Add evaluation results on the default config of xsum
Browse filesBeep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\
Your model has been evaluated on the default config of the [xsum](https://huggingface.co/datasets/xsum) dataset by
@grapplerulrich
, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-xsum-9818ea4b-12975769).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=xsum).\
Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=xsum).
README.md
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@@ -51,8 +51,58 @@ language:
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licenses:
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- cc-by-nc-sa-4.0
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widget:
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-
- text:
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-
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---
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# mT5-multilingual-XLSum
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licenses:
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- cc-by-nc-sa-4.0
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widget:
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+
- text: Videos that say approved vaccines are dangerous and cause autism, cancer or
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infertility are among those that will be taken down, the company said. The policy
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includes the termination of accounts of anti-vaccine influencers. Tech giants
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have been criticised for not doing more to counter false health information on
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their sites. In July, US President Joe Biden said social media platforms were
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largely responsible for people's scepticism in getting vaccinated by spreading
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misinformation, and appealed for them to address the issue. YouTube, which is
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owned by Google, said 130,000 videos were removed from its platform since last
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year, when it implemented a ban on content spreading misinformation about Covid
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vaccines. In a blog post, the company said it had seen false claims about Covid
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jabs "spill over into misinformation about vaccines in general". The new policy
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covers long-approved vaccines, such as those against measles or hepatitis B. "We're
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expanding our medical misinformation policies on YouTube with new guidelines on
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currently administered vaccines that are approved and confirmed to be safe and
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effective by local health authorities and the WHO," the post said, referring to
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the World Health Organization.
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model-index:
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- name: csebuetnlp/mT5_multilingual_XLSum
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results:
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- task:
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type: summarization
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name: Summarization
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dataset:
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name: xsum
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type: xsum
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config: default
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split: test
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metrics:
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- name: ROUGE-1
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type: rouge
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value: 36.5002
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verified: true
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- name: ROUGE-2
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type: rouge
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value: 13.934
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verified: true
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- name: ROUGE-L
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type: rouge
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value: 28.9876
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verified: true
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- name: ROUGE-LSUM
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type: rouge
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value: 28.9958
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verified: true
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- name: loss
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type: loss
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value: 2.0674800872802734
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verified: true
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- name: gen_len
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type: gen_len
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value: 26.9733
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verified: true
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---
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# mT5-multilingual-XLSum
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