modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
CAMeL-Lab/bert-base-arabic-camelbert-msa-poetry | [
"البسيط",
"الخفيف",
"الدوبيت",
"الرجز",
"الرمل",
"السريع",
"السلسلة",
"الطويل",
"الكامل",
"المتدارك",
"المتقارب",
"المجتث",
"المديد",
"المضارع",
"المقتضب",
"المنسرح",
"المواليا",
"الهزج",
"الوافر",
"شعر التفعيلة",
"شعر حر",
"عامي",
"موشح"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-MSA Poetry Classification Model
## Model description
**CAMeLBERT-MSA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Mod... | 3,393 |
Cameron/BERT-Jigsaw | null | Entry not found | 15 |
JonatanGk/roberta-base-bne-finetuned-cyberbullying-spanish | [
"Not_bullying",
"Bullying"
] | ---
language: es
tags:
- "spanish"
metrics:
- accuracy
widget:
- text: "Eres mas pequeño que un pitufo!"
- text: "Eres muy feo!"
- text: "Odio tu forma de hablar!"
- text: "Eres tan fea que cuando eras pequeña te echaban de comer por debajo de la puerta."
---
# roberta-base-bne-finetuned-ciberbullying-spanish
Th... | 2,686 |
Nenma/romanian-bert-fake-news | null | Entry not found | 15 |
TransQuest/monotransquest-da-ru_en-reddit_wikiquotes | [
"LABEL_0"
] | ---
language: ru-en
tags:
- Quality Estimation
- monotransquest
- DA
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-accuracy QE t... | 5,414 |
benjaminbeilharz/bert-base-uncased-dailydialog-turn-classifier | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | Entry not found | 15 |
boronbrown48/wangchanberta-topic-classification | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | Entry not found | 15 |
boychaboy/MNLI_bert-base-uncased_2 | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
cardiffnlp/bertweet-base-stance-abortion | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
pertschuk/albert-large-intent-v3 | null | Entry not found | 15 |
sagteam/pharm-relation-extraction | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7"
] | pharm-relation-extraction
===
Model trained to recognize 4 types of relationships between significant pharmacological entities in russian-language reviews: ADR–Drugname, Drugname–Diseasename, Drugname–SourceInfoDrug, Diseasename–Indication. The input of the model is a review text and a pair of entities, between which i... | 2,714 |
wrmurray/roberta-base-finetuned-imdb | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accura... | 1,625 |
tae898/emoberta-large | [
"anger",
"disgust",
"fear",
"joy",
"neutral",
"sadness",
"surprise"
] | ---
language: en
tags:
- emoberta
- roberta
license: mit
datasets:
- MELD
- IEMOCAP
---
Check https://github.com/tae898/erc for the details
[Watch a demo video!](https://youtu.be/qbr7fNd6J28)
# Emotion Recognition in Coversation (ERC)
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/... | 6,025 |
Intel/roberta-base-mrpc-int8-static | [
"0",
"1"
] | ---
language:
- en
license: mit
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingStatic
datasets:
- glue
metrics:
- f1
model-index:
- name: roberta-base-mrpc-int8-static
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
... | 1,414 |
Hate-speech-CNERG/urdu-abusive-MuRIL | null | ---
language: ur
license: afl-3.0
---
This model is used to detect **abusive speech** in **Urdu**. It is finetuned on MuRIL model using Urdu abusive speech dataset.
The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicAbusive)
LABEL_0 :-> Normal... | 955 |
HiTZ/A2T_RoBERTa_SMFA_ACE-arg | [
"contradiction",
"entailment",
"neutral"
] | ---
pipeline_tag: zero-shot-classification
datasets:
- snli
- anli
- multi_nli
- multi_nli_mismatch
- fever
---
# A2T Entailment model
**Important:** These pretrained entailment models are intended to be used with the [Ask2Transformers](https://github.com/osainz59/Ask2Transformers) library but are also fully compatib... | 3,612 |
Adapting/comfort_congratulations_neutral-classifier | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] |
# Adapting/comfort_congratulations_neutral-classifier
code used to train this model: https://colab.research.google.com/drive/1BHc8UMuT0sRyA_M24Acits5oHwUmjsFm?usp=sharing
dataset: https://huggingface.co/datasets/Adapting/empathetic_dialogues_v2
LABEL_0: neutral
LABEL_1: congratulating
LABEL_2: comforting | 311 |
dwing/distilbert-base-uncased-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: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... | 1,801 |
ArnavL/roberta-base-agnews-0 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | Entry not found | 15 |
aatmasidha/newsmodelclassification | [
"Sadness",
"Joy",
"Love",
"Anger",
"Fear",
"Surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: newsmodelclassification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
... | 1,768 |
zhernosek12/classif_sasha | [
"cmr",
"inoe",
"rgd",
"schet",
"schet-faktura",
"tovarnaya-nakladnaya"
] | Entry not found | 15 |
PGT/graphnystromformer-s-artificial-balanced-max500-490000-0 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6"
] | Entry not found | 15 |
CAMeL-Lab/bert-base-arabic-camelbert-ca-poetry | [
"البسيط",
"الخفيف",
"الدوبيت",
"الرجز",
"الرمل",
"السريع",
"السلسلة",
"الطويل",
"الكامل",
"المتدارك",
"المتقارب",
"المجتث",
"المديد",
"المضارع",
"المقتضب",
"المنسرح",
"المواليا",
"الهزج",
"الوافر",
"شعر التفعيلة",
"شعر حر",
"عامي",
"موشح"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-CA Poetry Classification Model
## Model description
**CAMeLBERT-CA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Class... | 3,380 |
Capreolus/electra-base-msmarco | null | # capreolus/electra-base-msmarco
## Model description
ELECTRA-Base model (`google/electra-base-discriminator`) fine-tuned on the MS MARCO passage classification task. It is intended to be used as a `ForSequenceClassification` model, but requires some modification since it contains a BERT classification head rather tha... | 935 |
Intel/bert-base-uncased-mnli-sparse-70-unstructured | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: en
---
# Sparse BERT base model fine tuned to MNLI (uncased)
Fine tuned sparse BERT base to MNLI (GLUE Benchmark) task from [bert-base-uncased-sparse-70-unstructured](https://huggingface.co/Intel/bert-base-uncased-sparse-70-unstructured).
<br><br>
Note: This model requires `transformers==2.10.0`
## Eva... | 759 |
adelevie/distilbert-gsa-eula-opp | null | Entry not found | 15 |
akdeniz27/bert-turkish-text-classification | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8"
] | ---
language: tr
---
# Turkish Text Classification for Complaints Data Set
This model is a fine-tune model of https://github.com/stefan-it/turkish-bert by using text classification data with 9 categories as follows:
id_to_category = {0: 'KONFORSUZLUK', 1: 'TARİFE İHLALİ', 2: 'DURAKTA DURMAMA', 3: 'ŞOFÖR-PERSONEL ŞİK... | 467 |
arianpasquali/distilbert-base-multilingual-cased-toxicity | [
"not_toxic",
"toxic"
] | Entry not found | 15 |
recobo/chemical-bert-uncased-pharmaceutical-chemical-classifier | null | ---
language: "en"
tags:
- buy-intent
- sell-intent
- consumer-intent
widget:
- text: "Flutoprazepam (Restas) is a drug which is a benzodiazepine. It was patented in Japan by Sumitomo."
---
# Chemical vs Pharmaceutical Domain Document Classifier
Chemical domain language model finetuned on 13K Chemical, and 14K Pharma W... | 1,130 |
ShihTing/HealthBureauSix | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
tags: autonlp
language: unk
widget:
- text: "民眾來電反映：事由：護士態度惡劣，對病人大吼大叫，對於態度惡劣的人卻於與錄用，敬請相關單位改善"
- text: "民眾來電：
時間:2016年3月24號至2019年10月26號
地點:三軍總醫院 北投分院
事由:民眾表揚上述地點及時間有些醫護人員很優秀、親切、具有專業服務水準、好相處(2病房的護理師陳怡鎮、歐素玲、陳芊糖，7病房蔡閔儒，12病房林哲玄、黃仙怡，主治醫師楊蕙年)
訴求:敬請相關單位給予表揚與肯定
"
- text: "本人之先生2-3年前接受吳醫師植牙治療，本人之先生已付完植牙醫療費用，但吳醫師尚未完成本人先生之植牙，診... | 547 |
spartan97/distilbert-base-uncased-finetuned-objectivity-rotten | [
"NEGATIVE",
"POSITIVE"
] | ---
license: gpl-3.0
---
Objectivity sentence classification model based on **distilbert-base-uncased-finetuned-sst-2-english**. It was fine-tuned with Rotten-IMDB movie review [data](http://www.cs.cornell.edu/people/pabo/movie-review-data/) using extracted sentences from film plots as objective examples and review co... | 652 |
tsdocode/phobert-finetune-hatespeech | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language:
- vi
tags:
- classification
widget:
- text: "Xấu vcl"
example_title: "Công kích"
- text: "Đồ ngu"
example_title: "Thù ghét"
- text: "Xin chào chúc một ngày tốt lành"
example_title: "Normal"
---
## [PhoBert](https://huggingface.co/vinai/phobert-base/tree/main) finetuned version for hate speech dete... | 1,242 |
waboucay/camembert-large-finetuned-xnli_fr_3_classes-finetuned-repnum_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 | 78.3 | 78.3 |
| test ... | 367 |
AI-Prize-Challenges/autotrain-finetuned1-1035435583 | [
"negative",
"positive"
] | ---
tags: autotrain
language: zh
widget:
- text: "I love AutoTrain 🤗"
datasets:
- AI-Prize-Challenges/autotrain-data-finetuned1
co2_eq_emissions: 0.03608660562919794
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1035435583
- CO2 Emissions (in grams): 0.03608660562919794
## Va... | 1,232 |
Eleven/distilbert-base-uncased-finetuned-emotion | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | 1,487 |
Jimchoo91/distilbert-base-uncased-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: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... | 1,797 |
IlyaGusev/xlm_roberta_large_headline_cause_simple | [
"not_cause",
"left_right",
"right_left"
] | ---
language:
- ru
- en
tags:
- xlm-roberta-large
datasets:
- IlyaGusev/headline_cause
license: apache-2.0
widget:
- text: "Песков опроверг свой перевод на удаленку</s>Дмитрий Песков перешел на удаленку"
---
# XLM-RoBERTa HeadlineCause Simple
## Model description
This model was trained to predict the presence of ca... | 3,163 |
Narsil/tiny-distilbert-sequence-classification | null | Entry not found | 15 |
boychaboy/MNLI_bert-base-uncased | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
boychaboy/MNLI_roberta-base | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
crazould/multimodal-emotion-recognition | [
"anger",
"disgust",
"fear",
"joy",
"neutral",
"sadness",
"surprise"
] | Entry not found | 15 |
erst/xlm-roberta-base-finetuned-db07 | [
"011100",
"011200",
"011300",
"011400",
"011500",
"011600",
"011900",
"012100",
"012200",
"012300",
"012400",
"012500",
"012600",
"012700",
"012800",
"012900",
"013000",
"014100",
"014200",
"014300",
"014400",
"014500",
"014610",
"014620",
"014700",
"014910",
"014... | # Classifying Text into DB07 Codes
This model is [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) fine-tuned to classify Danish descriptions of activities into [Dansk Branchekode DB07](https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/dansk-branchekode-db07) codes.
## Data
Approximately 2.5 mill... | 1,254 |
federicopascual/finetuning-sentiment-model-3000-samples-testcopy | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples-testcopy
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_tex... | 1,524 |
nickmuchi/distilroberta-finetuned-financial-text-classification | [
"bearish",
"neutral",
"bullish"
] | ---
license: apache-2.0
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
- sentence_50agree
- generated_from_trainer
- financial
- stocks
- sentiment
datasets:
- financial_phrasebank
- Kaggle Self label
- nickmuchi/financial-classification
metrics:
- f1
widget:
- text: "The USD rallied by 10% la... | 3,192 |
persiannlp/mbert-base-parsinlu-multiple-choice | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mbert
- persian
- farsi
pipeline_tag: text-classification
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوا... | 2,045 |
textattack/albert-base-v2-RTE | null | ## TextAttack Model Card
This `albert-base-v2` 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 64, a learning
rate of 3e-05, and a maximum sequence length of 128.
Since this was a classi... | 619 |
l3cube-pune/mahahate-multi-roberta | [
"Hate",
"Offensive",
"Profane",
"None"
] | ---
language: mr
tags:
license: cc-by-4.0
datasets:
- L3Cube-MahaHate
widget:
- text: "I like you. </s></s> I love you."
---
## MahaHate-multi-RoBERTa
MahaHate-multi-RoBERTa (Marathi Hate speech identification) is a MahaRoBERTa(l3cube-pune/marathi-roberta) model fine-tuned on L3Cube-MahaHate - a Marathi tweet-based... | 712 |
frasermince/longformer-fake-news | null | Entry not found | 15 |
AbhiNaiky/finetuning-sentiment-model-3000-samples | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... | 1,507 |
HiTZ/A2T_RoBERTa_SMFA_TACRED-re | [
"contradiction",
"entailment",
"neutral"
] | ---
pipeline_tag: zero-shot-classification
datasets:
- snli
- anli
- multi_nli
- multi_nli_mismatch
- fever
---
# A2T Entailment model
**Important:** These pretrained entailment models are intended to be used with the [Ask2Transformers](https://github.com/osainz59/Ask2Transformers) library but are also fully compatib... | 3,612 |
CEBaB/roberta-base.CEBaB.sa.2-class.exclusive.seed_42 | [
"0",
"1"
] | Entry not found | 15 |
emre/turkish-sentiment-analysis | [
"Negative",
"Notr",
"Positive"
] | ---
tags: autotrain
language: tr
widget:
- text: "Bu ürün gerçekten güzel çıktı"
datasets:
- emre/autotrain-data-turkish-sentiment-analysis
co2_eq_emissions: 120.82460124309924
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 870727732
- CO2 Emissions (in grams): 120.82460124... | 1,421 |
Mim/biobert-procell-demo | [
"accept",
"reject"
] | ---
tags: biobert
language: unk
widget:
- text: "Cell lines expressing proteins 🤗"
datasets:
- Mim/autotrain-data-biobert-procell
co2_eq_emissions: 0.5988414315305852
---
# Model Trained Using biobert
- Problem type: Binary Classification
- Model ID: 896229149
- CO2 Emissions (in grams): 0.5988414315305852
## Valid... | 1,220 |
Dafa/factcc | null | ---
license: afl-3.0
---
| 25 |
Xuan-Rui/pet-1000-iPT.p4PTmBERT | null | Entry not found | 15 |
asdc/roberta-base-biomedical-clinical-es-finetuned-text_classification | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6"
] | Entry not found | 15 |
waboucay/camembert-large-finetuned-xnli_fr_3_classes-finetuned-repnum_wl-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 | 75.4 | 75.4 |
| test ... | 367 |
Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469 | [
"I am not sure how X will interpret Y’s answer",
"In the middle, neither yes nor no",
"No",
"Other",
"Probably no",
"Probably yes / sometimes yes",
"Yes",
"Yes, subject to some conditions"
] | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Siddish/autotrain-data-yes-or-no-classifier-on-circa
co2_eq_emissions: 0.1287915253247826
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1009033469
- CO2 Emissions (in grams): 0.1287915253247... | 1,471 |
sam34738/xlm-roberta-hindi-nisha | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6"
] | ---
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-hindi-nisha
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. -->
# xlm-roberta-hindi-nisha
This m... | 1,357 |
matanbn/smsPhishing | null | Entry not found | 15 |
baykenney/bert-base-gpt2detector-topp96 | [
"Human",
"Machine"
] | Entry not found | 15 |
bella/bert_finetuning_test | null | Entry not found | 15 |
blackbird/alberta-base-mnli-v1 | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
boychaboy/MNLI_distilbert-base-cased_2 | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
classla/roberta-base-frenk-hate | null | ---
language: "en"
tags:
- text-classification
- hate-speech
widget:
- text: "Gay is okay."
---
# roberta-base-frenk-hate
Text classification model based on [`roberta-base`](https://huggingface.co/roberta-base) and fine-tuned on the [FRENK dataset](https://www.clarin.si/repository/xmlui/handle/11356/1433) compr... | 4,315 |
cross-encoder/msmarco-MiniLM-L12-en-de-v1 | [
"LABEL_0"
] | ---
license: apache-2.0
---
# Cross-Encoder for MS MARCO - EN-DE
This is a cross-lingual Cross-Encoder model for EN-DE that can be used for passage re-ranking. It was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: ... | 4,796 |
m3hrdadfi/albert-fa-base-v2-sentiment-multi | [
"Negative",
"Neutral",
"Positive"
] | ---
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... | 1,938 |
prajjwal1/albert-base-v1-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | If you use the model, please consider citing this 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},
... | 352 |
Miniproject/BERT | [
"1 star",
"2 stars",
"3 stars",
"4 stars",
"5 stars"
] | ---
language:
- en
---
# Bert-base-uncased-sentiment
BERT stands for Bidirectional Encoder Representations from Transformers. It is a recent paper published by researchers at Google AI Language. BERT makes use of Transformer, an attention mechanism that learns contextual relations between words (or sub-words) in a t... | 4,765 |
Bryan0123/bert-hashtag-to-hashtag | [
"#art",
"#beautiful",
"#fashion",
"#instagood",
"#instagram",
"#love",
"#nature",
"#photography",
"#photooftheday",
"#travel"
] | Entry not found | 15 |
Raychanan/Longformer_Conflict | null | training_args = TrainingArguments(
output_dir="./results",
learning_rate=5e-5,
per_device_train_batch_size=1,
per_device_eval_batch_size=1,
num_train_epochs=5,
weight_decay=0.01,
evaluation_strategy="epoch",
push_to_hub=True
) | 258 |
bomera/distilbert-base-uncased-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: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... | 1,807 |
Manishkalra/finetuning-movie-sentiment-model-9000-samples | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-movie-sentiment-model-9000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
... | 1,533 |
Xuan-Rui/pet-1000-iPT.p4PTptBERT | null | Entry not found | 15 |
sahn/distilbert-base-uncased-finetuned-imdb-blur | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-imdb-blur
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metr... | 1,935 |
cardiffnlp/tweet-topic-19-single | [
"arts_&_culture",
"business_&_entrepreneurs",
"daily_life",
"pop_culture",
"science_&_technology",
"sports_&_gaming"
] | # tweet-topic-19-single
This is a roBERTa-base model trained on ~90m tweets until the end of 2019 (see [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m)), and finetuned for single-label topic classification on a corpus of 6,997 tweets.
The original roBERTa-base model can be found [here](https://... | 2,122 |
edmundhui/mental_health_trainer | [
"ADHD",
"OCD",
"aspergers",
"depression",
"ptsd"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: mental_health_trainer
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. -->
# mental_health... | 1,121 |
semy/finetuning-tweeteval-hate-speech | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-tweeteval-hate-speech
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 remov... | 1,188 |
anneke/finetuning-distilbert-base-uncased-5000-samples | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-distilbert-base-uncased-5000-samples
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | 1,231 |
CAMeL-Lab/bert-base-arabic-camelbert-mix-poetry | [
"البسيط",
"الخفيف",
"الدوبيت",
"الرجز",
"الرمل",
"السريع",
"السلسلة",
"الطويل",
"الكامل",
"المتدارك",
"المتقارب",
"المجتث",
"المديد",
"المضارع",
"المقتضب",
"المنسرح",
"المواليا",
"الهزج",
"الوافر",
"شعر التفعيلة",
"شعر حر",
"عامي",
"موشح"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-Mix Poetry Classification Model
## Model description
**CAMeLBERT-Mix Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Mix... | 3,368 |
Jorgeutd/bert-base-uncased-ade-Ade-corpus-v2 | null | ---
language: en
widget:
- text: "I got a rash from taking acetaminophen"
tags:
- sagemaker
- bert-base-uncased
- text classification
license: apache-2.0
datasets:
- adecorpusv2
model-index:
- name: BERT-ade_corpus
results:
- task:
name: Text Classification
type: text-classification
dataset:
... | 1,618 |
JovenPai/bert_finetunning_test | [
"LABEL_0",
"LABEL_1"
] | Entry not found | 15 |
Maha/hi-const21-hibert_final | null | Entry not found | 15 |
PubChimps/dlfBERT | null | Entry not found | 15 |
TehranNLP/bert-base-cased-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
airKlizz/gbert-base-germeval21-toxic-with-data-augmentation | null | Entry not found | 15 |
microsoft/tapex-large-finetuned-tabfact | [
"LABEL_0",
"LABEL_1"
] | ---
language: en
tags:
- tapex
- table-question-answering
datasets:
- tab_fact
license: mit
---
# TAPEX (large-sized model)
TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, J... | 2,576 |
palakagl/bert_MultiClass_TextClassification | [
"alarm_query",
"alarm_remove",
"alarm_set",
"audio_volume_down",
"audio_volume_mute",
"audio_volume_up",
"calendar_query",
"calendar_remove",
"calendar_set",
"cooking_recipe",
"datetime_convert",
"datetime_query",
"email_addcontact",
"email_query",
"email_querycontact",
"email_sendemai... | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- palakagl/autotrain-data-PersonalAssitant
co2_eq_emissions: 5.080390550458655
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 717221775
- CO2 Emissions (in grams): 5.080390550458655
## Validat... | 1,418 |
okho0653/Bio_ClinicalBERT-zero-shot-sentiment-model | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: Bio_ClinicalBERT-zero-shot-sentiment-model
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. -->
#... | 1,076 |
CEBaB/roberta-base.CEBaB.sa.5-class.exclusive.seed_42 | [
"0",
"1",
"2",
"3",
"4"
] | Entry not found | 15 |
CEBaB/roberta-base.CEBaB.sa.5-class.exclusive.seed_66 | [
"0",
"1",
"2",
"3",
"4"
] | Entry not found | 15 |
CEBaB/roberta-base.CEBaB.sa.5-class.exclusive.seed_88 | [
"0",
"1",
"2",
"3",
"4"
] | Entry not found | 15 |
CEBaB/roberta-base.CEBaB.sa.5-class.exclusive.seed_99 | [
"0",
"1",
"2",
"3",
"4"
] | Entry not found | 15 |
ziq/depression_tweet | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: depression_tweet
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. -->
# depre... | 1,547 |
jboomc/rotten_tomatoes_finetuned | [
"neg",
"pos"
] | Entry not found | 15 |
RomanCast/no_init_miam_loria_finetuned | [
"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",... | ---
language:
- fr
--- | 22 |
ArneD/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... | 1,805 |
Anonymous1111/bert-base-emotion | [
"anger",
"fear",
"joy",
"love",
"sadness",
"surprise"
] | ---
license: apache-2.0
---
| 28 |
Elron/bleurt-base-128 | [
"LABEL_0"
] | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | 999 |
bipin/malayalam-news-classifier | [
"business",
"entertainment",
"sports"
] | ---
license: mit
tags:
- text-classification
- roberta
- malayalam
- pytorch
widget:
- text: "2032 ഒളിമ്പിക്സിന് ബ്രിസ്ബെയ്ന് വേദിയാകും; ഗെയിംസിന് വേദിയാകുന്ന മൂന്നാമത്തെ ഓസ്ട്രേലിയന് നഗരം"
---
## Malayalam news classifier
### Overview
This model is trained on top of [MalayalamBert](https://huggingface.co/... | 1,096 |
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