modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
projecte-aina/roberta-base-ca-cased-te | [
"ENTAILMENT",
"NEUTRAL",
"CONTRADICTION"
] | ---
language:
- ca
license: apache-2.0
tags:
- "catalan"
- "textual entailment"
- "teca"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "projecte-aina/teca"
metrics:
- "accuracy"
model-index:
- name: roberta-base-ca-cased-te
results:
- task:
type: text-classification # Required. Example:... | 2,716 |
qingtan007/bert_finetuning_test | [
"LABEL_0",
"LABEL_1"
] | Entry not found | 15 |
quarter100/BoolQ_dain_test | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
quarter100/ko-boolq-model | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | labeled by "YES" : 1, "NO" : 0, "No Answer" : 2
fine tuned by klue/roberta-large | 80 |
researchaccount/sa_sub2 | [
"Negative",
"Neutral",
"Positive"
] | ---
language: en
widget:
- text: "USER USER USER USER لاحول ولاقوه الا بالله 💔 💔 💔 💔 HASH TAG متي يصدر قرار العشرين ! ! ! ! ! !"
---
Sub 2 | 142 |
rexxar96/autonlp-sentiment-analysis-456211724 | [
"0",
"1"
] | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- rexxar96/autonlp-data-sentiment-analysis
co2_eq_emissions: 22.28263989637389
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 456211724
- CO2 Emissions (in grams): 22.28263989637389
## Validation Metric... | 1,194 |
rg089/bert_newspaper_source | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | Entry not found | 15 |
riyadhctg/distilbert-base-uncased-finetuned-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model_index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | 1,997 |
rockmiin/ko-boolq-model | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | labeled by "YES" : 1, "NO" : 0, "No Answer" : 2
fine tuned by klue/roberta-large | 80 |
saattrupdan/verdict-classifier-en | [
"factual",
"misinformation",
"other"
] | ---
license: mit
language: en
tags:
- generated_from_trainer
model-index:
- name: verdict-classifier-en
results:
- task:
type: text-classification
name: Verdict Classification
widget:
- "Even though it might look true, it has been taken out of context."
---
# English Verdict Classifier
This model is a ... | 13,095 |
sciarrilli/distilbert-base-uncased-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
... | 2,351 |
sgugger/test-upload1 | null | Entry not found | 15 |
shokiokita/distilbert-base-uncased-finetuned-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | 1,999 |
shokiokita/distilbert-base-uncased-finetuned-mrpc | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
... | 2,010 |
simonmun/Ey_SentenceClassification | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7"
] | Entry not found | 15 |
sismetanin/rubert-ru-sentiment-rureviews | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## RuBERT-ru-sentiment-RuReviews
RuBERT-ru-sentiment-RuReviews is a [RuBERT](https://huggingface.co/DeepPavlov/rubert-base-cased) model fine-tuned on [RuReviews dataset](https://github.com/sismetanin/rureviews) of Russian-language reviews from the ”Women’s ... | 6,340 |
sismetanin/rubert_conversational-ru-sentiment-rusentiment | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## RuBERT-Conversational-ru-sentiment-RuSentiment
RuBERT-Conversational-ru-sentiment-RuSentiment is a [RuBERT-Conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model fine-tuned on [RuSentiment dataset](https://github.com/te... | 6,388 |
sismetanin/sbert-ru-sentiment-liniscrowd | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
sismetanin/sbert-ru-sentiment-sentirueval2016 | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
sismetanin/xlm_roberta_large-ru-sentiment-sentirueval2016 | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
socialmediaie/TRAC2020_ALL_A_bert-base-multilingual-uncased | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | 5,074 |
socialmediaie/TRAC2020_ALL_C_bert-base-multilingual-uncased | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying
Our approach is described in our paper titled:
> Mishra, Sudhanshu, Shivangi Prasa... | 4,658 |
socialmediaie/TRAC2020_HIN_B_bert-base-multilingual-uncased | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | 5,074 |
socialmediaie/TRAC2020_HIN_C_bert-base-multilingual-uncased | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | 5,074 |
soham950/timelines_classifier | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
tals/albert-base-mnli | [
"NOT ENOUGH INFO",
"REFUTES",
"SUPPORTS"
] | ---
language: python
datasets:
- fever
- glue
- multi_nli
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When ... | 2,369 |
tanay/xlm-fine-tuned | null | Entry not found | 15 |
taoroalin/classifier_12aug_50k_labels | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
textattack/distilbert-base-uncased-QQP | null | Entry not found | 15 |
unicamp-dl/mMiniLM-L6-v2-en-msmarco | [
"LABEL_0"
] | ---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- en
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mMiniLM-L6 Reranker finetuned on English MS MARCO
## Introduction
mMiniLM-L6-v2-en-msmarco is a multilingual miniLM-based model fine-tuned on Eng... | 1,292 |
unicamp-dl/mMiniLM-L6-v2-pt-msmarco-v1 | [
"LABEL_0"
] | ---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mMiniLM-L6-v2 Reranker finetuned on mMARCO
## Introduction
mMiniLM-L6-v2-pt-msmarco-v1 is a multilingual miniLM-based model finetuned on a... | 1,445 |
usami/distilbert-base-uncased-finetuned-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | 1,999 |
valurank/distilroberta-mbfc-bias | [
"extremeright",
"leastbiased",
"left",
"leftcenter",
"right",
"rightcenter",
"unknown"
] | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-mbfc-bias
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. -->
# distilroberta-mb... | 2,836 |
verloop/Hinglish-DistilBert-Class | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
vesteinn/XLMR-ENIS-finetuned-cola | null | ---
license: agpl-3.0
tags:
- generated_from_trainer
datasets:
- glue
language:
- en
- is
metrics:
- matthews_correlation
model-index:
- name: XLMR-ENIS-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
... | 1,980 |
victor/autonlp-imdb-reviews-sentiment-329982 | [
"negative",
"positive"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- victor/autonlp-data-imdb-reviews-sentiment
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 329982
## Validation Metrics
- Loss: 0.24620144069194794
- Accuracy: 0.9300053431035799
- Precision: 0.9299029... | 1,108 |
vionwinnie/albert-goodnotes-reddit | [
"Question - Mac",
"Question - Other",
"Question - iPad",
"Review",
"Stylus problems",
"Templates"
] | Entry not found | 15 |
vittoriomaggio/bert-base-msmarco-fiqa-transfer | null | Entry not found | 15 |
vovaf709/bert_classifier | null | Entry not found | 15 |
w11wo/sundanese-gpt2-base-emotion-classifier | [
"anger",
"fear",
"joy",
"sadness"
] | ---
language: su
tags:
- sundanese-gpt2-base-emotion-classifier
license: mit
widget:
- text: "Wah, éta gélo, keren pisan!"
---
## Sundanese GPT-2 Base Emotion Classifier
Sundanese GPT-2 Base Emotion Classifier is an emotion-text-classification model based on the [OpenAI GPT-2](https://cdn.openai.com/better-langua... | 4,430 |
wgpubs/session-4-imdb-model | [
"NEGATIVE",
"POSITIVE"
] | Entry not found | 15 |
xysmalobia/test-trainer | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: test-trainer
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
- name: Accuracy
... | 1,809 |
yacov/yacov-athena-DistilBertSC | null | hello
| 6 |
ybybybybybybyb/autonlp-revanalysis-6711455 | [
"긍정",
"부정",
"중립"
] | ---
tags: autonlp
language: ko
widget:
- text: "I love AutoNLP 🤗"
datasets:
- ybybybybybybyb/autonlp-data-revanalysis
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 6711455
## Validation Metrics
- Loss: 0.8241586089134216
- Accuracy: 0.7835820895522388
- Macro F1: 0.529738... | 1,314 |
yoshitomo-matsubara/bert-base-uncased-rte_from_bert-large-uncased-rte | null | ---
language: en
tags:
- bert
- rte
- glue
- kd
- torchdistill
license: apache-2.0
datasets:
- rte
metrics:
- accuracy
---
`bert-base-uncased` fine-tuned on RTE dataset, using fine-tuned `bert-large-uncased` as a teacher model, [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab... | 824 |
yoshitomo-matsubara/bert-base-uncased-sst2_from_bert-large-uncased-sst2 | null | ---
language: en
tags:
- bert
- sst2
- glue
- kd
- torchdistill
license: apache-2.0
datasets:
- sst2
metrics:
- accuracy
---
`bert-base-uncased` fine-tuned on SST-2 dataset, using fine-tuned `bert-large-uncased` as a teacher model, [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google C... | 829 |
zhc/distilbert-base-uncased-finetuned-mrpc-test | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
... | 1,726 |
zhuqing/roberta-base-uncased-netmums-classification-intersection | null | Entry not found | 15 |
ziqingyang/XLMRobertaBaseForPAWSX-en | null | Entry not found | 15 |
zyl1024/bert-base-cased-finetuned-qqp | [
"duplicate",
"not_duplicate"
] | Entry not found | 15 |
inovex/multi2convai-corona-it-bert | [
"corona.traffic",
"corona.supplies",
"corona.quarantine",
"corona.masks",
"corona.illness",
"corona.package",
"corona.vaccine",
"corona.rumors",
"corona.risk",
"corona.course",
"corona.symptoms",
"corona.patients",
"corona.deathRate",
"corona.infect",
"corona.protect",
"corona.definiti... | ---
tags:
- text-classification
widget:
- text: "Devo indossare una maschera?"
license: mit
language: it
---
# Multi2ConvAI-Corona: finetuned Bert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://m... | 978 |
inovex/multi2convai-quality-de-mbert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Starte das Programm"
license: mit
language: de
---
# Multi2ConvAI-Quality: finetuned MBert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2co... | 969 |
sancharidan/scibert_expfinder_SCIS | null | Entry not found | 15 |
mp6kv/feedback_intent_test | [
"negative_feedback",
"neutral_feedback",
"positive_feedback"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: feedback_intent_test
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. -->
# feedback_intent_test
... | 1,611 |
nepp1d0/smiles-target-interaction | null | Entry not found | 15 |
khavitidala/xlmroberta-large-fine-tuned-indo-hoax-classification | [
"Fakta",
"Hoaks"
] | ---
tags:
- exbert
language: multilingual
inference: true
license: mit
---
# Fine-tuned version of XLM-RoBERTa (large-sized model)
fine tune by Ryan Abdurohman
# XLM-RoBERTa (large-sized model)
XLM-RoBERTa model pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the pap... | 4,876 |
joniponi/multilabel_inpatient_comments | [
"admin",
"bathroom",
"bill",
"cc",
"clean",
"communication",
"condition",
"covid",
"depts",
"doctor",
"family",
"food",
"health",
"nice",
"nurse",
"rude",
"staff",
"stay",
"treatment"
] | Entry not found | 15 |
ningkko/drug-stance-bert | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
tags:
- generated_from_trainer
model-index:
- name: drug-stance-bert
results: [1, 0, 2]
---
<!-- 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. -->
# drug-stance-bert
This model is... | 3,981 |
msamogh/autonlp-cai-out-of-scope-649919118 | [
"0",
"1"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- msamogh/autonlp-data-cai-out-of-scope
co2_eq_emissions: 0.3996916853309825
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 649919118
- CO2 Emissions (in grams): 0.3996916853309825
## Validation Metrics
... | 1,174 |
mnavas/roberta-finetuned-CPV_Spanish | [
"03",
"09",
"14",
"15",
"16",
"18",
"19",
"22",
"24",
"30",
"31",
"32",
"33",
"34",
"35",
"37",
"38",
"39",
"41",
"42",
"43",
"44",
"45",
"48",
"50",
"51",
"55",
"60",
"63",
"64",
"65",
"66",
"70",
"71",
"72",
"73",
"75",
"76",
"77",
"79"... | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-CPV_Spanish
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 t... | 17,445 |
yy642/bert-base-uncased-finetuned-mnli-max-length-32-epoch-1 | null | Entry not found | 15 |
yy642/bert-base-uncased-finetuned-mnli-max-length-256-epoch-6 | null | Entry not found | 15 |
istassiy/ysda_2022_ml2_hw3_distilbert_base_uncased | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7"
] | Entry not found | 15 |
hackathon-pln-es/readability-es-3class-sentences | [
"advanced",
"basic",
"intermediate"
] | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- bertin
pipeline_tag: text-classification
widget:
- text: Las Líneas de Nazca son una serie de marcas trazadas en el suelo, cuya anchura oscila entre los 40 y los 110 centímetros.
- text: Hace mucho tiempo, en el gran océano que baña las costas del Perú no ... | 3,207 |
sadia-afrin-purba/fake-news-classifier | null | ---
license: mit
---
| 24 |
gdwangh/distilbert-base-uncased-finetuned-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | 1,999 |
vicl/canine-c-finetuned-mrpc | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: canine-c-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
- name: Accu... | 1,964 |
unjustify/autotrain-commonsense_1-696121179 | [
"0",
"1"
] | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- unjustify/autotrain-data-commonsense_1
co2_eq_emissions: 4.355285184457145
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 696121179
- CO2 Emissions (in grams): 4.355285184457145
## Validation Met... | 1,196 |
vicl/distilbert-base-uncased-finetuned-cola | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | 1,999 |
reichenbach/fake-news-detector-v2 | null | Entry not found | 15 |
nkn002/longformer_fakenews_cls | null | Entry not found | 15 |
jason9693/klue-roberta-small-apeach | [
"Default",
"Spoiled"
] | ---
language: ko
widget:
- text: "응 어쩔티비~~"
datasets:
- jason9693/APEACH
--- | 76 |
jason9693/kcelectra-v2022-dev-apeach | [
"Default",
"Spoiled"
] | ---
language: ko
widget:
- text: "코딩을 🐶🍾👟같이 하니까 맨날 장애나잖아 이 🧑🦽아"
datasets:
- jason9693/APEACH
--- | 97 |
supriyaraj47/roberta-base-nli | null | Entry not found | 15 |
waboucay/camembert-base-finetuned-nli-repnum_wl-rua_wl | [
"contradiction",
"non-contradiction"
] | ---
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 | 73.5 | 73.5 |
| test ... | 367 |
waboucay/camembert-base-finetuned-nli-xnli_fr-repnum_wl-rua_wl | [
"contradiction",
"non-contradiction"
] | ---
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 | 83.1 | 82.2 |
| test ... | 367 |
tuhailong/cross_encoder_roberta-wwm-ext-large | [
"LABEL_0"
] | ---
language: zh
tags:
- cross-encoder
datasets:
- dialogue
---
# Data
train data is similarity sentence data from E-commerce dialogue, about 50w sentence pairs.
## Model
model created by [sentence-tansformers](https://www.sbert.net/index.html)，model struct is cross-encoder，pretrained model is hfl/chinese-roberta-wwm... | 655 |
intellisr/autotrain-twitterMbti-758223271 | [
"0",
"1",
"10",
"11",
"12",
"13",
"14",
"15",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"9"
] | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- intellisr/autotrain-data-twitterMbti
co2_eq_emissions: 0.3313142450338848
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 758223271
- CO2 Emissions (in grams): 0.3313142450338848
## Validatio... | 1,404 |
hanxiong/distilbert-base-uncased-finetuned-cola | null | Entry not found | 15 |
mwong/roberta-base-climate-evidence-related | null | ---
language: en
license: mit
tags:
- text classification
- fact checking
datasets:
- mwong/fever-evidence-related
- mwong/climate-evidence-related
widget:
- text: "Earth’s changing climate is a critical issue and poses the risk of significant environmental, social and economic disruptions around the globe.</s></s>Beca... | 1,175 |
masapasa/deberta_amazon_reviews_v1 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: deberta_amazon_reviews_v1
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. -->
# deberta_amazon_r... | 1,061 |
satish860/sms_spam_detection-manning | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: sms_spam_detection-manning
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... | 1,194 |
juancavallotti/bert-base-culinary | [
"contradiction",
"entailment"
] | Entry not found | 15 |
manueltonneau/bert-twitter-es-job-offer | null | ---
language: es # <-- my language
widget:
- text: "Difunde a contactos: #trabajo: Cajeros Zona Taxqueña- Turnos fijos. Oaxaca"
---
# Detection of employment status disclosures on Twitter
## Model main characteristics:
- class: Job Offer (1), else (0)
- country: MX
- language: Spanish
- architecture: BERT b... | 1,081 |
shahidul034/sentence_equivalent_check | [
"equivalent",
"not_equivalent"
] | This model helps to identify the equivalent of two sentences.
==>python 3.8 working in transformers installation
-->pip install git+https://github.com/huggingface/transformers
-->python -m pip install jupyter
-->pip install torch==1.5.0 -f https://download.pytorch.org/whl/torch_stable.html
-->pip install tensorflow-gp... | 2,942 |
shoubhik/electra_abbv | [
"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... | Entry not found | 15 |
mrm8488/data2vec-text-base-finetuned-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: data2vec-text-base-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mnli
metrics:
- name: Accura... | 1,872 |
victoriapl01/sensitive_spanish_classifier | null | Entry not found | 15 |
mrm8488/data2vec-text-base-finetuned-cola | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: data2vec-text-base-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- ... | 1,932 |
mrm8488/data2vec-text-base-finetuned-rte | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: data2vec-text-base-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: rte
metrics:
- name: Accuracy... | 1,855 |
nikhilmatta/NewsBiasClassifier | null | Entry not found | 15 |
princeton-nlp/CoFi-CoLA-s95 | [
"0",
"1"
] | This is a model checkpoint for "[Structured Pruning Learns Compact and Accurate Models](https://arxiv.org/pdf/2204.00408.pdf)". The model is pruned from `bert-base-uncased` to a 95% sparsity on dataset CoLA. Please go to [our repository](https://github.com/princeton-nlp/CoFiPruning) for more details on how to use the m... | 434 |
mrm8488/electricidad-small-finetuned-politices-binary | null | Entry not found | 15 |
reallycarlaost/finetuning-tut-model | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | Entry not found | 15 |
jkhan447/language-detection-RoBert-base | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: language-detection-RoBert-base
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... | 1,150 |
jtang9001/skynet_gpt2_2 | [
"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 |
peter2000/xlm-roberta-base-finetuned-osdg | [
"sdg_1",
"sdg_10",
"sdg_11",
"sdg_12",
"sdg_13",
"sdg_14",
"sdg_15",
"sdg_2",
"sdg_3",
"sdg_4",
"sdg_5",
"sdg_6",
"sdg_7",
"sdg_8",
"sdg_9"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-osdg
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-robert... | 1,855 |
mmillet/rubert-tiny2_finetuned_emotion_experiment_modified_CE_LOSS_resampling | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: rubert-tiny2_finetuned_emotion_experiment_modified_CE_LOSS_resampling
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofre... | 2,410 |
someoneorlov/rubert_contact | null | ---
license: apache-2.0
---
| 28 |
z-dickson/CAP_coded_UK_statutory_instruments | [
"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"
] | ---
tags:
- generated_from_keras_callback
model-index:
- name: CAP_coded_UK_statutory_instruments
results: []
widget:
- text: "The National Health Service (Charges for Drugs and Appliances) (Scotland) Regulations 2007"
example_title: "example 1"
- text: "The Inshore Fishing (Prohibited Methods of Fishing) (Luce ... | 1,884 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.