modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
andi611/distilbert-base-uncased-qa-boolq | [
"False",
"True"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- boolq
metrics:
- accuracy
model_index:
- name: distilbert-base-uncased-boolq
results:
- task:
name: Question Answering
type: question-answering
dataset:
name: boolq
type: boolq
args: default
metri... | 1,900 |
Hate-speech-CNERG/dehatebert-mono-indonesian | [
"NON_HATE",
"HATE"
] | This model is used detecting **hatespeech** in **Indonesian language**. The mono in the name refers to the monolingual setting, where the model is trained using only Arabic language data. It is finetuned on multilingual bert model.
The model is trained with different learning rates and the best validation score achieve... | 1,019 |
liam168/c2-roberta-base-finetuned-dianping-chinese | [
"negative",
"positive"
] | ---
language: zh
widget:
- text: "我喜欢下雨。"
- text: "我讨厌他。"
---
# liam168/c2-roberta-base-finetuned-dianping-chinese
## Model description
用中文对话情绪语料训练的模型，2分类：乐观和悲观。
## Overview
- **Language model**: BertForSequenceClassification
- **Model size**: 410M
- **Language**: Chinese
## Example
```python
>>> from transform... | 921 |
lincoln/flaubert-mlsum-topic-classification | [
"Culture",
"Economie",
"Education",
"Environement",
"Justice",
"Opinion",
"Politique",
"Societe",
"Sport",
"Technologie"
] | ---
language:
- fr
license: mit
datasets:
- MLSUM
pipeline_tag: "text-classification"
widget:
- text: La bourse de paris en forte baisse après que des canards ont envahit le parlement.
tags:
- text-classification
- flaubert
---
# Classification d'articles de presses avec Flaubert
Ce modèle se base sur le modèl... | 5,264 |
uer/roberta-base-finetuned-ifeng-chinese | [
"International news",
"Taiwan - Hong Kong - Macau politics",
"mainland China politics",
"military news",
"society news"
] | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... | 5,141 |
Toshifumi/bert-base-multilingual-cased-finetuned-emotion | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: bert-base-multilingual-cased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: de... | 1,827 |
Supreeth/Toxic-XLM_RoBERTa | null | ---
license: afl-3.0
---
| 25 |
ArnavL/roberta-base-imdb-0 | null | Entry not found | 15 |
Jorgeutd/sagemaker-roberta-base-emotion | [
"anger",
"fear",
"joy",
"love",
"sadness",
"surprise"
] |
---
language: en
widget:
- text: "I am really upset that I have to call up to three times to the number on the back of my insurance card for my call to be answer"
tags:
- sagemaker
- roberta-base
- text classification
license: apache-2.0
datasets:
- emotion
model-index:
- name: sagemaker-roberta-base-emotion
results... | 1,425 |
SimonZvara/Memes-CS_1.0 | [
"LABEL_0"
] | Model used by Memes-CS (Metric for Evaluating Model Efficiency in Summarization).
Part of my bachelor's thesis.
Šimon Zvára | 125 |
waboucay/camembert-large-finetuned-xnli_fr_3_classes-finetuned-rua_wl_3_classes | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- fr
tags:
- nli
metrics:
- f1
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 72.4 | 72.2 |
| test ... | 367 |
Anupama/distilbert-base-uncased-finetuned-emotion | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... | 1,804 |
textattack/distilbert-base-uncased-MRPC | null | ## TextAttack Model Card
This `distilbert-base-uncased` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 32, a learning
rate of 2e-05, and a maximum sequence length of 256.
Since this was... | 628 |
Jackett/subject_classifier_extended | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | Label mappings
{'LABEL_0':'Biology','LABEL_1':'Physics','LABEL_2':'Chemistry','LABEL_3':'Maths','LABEL_4':'Social Science','LABEL_5':'English'}
Training data distribution
Physics - 7000
Maths - 7000
Biology - 7000
Chemistry - 7000
English - 5254
Social Science - 7000 | 270 |
arghya007/roberta-scarcasm-discriminator | null | Entry not found | 15 |
BNZSA/distilbert-base-uncased-country-NER-address | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_100",
"LABEL_1000",
"LABEL_10000",
"LABEL_10001",
"LABEL_10002",
"LABEL_10003",
"LABEL_10004",
"LABEL_10005",
"LABEL_10006",
"LABEL_10007",
"LABEL_10008",
"LABEL_10009",
"LABEL_1001",
"LABEL_10010",
"LABEL_10011",
"LABEL_10012",
"LABEL_1... | ---
license: gpl-3.0
---
| 25 |
M-FAC/bert-mini-finetuned-mrpc | null | # BERT-mini model finetuned with M-FAC
This model is finetuned on MRPC dataset with state-of-the-art second-order optimizer M-FAC.
Check NeurIPS 2021 paper for more details on M-FAC: [https://arxiv.org/pdf/2107.03356.pdf](https://arxiv.org/pdf/2107.03356.pdf).
## Finetuning setup
For fair comparison against default ... | 2,785 |
ZiweiG/ziwei-bertimdb-prob | null | Entry not found | 15 |
nickmuchi/deberta-v3-base-finetuned-finance-text-classification | [
"bearish",
"bullish",
"neutral"
] | ---
license: mit
tags:
- generated_from_trainer
- financial-sentiment-analysis
- sentiment-analysis
- sentence_50agree
- financial
- stocks
- sentiment
datasets:
- financial_phrasebank
- Kaggle Self label
- nickmuchi/financial-classification
widget:
- text: "The USD rallied by 3% last night as the Fed hiked interest ra... | 3,846 |
ZiweiG/ziwei-bert-imdb | null | Entry not found | 15 |
cardiffnlp/bertweet-base-emoji | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_19",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | 0 | |
kssteven/ibert-roberta-large-mnli | [
"CONTRADICTION",
"NEUTRAL",
"ENTAILMENT"
] | Entry not found | 15 |
philschmid/tiny-distilbert-classification | [
"NEGATIVE",
"POSITIVE"
] | # Test model
> ## This model is used to run tests for the Hugging Face DLCs | 77 |
IsaacRodgz/Tamil-Hate-Speech | [
"Hate-Speech",
"Non-Hate-Speech"
] | Entry not found | 15 |
Farshid/distilbert-base-uncased_allagree3 | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased_allagree3
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial... | 2,432 |
AhmedBou/TuniBert | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
Luyu/bert-base-mdoc-hdct | [
"LABEL_0"
] | ---
language:
- en
tags:
- text reranking
license: apache-2.0
datasets:
- MS MARCO document ranking
---
# BERT Reranker for MS-MARCO Document Ranking
## Model description
A text reranker trained for HDCT retriever on MS MARCO document dataset.
## Intended uses & limitations
It is possible to work with other retriev... | 881 |
Narrativa/distilroberta-finetuned-stereotype-detection | [
"neutral",
"stereotype",
"anti-stereotype"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- stereotype
- gender
- gender_bias
widget:
- text: "Cauterize is not just for fans of the guitarist or his other projects, but those that love music that is both aggressive and infectious and gave the album 4 out of 5 stars ."
metrics:
- accuracy
model-index:
- na... | 2,194 |
Prompsit/paraphrase-bert-en | [
"Not Paraphrase",
"Paraphrase"
] | ---
pipeline_tag: text-classification
inference: false
language: en
tags:
- transformers
---
# Prompsit/paraphrase-bert-en
This model allows to evaluate paraphrases for a given phrase.
We have fine-tuned this model from pretrained "bert-base-uncased".
Model built under a TSI-100905-2019-4 project, co-financed by M... | 2,114 |
transformersbook/distilbert-base-uncased-finetuned-clinc | [
"accept_reservations",
"account_blocked",
"alarm",
"application_status",
"apr",
"are_you_a_bot",
"balance",
"bill_balance",
"bill_due",
"book_flight",
"book_hotel",
"calculator",
"calendar",
"calendar_update",
"calories",
"cancel",
"cancel_reservation",
"car_rental",
"card_declin... | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | 2,246 |
MoritzLaurer/covid-policy-roberta-21 | [
"Anti-Disinformation Measures",
"COVID-19 Vaccines",
"Closure and Regulation of Schools",
"Curfew",
"Declaration of Emergency",
"External Border Restrictions",
"Health Monitoring",
"Health Resources",
"Health Testing",
"Hygiene",
"Internal Border Restrictions",
"Lockdown",
"New Task Force, B... | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy (balanced)
- F1 (weighted)
widget:
- text: "All non-essential work activity will stop in Spain from tomorrow until 9 April but there is some confusion as to which jobs can continue under the new lockdown restrictions"
---
# Covid-Policy-RoBERTa-21
Thi... | 729 |
totoro4007/cryptoroberta-base-finetuned | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
adamnik/bert-entailment-detection | null | ---
license: mit
---
| 21 |
monologg/koelectra-base-finetuned-nsmc | [
"negative",
"positive"
] | Entry not found | 15 |
Hate-speech-CNERG/dehatebert-mono-polish | [
"NON_HATE",
"HATE"
] | ---
language: pl
license: apache-2.0
---
This model is used detecting **hatespeech** in **Polish language**. The mono in the name refers to the monolingual setting, where the model is trained using only English language data. It is finetuned on multilingual bert model.
The model is trained with different learning rates... | 1,057 |
hf-internal-testing/tiny-plbart | null | Entry not found | 15 |
DLochmelis33/22s-dl-sentiment-1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
model-index:
- name: 22s-dl-sentiment-1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_review_full
type: yelp_review_full
args: yelp_rev... | 1,453 |
PGT/graphnystromformer-artificial-balanced-max500-490000-0 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6"
] | Entry not found | 15 |
boychaboy/SNLI_bert-large-uncased | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
edwardgowsmith/pt-finegrained-few-shot | null | Entry not found | 15 |
lewtun/bert-large-uncased-wwm-finetuned-boolq | null | Entry not found | 15 |
pedropei/aspect-level-certainty | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
prajjwal1/albert-base-v2-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | If you use the model, please consider citing the paper
```
@misc{bhargava2021generalization,
title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics},
author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers},
year={2021},
eprint={2110.01518},
archivePrefix={arXiv},
... | 479 |
navteca/ms-marco-MiniLM-L-12-v2 | [
"LABEL_0"
] | ---
language: en
license: mit
pipeline_tag: text-classification
tags:
- sentence-transformers
---
# Cross-Encoder for MS Marco
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. ... | 2,597 |
James-kc-min/AGT_Roberta2 | null | Hugging Face's logo
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Text Classification
PyTorch
Transformers
apache-2.0
roberta
generated_from_traine... | 1,584 |
RogerKam/roberta_fine_tuned_sentiment_newsmtsc | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_fine_tuned_sentiment_newsmtsc
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this ... | 1,180 |
amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061 | [
"negative",
"neutral",
"positive"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- amansolanki/autonlp-data-Tweet-Sentiment-Extraction
co2_eq_emissions: 3.651199395353127
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 20114061
- CO2 Emissions (in grams): 3.651199395353127
## Val... | 1,447 |
fabriceyhc/bert-base-uncased-ag_news | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: bert-base-uncased-ag_news
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ag_news
type: ag_news
args: default
metrics:... | 3,204 |
projecte-aina/roberta-base-ca-cased-sts | [
"SIMILARITY"
] | ---
language:
- ca
pipeline_tag: text-classification
license: apache-2.0
tags:
- "catalan"
- "semantic textual similarity"
- "sts-ca"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "projecte-aina/sts-ca"
metrics:
- "pearson"
model-index:
- name: roberta-base-ca-cased-sts
results:
- task:
type: text-clas... | 3,903 |
textattack/distilbert-base-uncased-QNLI | null | Entry not found | 15 |
AlekseyDorkin/xlm-roberta-en-ru-emoji | [
"☀",
"✨",
"❤",
"🇺🇸",
"🎄",
"💕",
"💙",
"💜",
"💯",
"📷",
"📸",
"🔥",
"😁",
"😂",
"😉",
"😊",
"😍",
"😎",
"😘",
"😜"
] | ---
language:
- en
- ru
datasets:
- tweet_eval
model_index:
- name: xlm-roberta-en-ru-emoji
results:
- task:
name: Sentiment Analysis
type: sentiment-analysis
dataset:
name: Tweet Eval
type: tweet_eval
args: emoji
widget:
- text: "Отлично!"
- text: "Awesome!"
- text: "l... | 399 |
adrianmoses/autonlp-auto-nlp-lyrics-classification-19333717 | [
"Dance",
"Heavy Metal",
"Hip Hop",
"Indie",
"Pop",
"Rock"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- adrianmoses/autonlp-data-auto-nlp-lyrics-classification
co2_eq_emissions: 88.89388195672073
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 19333717
- CO2 Emissions (in grams): 88.89388195672073
##... | 1,465 |
chihao/bert_cn_finetuning | [
"LABEL_0",
"LABEL_1"
] | Entry not found | 15 |
chitra/distilbert-negation | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
kco4776/soongsil-bert-wellness | [
"감정",
"내원이유",
"모호함",
"배경",
"부가설명",
"상태",
"원인",
"일반대화",
"자가치료",
"증상",
"치료이력",
"현재상태"
] | ## References
- [Soongsil-BERT](https://github.com/jason9693/Soongsil-BERT) | 75 |
m3hrdadfi/albert-fa-base-v2-clf-persiannews | [
"اجتماعی",
"اقتصادی",
"بین الملل",
"سیاسی",
"علمی فناوری",
"فرهنگی هنری",
"ورزشی",
"پزشکی"
] | ---
language: fa
license: apache-2.0
---
# ALBERT Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
[ALBERT-Persian](https://github.com/m3hrdadfi/albert-persian) is the first attempt on ALBERT for the Persian Language. The model was tra... | 2,676 |
poom-sci/bert-base-uncased-multi-emotion | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_19",
"LABEL_2",
"LABEL_20",
"LABEL_21",
"LABEL_22",
"LABEL_23",
"LABEL_24",
"LABEL_25",
"LABEL_26",
"LABEL_27",
"LABEL_3",
"LABEL_4",
... | ---
language:
- en
tags:
- translation
license: apache-2.0
datasets:
- go_emotions
---
created for study | 105 |
adamnik/bert-event-detection | null | ---
license: mit
---
| 21 |
A-bhimany-u08/bert-base-cased-qqp | null |
---
inference: False
datasets:
- qqp
---
bert-base-cased model trained on quora question pair dataset. The task requires to predict whether the two given sentences (or questions) are `not_duplicate` (label 0) or `duplicate` (label 1). The model achieves 89% evaluation accuracy
| 318 |
Cameron/BERT-jigsaw-severetoxic | null | Entry not found | 15 |
M-FAC/bert-mini-finetuned-sst2 | null | # BERT-mini model finetuned with M-FAC
This model is finetuned on SST-2 dataset with state-of-the-art second-order optimizer M-FAC.
Check NeurIPS 2021 paper for more details on M-FAC: [https://arxiv.org/pdf/2107.03356.pdf](https://arxiv.org/pdf/2107.03356.pdf).
## Finetuning setup
For fair comparison against default... | 2,733 |
SparkBeyond/roberta-large-sts-b | [
"LABEL_0"
] |
# Roberta Large STS-B
This model is a fine tuned RoBERTA model over STS-B.
It was trained with these params:
!python /content/transformers/examples/text-classification/run_glue.py \
--model_type roberta \
--model_name_or_path roberta-large \
--task_name STS-B \
--do_train \
--do_eval \
--do_l... | 1,949 |
emrecan/convbert-base-turkish-mc4-cased-allnli_tr | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- tr
tags:
- zero-shot-classification
- nli
- pytorch
pipeline_tag: zero-shot-classification
license: apache-2.0
datasets:
- nli_tr
metrics:
- accuracy
widget:
- text: "Dolar yükselmeye devam ediyor."
candidate_labels: "ekonomi, siyaset, spor"
- text: "Senaryo çok saçmaydı, beğendim diyemem."
candidat... | 7,095 |
lighteternal/fact-or-opinion-xlmr-el | null | ---
language:
- en
- el
- multilingual
tags:
- text-classification
- fact-or-opinion
- transformers
widget:
- text: "Ξεχωρίζει η καθηλωτική ερμηνεία του πρωταγωνιστή."
- text: "Η Ελλάδα είναι χώρα της Ευρώπης."
- text: "Tolkien was an English writer"
- text: "Tolkien is my favorite writer."
pipeline_tag: text-clas... | 1,847 |
dexay/reDs3others | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_19",
"LABEL_2",
"LABEL_20",
"LABEL_21",
"LABEL_22",
"LABEL_23",
"LABEL_24",
"LABEL_25",
"LABEL_26",
"LABEL_27",
"LABEL_28",
"LABEL_29",... | Entry not found | 15 |
Cameron/BERT-jigsaw-identityhate | null | Entry not found | 15 |
Emanuel/twitter-emotion-deberta-v3-base | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: twitter-emotion-deberta-v3-base
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
... | 921 |
NYTK/sentiment-hts2-xlm-roberta-hungarian | null | ---
language:
- hu
tags:
- text-classification
license: gpl
metrics:
- accuracy
widget:
- text: "Jó reggelt! majd küldöm az élményhozókat :)."
---
# Hungarian Sentence-level Sentiment Analysis model with XLM-RoBERTa
For further models, scripts and details, see [our repository](https://github.com/nytud/sentiment-... | 1,153 |
SetFit/deberta-v3-large__sst2__train-8-2 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comm... | 2,400 |
joeddav/distilbert-base-uncased-agnews-student | [
"business",
"science/tech",
"sports",
"the world"
] | ---
language: en
tags:
- text-classification
- pytorch
- tensorflow
datasets:
- ag_news
license: mit
widget:
- text: "Armed conflict has been a near-constant policial and economic burden."
- text: "Tom Brady won his seventh Super Bowl last night."
- text: "Dow falls more than 100 points after disappointing jobs data"
-... | 1,290 |
pparasurama/raceBERT | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | Entry not found | 15 |
DaNLP/da-bert-hatespeech-classification | [
"Personangreb",
"Spam & indhold",
"Sprogbrug",
"Særlig opmærksomhed"
] | ---
language:
- da
tags:
- bert
- pytorch
- hatespeech
license: cc-by-sa-4.0
datasets:
- social media
metrics:
- f1
widget:
- text: "Senile gamle idiot"
---
# Danish BERT for hate speech classification
The BERT HateSpeech model classifies offensive Danish text into 4 categories:
* `Særlig opmærksomhed` (special att... | 1,341 |
LeoFeng/ChineseSequenceClassification | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | 利用THUC dataset 訓練的文章分類器，共支援14種種類 | 32 |
sangrimlee/bert-base-multilingual-cased-nsmc | null | ---
language: ko
---
# BERT multilingual basecased finetuned with NSMC
This model is a fine-tune checkpoint of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased), fine-tuned on [NSMC(Naver Sentiment Movie Corpus)](https://github.com/e9t/nsmc).
## Usage
You can use this model directl... | 724 |
Inari/deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy
datasets:
- snli-1.0
- multi-nli-1.0
- nli-fever
- anli-v1.0
widget:
- text: "British mountaineer Alison Hargreaves becomes the first woman to climb Mount Everest alone and without oxygen tanks. [SEP] Alison is a female."
- text: "Mr Lopez Obrador has ... | 1,358 |
MoritzLaurer/xtremedistil-l6-h256-mnli-fever-anli-ling-binary | [
"entailment",
"not_entailment"
] | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
datasets:
- multi_nli
- anli
- fever
- lingnli
pipeline_tag: zero-shot-classification
---
# xtremedistil-l6-h256-mnli-fever-anli-ling-binary
## Model description
This model was trained on 782 357 hypothesis-premise pairs fro... | 4,083 |
boychaboy/MNLI_distilroberta-base | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
cardiffnlp/bertweet-base-stance-feminist | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
textattack/xlnet-large-cased-SST-2 | null | Entry not found | 15 |
turing-usp/FinBertPTBR | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: pt
license: apache-2.0
widget:
- text: "O futuro de DI caiu 20 bps nesta manhã"
example_title: "Example 1"
- text: "O Nubank decidiu cortar a faixa de preço da oferta pública inicial (IPO) após revés no humor dos mercados internacionais com as fintechs."
example_title: "Example 2"
- text: "O Ibovespa... | 1,224 |
uclanlp/plbart-c-cpp-defect-detection | null | Entry not found | 15 |
autoevaluate/multi-class-classification | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: multi-class-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- ... | 2,894 |
gchhablani/bert-base-cased-finetuned-stsb | [
"LABEL_0"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert-base-cased-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: ... | 2,829 |
hamzab/roberta-fake-news-classification | null | ---
license: mit
widget:
- text: "Some ninja attacked the White House."
example_title: "Fake example 1"
language:
- en
tags:
- classification
datasets:
- "fake-and-real-news-dataset on kaggle"
---
## Overview
The model is a `roberta-base` fine-tuned on [fake-and-real-news-dataset](https://www.kaggle.com/datasets/clme... | 1,883 |
tinkoff-ai/response-quality-classifier-large | [
"relevance",
"specificity"
] | ---
license: mit
widget:
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]супер, вот только проснулся, у тебя как?"
example_title: "Dialog example 1"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]норм"
example_title: "Dialog example 2"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESP... | 2,575 |
anlausch/aq_bert_ibm | [
"LABEL_0"
] | ---
license: mit
---
Model trained on IBMArgRank30k for 2 epochs with a learning rate of 3e-5 (optimised via grid search) in a similar way as in Lauscher et al. 2020 (see below). The original model was Tensorflow-based. This model corresponds to a reimplementation with Transformers & PyTorch.
```
@inproceedings{lausch... | 1,943 |
mvonwyl/distilbert-base-uncased-imdb | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name... | 2,392 |
semy/hf-model-full-0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hf-model-full-0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -... | 1,444 |
Darkrider/covidbert_medmarco | [
"LABEL_0"
] | Fine-tuned CovidBERT on Med-Marco Dataset for passage ranking
# CovidBERT-MedNLI
This is the model **CovidBERT** trained by DeepSet on AllenAI's [CORD19 Dataset](https://pages.semanticscholar.org/coronavirus-research) of scientific articles about coronaviruses.
The model uses the original BERT wordpiece vocabulary ... | 1,422 |
banjtheman/distilbert-base-uncased-helpful-amazon | null | ---
license: apache-2.0
---
## Overview
This model was trained with data from https://registry.opendata.aws/helpful-sentences-from-reviews/ to predict how "helpful" a review is.
The model was fine-tuned from the `distilbert-base-uncased` model
### Labels
LABEL_0 - Not helpful
LABEL_1 - Helpful
##... | 1,006 |
textattack/distilbert-base-uncased-RTE | null | ## TextAttack Model Card
This `distilbert-base-uncased` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 16, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this was... | 629 |
agnihotri/cuad_contract_type | [
"Affiliate Agreement",
"Agency Agreements",
"Co_Branding",
"Collaboration",
"Consulting Agreements",
"Development",
"Distributor",
"Endorsement Agreement",
"Franchise",
"Hosting",
"IP",
"Joint Venture",
"License_Agreements",
"Maintenance",
"Manufacturing",
"Marketing",
"Non_Compete_N... | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- agnihotri/autotrain-data-contract_type
co2_eq_emissions: 0.07610944071640048
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 809725368
- CO2 Emissions (in grams): 0.07610944071640048
## Valid... | 1,401 |
sam34738/bert-hinglish | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-hinglish
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-hinglish
This m... | 1,339 |
Cameron/BERT-mdgender-convai-ternary | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021 | null | ---
license: apache-2.0
tags:
-
datasets:
- EXIST Dataset
widget:
- text: "manejas muy bien para ser mujer"
- text: "En temas políticos hombres y mujeres son iguales"
- text: "Los ipad son unos equipos electrónicos"
metrics:
- accuracy
model-index:
- name: twitter_sexismo-finetuned-exist2021
results:
- task:
... | 7,840 |
qanastek/51-languages-classifier | [
"af-ZA",
"am-ET",
"ar-SA",
"az-AZ",
"bn-BD",
"cy-GB",
"da-DK",
"de-DE",
"el-GR",
"en-US",
"es-ES",
"fa-IR",
"fi-FI",
"fr-FR",
"he-IL",
"hi-IN",
"hu-HU",
"hy-AM",
"id-ID",
"is-IS",
"it-IT",
"ja-JP",
"jv-ID",
"ka-GE",
"km-KH",
"kn-IN",
"ko-KR",
"lv-LV",
"ml-IN",... | ---
tags:
- Transformers
- text-classification
- multi-class-classification
languages:
- af-ZA
- am-ET
- ar-SA
- az-AZ
- bn-BD
- cy-GB
- da-DK
- de-DE
- el-GR
- en-US
- es-ES
- fa-IR
- fi-FI
- fr-FR
- he-IL
- hi-IN
- hu-HU
- hy-AM
- id-ID
- is-IS
- it-IT
- ja-JP
- jv-ID
- ka-GE
- km-KH
- kn-IN
- ko-KR
- lv-LV
- ml-IN
-... | 7,528 |
MilaNLProc/hate-ita | [
"hateful",
"non-hateful"
] | ---
language: it
license: mit
tags:
- text classification
- abusive language
- hate speech
- offensive language
widget:
- text: "Ci sono dei bellissimi capibara!"
example_title: "Hate Speech Classification 1"
- text: "Sei una testa di cazzo!!"
example_title: "Hate Speech Classification 2"
- text: "Ti odio!"
exam... | 3,133 |
semy/finetuning-sentiment-model-sst | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetuning-sentiment-model-sst
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fine... | 1,037 |
naem1023/electra-phrase-clause-classification | null | ---
license: artistic-2.0
---
| 30 |
any0019/text_style_classifier | null | Entry not found | 15 |
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