index int64 0 22.3k | modelId stringlengths 8 111 | label list | readme stringlengths 0 385k |
|---|---|---|---|
315 | 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... |
316 | MoritzLaurer/mDeBERTa-v3-base-mnli-xnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- multilingual
- en
- ar
- bg
- de
- el
- es
- fr
- hi
- ru
- sw
- th
- tr
- ur
- vi
- zh
license: mit
tags:
- zero-shot-classification
- text-classification
- nli
- pytorch
metrics:
- accuracy
datasets:
- multi_nli
- xnli
pipeline_tag: zero-shot-classification
widget:
- text: "Angela Merke... |
317 | MoritzLaurer/policy-distilbert-7d | [
"external relations",
"freedom and democracy",
"political system",
"economy",
"welfare and quality of life",
"fabric of society",
"social groups"
] | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy (balanced)
- F1 (weighted)
widget:
- text: "70-85% of the population needs to get vaccinated against the novel coronavirus to achieve herd immunity."
---
# Policy-DistilBERT-7d
## Model description
This model was trained on 129.669 manually annota... |
318 | 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... |
319 | Motahar/distilbert-sst2-mahtab | [
"NEGATIVE",
"POSITIVE"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: distilbert-sst2-mahtab
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. --... |
320 | Mulin/my_wolf_model | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | My First Model
- for classification of wolf |
321 | Mustang/BERT_responsible_AI | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: eupl-1.1
---
## BERT model van het project Explainable AI |
322 | NDugar/1epochv3 | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the B... |
323 | NDugar/2epochv3mlni | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the B... |
324 | NDugar/3epoch-3large | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the B... |
325 | NDugar/ZSD-microsoft-v2xxlmnli | [
"CONTRADICTION",
"NEUTRAL",
"ENTAILMENT"
] | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBERT... |
326 | NDugar/deberta-v2-xlarge-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
I tried to train v3 xl to mnli using my own training code and got this result. |
327 | NDugar/debertav3-mnli-snli-anli | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-mnli
- deberta
- deberta-v2
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT a... |
328 | NDugar/v2xl-again-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBERT... |
329 | NDugar/v3-Large-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the GLUE MNLI... |
330 | NDugar/v3large-1epoch | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the B... |
331 | NDugar/v3large-2epoch | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
tags:
- deberta-v3
- deberta-v2`
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the B... |
332 | NTUYG/DeepSCC-RoBERTa | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | ## How to use
```python
from simpletransformers.classification import ClassificationModel, ClassificationArgs
name_file = ['bash', 'c', 'c#', 'c++','css', 'haskell', 'java', 'javascript', 'lua', 'objective-c', 'perl', 'php', 'python','r','ruby', 'scala', 'sql', 'swift', 'vb.net']
deep_scc_model_args = Classification... |
335 | NYTK/sentiment-hts5-hubert-hungarian | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
language:
- hu
tags:
- text-classification
license: apache-2.0
metrics:
- accuracy
widget:
- text: Jó reggelt! majd küldöm az élményhozókat :).
---
# Hungarian Sentence-level Sentiment Analysis with Finetuned huBERT Model
For further models, scripts and details, see [our repository](https://github.com/nytud/senti... |
336 | NYTK/sentiment-hts5-xlm-roberta-hungarian | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
language:
- hu
tags:
- text-classification
license: mit
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-analysi... |
338 | 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... |
339 | Narrativaai/deberta-v3-small-finetuned-hate_speech18 | [
"NO_HATE",
"HATE",
"IDK",
"RELATION"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- hate_speech18
widget:
- text: "ok, so do we need to kill them too or are the slavs okay ? for some reason whenever i hear the word slav , the word slobber comes to mind and i picture a slobbering half breed creature like the humpback of notre dame or Igor haha... |
340 | Narrativaai/fake-news-detection-spanish | [
"REAL",
"FAKE"
] | ---
language: es
tags:
- generated_from_trainer
- fake
- news
- competition
datasets:
- fakedes
widget:
- text: 'La palabra "haiga", aceptada por la RAE [SEP] La palabra "haiga", aceptada por la RAE La Real Academia de la Lengua (RAE), ha aceptado el uso de "HAIGA", para su utilización en las tres personas del singul... |
341 | Narsil/deberta-large-mnli-zero-cls | [
"CONTRADICTION",
"NEUTRAL",
"ENTAILMENT"
] | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBE... |
342 | NathanZhu/GabHateCorpusTrained | [
"LABEL_0",
"LABEL_1"
] | Test for use in Google Colab :'( |
343 | NbAiLab/nb-bert-base-mnli | [
"contradiction",
"neutral",
"entailment"
] | ---
language: no
license: cc-by-4.0
thumbnail: https://raw.githubusercontent.com/NBAiLab/notram/master/images/nblogo_2.png
pipeline_tag: zero-shot-classification
tags:
- nb-bert
- zero-shot-classification
- pytorch
- tensorflow
- norwegian
- bert
datasets:
- mnli
- multi_nli
- xnli
widget:
- example_title: Nyhetsartikk... |
346 | NikolajMunch/danish-emotion-classification | [
"Afsky",
"Frygt",
"Glæde",
"Overraskelse",
"Tristhed",
"Vrede"
] | ---
widget:
- text: "Hold da op! Kan det virkelig passe?"
language:
- "da"
tags:
- sentiment
- emotion
- danish
---
# **-- EMODa --**
## BERT-model for danish multi-class classification of emotions
Classifies a danish sentence into one of 6 different emotions:
| Danish emotion | Ekman's emotion |
| -... |
347 | Noxel/sentiments_multilenguaje | [
"1 star",
"2 stars",
"3 stars",
"4 stars",
"5 stars"
] | ---
language:
- en
- nl
- de
- fr
- it
- es
license: mit
---
# bert-base-multilingual-uncased-sentiment
This a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish and Italian. It predicts the sentiment of the review as a n... |
348 | Omar95farag/distilbert-base-uncased-distilled-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-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... |
355 | Pratibha/xlm-roberta-base-finetuned-marc-en | [
"good",
"great",
"ok",
"poor",
"terrible"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
model-index:
- name: xlm-roberta-base-finetuned-marc-en
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 re... |
357 | 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... |
358 | Prompsit/paraphrase-bert-pt | [
"Not Paraphrase",
"Paraphrase"
] | ---
pipeline_tag: text-classification
inference: false
language: pt
tags:
- transformers
---
# Prompsit/paraphrase-bert-pt
This model allows to evaluate paraphrases for a given phrase.
We have fine-tuned this model from pretrained "neuralmind/bert-base-portuguese-cased".
Model built under a TSI-100905-2019-4 pr... |
359 | Prompsit/paraphrase-roberta-es | [
"Not Paraphrase",
"Paraphrase"
] | ---
pipeline_tag: text-classification
inference: false
language: es
tags:
- transformers
---
# Prompsit/paraphrase-roberta-es
This model allows to evaluate paraphrases for a given phrase.
We have fine-tuned this model from pretrained "PlanTL-GOB-ES/roberta-base-bne".
Model built under a TSI-100905-2019-4 projec... |
360 | ProsusAI/finbert | [
"positive",
"negative",
"neutral"
] | ---
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
widget:
- text: "Stocks rallied and the British pound gained."
---
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financi... |
361 | Qinghui/autonlp-fake-covid-news-36769078 | [
"0",
"1"
] | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Qinghui/autonlp-data-fake-covid-news
co2_eq_emissions: 23.42719853096565
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 36769078
- CO2 Emissions (in grams): 23.42719853096565
## Validation Metrics
- ... |
363 | Recognai/bert-base-spanish-wwm-cased-xnli | [
"contradiction",
"neutral",
"entailment"
] | ---
language: es
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
license: mit
pipeline_tag: zero-shot-classification
widget:
- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
candidate_labels: "cultura, sociedad, economia, salud, deportes"
---
# bert-bas... |
364 | Recognai/zeroshot_selectra_medium | [
"contradiction",
"neutral",
"entailment"
] | ---
language: es
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
pipeline_tag: zero-shot-classification
license: apache-2.0
widget:
- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
candidate_labels: "cultura, sociedad, economia, salud, deportes"
---
# Z... |
365 | Recognai/zeroshot_selectra_small | [
"contradiction",
"neutral",
"entailment"
] | ---
language: es
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
pipeline_tag: zero-shot-classification
license: apache-2.0
widget:
- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
candidate_labels: "cultura, sociedad, economia, salud, deportes"
---
# Ze... |
366 | RecordedFuture/Swedish-Sentiment-Fear | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: sv
license: mit
---
## Swedish BERT models for sentiment analysis
[Recorded Future](https://www.recordedfuture.com/) together with [AI Sweden](https://www.ai.se/en) releases two language models for sentiment analysis in Swedish. The two models are based on the [KB\/bert-base-swedish-cased](https://huggi... |
367 | RecordedFuture/Swedish-Sentiment-Violence | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: sv
license: mit
---
## Swedish BERT models for sentiment analysis
[Recorded Future](https://www.recordedfuture.com/) together with [AI Sweden](https://www.ai.se/en) releases two language models for sentiment analysis in Swedish. The two models are based on the [KB\/bert-base-swedish-cased](https://huggi... |
368 | Rexhaif/rubert-base-srl | [
"инструмент",
"каузатор",
"экспериенцер"
] | ---
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: rubert-base-srl
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. -->
# rubert-base-srl
This mod... |
369 | Riad/finetuned-bert-mrpc | [
"equivalent",
"not equivalent"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: finetuned-bert-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
- name: Accuracy... |
370 | Roberta55/deberta-base-mnli-finetuned-cola | [
"CONTRADICTION",
"ENTAILMENT",
"NEUTRAL"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: deberta-base-mnli-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- n... |
371 | Rocketknight1/distilbert-base-uncased-finetuned-cola | [
"Invalid",
"Valid"
] | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Rocketknight1/distilbert-base-uncased-finetuned-cola
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove th... |
375 | SEISHIN/distilbert-base-uncased-finetuned-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mnli
metrics:
- ... |
378 | Sahajtomar/German_Zeroshot | [
"entailment",
"neutral",
"contradiction"
] | ---
language: multilingual
tags:
- text-classification
- pytorch
- nli
- xnli
- de
datasets:
- xnli
pipeline_tag: zero-shot-classification
widget:
- text: "Letzte Woche gab es einen Selbstmord in einer nahe gelegenen kolonie"
candidate_labels: "Verbrechen,Tragödie,Stehlen"
hypothesis_template: "In deisem geht es u... |
382 | Sarim24/Sarim24 | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | |
383 | SetFit/MiniLM-L12-H384-uncased__sst2__all-train | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MiniLM-L12-H384-uncased__sst2__all-train
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 th... |
384 | SetFit/deberta-v3-base__sst2__all-train | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base__sst2__all-train
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 comme... |
385 | SetFit/deberta-v3-large__sst2__train-16-0 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-0
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 com... |
386 | SetFit/deberta-v3-large__sst2__train-16-1 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-1
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 com... |
387 | SetFit/deberta-v3-large__sst2__train-16-2 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-2
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 com... |
388 | SetFit/deberta-v3-large__sst2__train-16-3 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-3
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 com... |
389 | SetFit/deberta-v3-large__sst2__train-16-4 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-4
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 com... |
390 | SetFit/deberta-v3-large__sst2__train-16-5 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-5
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 com... |
391 | SetFit/deberta-v3-large__sst2__train-16-6 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-6
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 com... |
392 | SetFit/deberta-v3-large__sst2__train-16-7 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-7
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 com... |
393 | SetFit/deberta-v3-large__sst2__train-16-8 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-8
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 com... |
394 | SetFit/deberta-v3-large__sst2__train-16-9 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-9
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 com... |
395 | SetFit/deberta-v3-large__sst2__train-32-0 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-32-0
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 com... |
396 | SetFit/deberta-v3-large__sst2__train-32-1 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-32-1
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 com... |
397 | SetFit/deberta-v3-large__sst2__train-8-0 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-0
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 comm... |
398 | SetFit/deberta-v3-large__sst2__train-8-1 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-1
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... |
399 | 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... |
400 | SetFit/deberta-v3-large__sst2__train-8-3 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-3
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... |
401 | SetFit/deberta-v3-large__sst2__train-8-4 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-4
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... |
402 | SetFit/deberta-v3-large__sst2__train-8-5 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-5
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... |
403 | SetFit/deberta-v3-large__sst2__train-8-6 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-6
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... |
404 | SetFit/deberta-v3-large__sst2__train-8-7 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-7
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... |
405 | SetFit/deberta-v3-large__sst2__train-8-8 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-8
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... |
406 | SetFit/deberta-v3-large__sst2__train-8-9 | [
"negative",
"positive"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-9
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... |
407 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-0 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
408 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-1 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
409 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-2 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
410 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-3 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
411 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-4 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
412 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-5 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
413 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-6 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-6
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
414 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-7 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-7
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
415 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-8 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-8
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
416 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-9 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-16-9
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
417 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-0 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
418 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-1 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
419 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-2 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
420 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-3 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
421 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-4 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
422 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-5 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
423 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-6 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-6
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
424 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-7 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-7
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
425 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-8 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-8
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
426 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-9 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-32-9
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
427 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-0 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
428 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-1 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
429 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-2 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__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 com... |
430 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-3 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
431 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-4 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
432 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
433 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-6 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-6
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
434 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-7 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-7
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
435 | SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-8 | [
"hate speech",
"neither",
"offensive language"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-8
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
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