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Update README.md
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: verdict-classifier
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results:
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---
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should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2238
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- F1 Macro: 0.8540
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- F1 Misinformation: 0.9798
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- Prec Factual: 0.9889
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- Prec Other: 0.5294
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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- Transformers 4.11.3
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- Pytorch 1.9.0+cu102
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- Datasets 1.9.0
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- Tokenizers 0.10.2
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---
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license: mit
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language:
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- am
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- ar
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- hy
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- eu
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- bn
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- bs
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- bg
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- my
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- hr
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- ca
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- cs
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- da
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- nl
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- en
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- et
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- fi
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- fr
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- ka
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- de
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- el
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- gu
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- ht
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- iw
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- hi
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- hu
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- is
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- in
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- it
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- ja
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- kn
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- km
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- ko
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- lo
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- lv
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- lt
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- ml
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- mr
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- ne
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- no
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- or
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- pa
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- ps
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- fa
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- pl
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- pt
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- ro
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- ru
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- sr
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- zh
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- sd
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- si
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- sk
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- sl
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- es
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- sv
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- tl
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- ta
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- te
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- th
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- tr
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- uk
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- ur
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- ug
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- vi
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- cy
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tags:
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- generated_from_trainer
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model-index:
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- name: verdict-classifier-en
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results:
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- task:
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type: text-classification
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name: Verdict Classification
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widget:
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- "Even though it might look true, it has been taken out of context."
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---
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# Multilingual Verdict Classifier
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on 2,500 deduplicated multilingual verdicts from [Google Fact Check Tools API](https://developers.google.com/fact-check/tools/api/reference/rest/v1alpha1/claims/search), translated into 65 languages with the [Google Cloud Translation API](https://cloud.google.com/translate/docs/reference/rest/).
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It achieves the following results on the evaluation set, being 1,000 such verdicts, but here including duplicates to represent the true distribution:
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- Loss: 0.2238
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- F1 Macro: 0.8540
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- F1 Misinformation: 0.9798
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- Prec Factual: 0.9889
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- Prec Other: 0.5294
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## Training procedure
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- Transformers 4.11.3
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- Pytorch 1.9.0+cu102
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- Datasets 1.9.0
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- Tokenizers 0.10.2
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