965c-d4d9dfeeca48-5250 | autoevaluate | 2022-11-21T13:20:39Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:20:39Z | 2022-11-21T13:19:56.000Z | 2022-11-21T13:19:56 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: autoevaluate/multi-class-classification
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.0498039796948... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-5c51f1de-f5e2-46a7-861f-b1b7c80db774-5351 | autoevaluate | 2022-11-21T13:26:28Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:26:28Z | 2022-11-21T13:25:52.000Z | 2022-11-21T13:25:52 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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DRNAnimations/Kirby | DRNAnimations | 2022-11-21T13:34:13Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T13:34:13Z | 2022-11-21T13:31:56.000Z | 2022-11-21T13:31:56 | Entry not found | [
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autoevaluate/autoeval-staging-eval-project-a02353d8-c94a-4476-bd14-15028ee3f918-5452 | autoevaluate | 2022-11-21T13:33:16Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:33:16Z | 2022-11-21T13:32:44.000Z | 2022-11-21T13:32:44 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- autoevaluate/zero-shot-classification-sample
eval_info:
task: text_zero_shot_classification
model: autoevaluate/zero-shot-classification
metrics: []
dataset_name: autoevaluate/zero-shot-classification-sample
dataset_config: autoevaluate--zero-shot-classification-sample
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: autoevaluate/zero-shot-classification
* Dataset: autoevaluate/zero-shot-classification-sample
* Config: autoevaluate--zero-shot-classification-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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-0.02573315240442... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-31466167-6d47-4d63-9ebd-59fe66b62d96-5553 | autoevaluate | 2022-11-21T13:39:35Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:39:35Z | 2022-11-21T13:38:58.000Z | 2022-11-21T13:38:58 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.0483857765793... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-fa97c361-989b-438c-bd2b-73aa1588c214-5654 | autoevaluate | 2022-11-21T13:46:15Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:46:15Z | 2022-11-21T13:45:42.000Z | 2022-11-21T13:45:42 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.0483857765793... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-03e83e3b-2528-4e84-b075-34edd28549da-5755 | autoevaluate | 2022-11-21T13:54:09Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:54:09Z | 2022-11-21T13:53:36.000Z | 2022-11-21T13:53:36 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.250057190656662,
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0.04298580065369606,
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-0.6307750940322876,
0.0483857765793... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
polinaeterna/texts_configs | polinaeterna | 2022-11-22T10:40:54Z | 15 | 0 | null | [
"region:us"
] | 2022-11-22T10:40:54Z | 2022-11-21T14:01:15.000Z | 2022-11-21T14:01:15 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-6ba515cb-e9ef-49fe-9bb8-a4281c03605e-5856 | autoevaluate | 2022-11-21T14:04:47Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:04:47Z | 2022-11-21T14:04:10.000Z | 2022-11-21T14:04:10 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.4714495837688446,
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-0.6307750940322876,
0.0483857765793... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-371fafb5-556b-4565-a7bf-530b1396895e-5957 | autoevaluate | 2022-11-21T14:11:01Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:11:01Z | 2022-11-21T14:10:27.000Z | 2022-11-21T14:10:27 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
-0.4283809959888458,
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0.250057190656662,
0.19630765914916992,
0.04298580065369606,
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0.16937695443630219,
0.4714495837688446,
-1.0458141565322876,
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-0.6307750940322876,
0.0483857765793... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-19f625bb-a07b-4f3a-bec2-d734d6029176-6159 | autoevaluate | 2022-11-21T14:19:12Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:19:12Z | 2022-11-21T14:18:39.000Z | 2022-11-21T14:18:39 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- autoevaluate/conll2003-sample
eval_info:
task: entity_extraction
model: autoevaluate/entity-extraction
metrics: []
dataset_name: autoevaluate/conll2003-sample
dataset_config: autoevaluate--conll2003-sample
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: autoevaluate/entity-extraction
* Dataset: autoevaluate/conll2003-sample
* Config: autoevaluate--conll2003-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.04434997588396... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
KnutJaegersberg/interpretable_word_embeddings | KnutJaegersberg | 2022-11-25T12:10:11Z | 15 | 1 | null | [
"license:mit",
"region:us"
] | 2022-11-25T12:10:11Z | 2022-11-21T14:21:38.000Z | 2022-11-21T14:21:38 | ---
license: mit
---
These word embeddings were computed using the POLAR technique to reproject 'common' word embeddings into roundabout 700 interpretable dimensions of polar opposites (i.e. good/bad).
I just used their scripts here:
https://github.com/Sandipan99/POLAR
I applied those on the wikidata5m embeddings, 5 million knowledge graph embeddings (SimplE).
https://graphvite.io/docs/latest/pretrained_model.html
As the model became too huge, I further filtered it for overlap with fasttext embedding tokens.
Not all dimensions make sense, this is a work in progress.
I intend to remove dimensions which turn out to not make sense, when using them. | [
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0.07311566919088364... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
MikCil/un_dataset | MikCil | 2022-11-21T14:45:38Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T14:45:38Z | 2022-11-21T14:44:54.000Z | 2022-11-21T14:44:54 | ---
dataset_info:
features:
- name: image
dtype: image
- name: caption
dtype: string
splits:
- name: train
num_bytes: 462328883.0
num_examples: 904
- name: validation
num_bytes: 462328883.0
num_examples: 904
download_size: 924654154
dataset_size: 924657766.0
---
# Dataset Card for "un_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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nkandpa2/qa_entities | nkandpa2 | 2022-11-21T17:04:24Z | 15 | 1 | null | [
"license:bigscience-openrail-m",
"region:us"
] | 2022-11-21T17:04:24Z | 2022-11-21T16:28:21.000Z | 2022-11-21T16:28:21 | ---
license: bigscience-openrail-m
---
| [
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dvgodoy/auto-mpg-split | dvgodoy | 2022-11-21T16:46:31Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T16:46:31Z | 2022-11-21T16:28:39.000Z | 2022-11-21T16:28:39 | ---
dataset_info:
features:
- name: mpg
dtype: float64
- name: cylinders
dtype: int64
- name: displacement
dtype: float64
- name: horsepower
dtype: float64
- name: weight
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- name: acceleration
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- name: model year
dtype: int64
- name: origin
dtype: int64
- name: car name
dtype: string
splits:
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num_examples: 318
- name: test
num_bytes: 3363.819095477387
num_examples: 40
- name: valid
num_bytes: 3363.819095477387
num_examples: 40
download_size: 22370
dataset_size: 33470.0
---
# Dataset Card for "auto-mpg-split"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
dvgodoy/auto-mpg | dvgodoy | 2022-11-21T16:45:37Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T16:45:37Z | 2022-11-21T16:37:13.000Z | 2022-11-21T16:37:13 | ---
dataset_info:
features:
- name: mpg
dtype: float64
- name: cylinders
dtype: int64
- name: displacement
dtype: float64
- name: horsepower
dtype: float64
- name: weight
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dtype: int64
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dtype: int64
- name: car name
dtype: string
splits:
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num_bytes: 33470
num_examples: 398
download_size: 13036
dataset_size: 33470
---
# Dataset Card for "auto-mpg"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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xtreme-s/submissions | xtreme-s | 2022-11-21T16:56:02Z | 15 | 0 | null | [
"region:us"
] | 2022-11-21T16:56:02Z | 2022-11-21T16:55:37.000Z | 2022-11-21T16:55:37 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
mcrovero/icons | mcrovero | 2022-11-21T17:14:38Z | 15 | 0 | null | [
"license:gpl",
"region:us"
] | 2022-11-21T17:14:38Z | 2022-11-21T17:11:10.000Z | 2022-11-21T17:11:10 | ---
license: gpl
---
| [
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-0.0478260256350... | null | null | null | null | null | null | null | null | null | null | null | null | null |
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