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@@ -9,14 +9,36 @@ model-index:
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  - name: Fake-News-Detector
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  results: []
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  widget:
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- - text: "In a shocking turn of events, reports have surfaced suggesting that a clandestine meeting of world leaders took place on Mars to discuss plans for the colonization of the Red Planet. According to anonymous sources within the highest echelons of government, the summit was organized by a coalition of space agencies and private corporations aiming to expedite humanity's expansion beyond Earth. The meeting purportedly took place in a hidden underground facility on Mars, accessible only to a select few individuals privy to the ambitious project."
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- example_title: "Mars Meeting"
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- - text: "In a groundbreaking revelation that has sent shockwaves through the scientific community, Dr. Rachel Bennett, a renowned researcher at the prestigious Cambridge Institute of Biotechnology, claims to have unlocked the elusive secret to eternal youth. According to Dr. Bennett, years of tireless research have culminated in the discovery of a revolutionary anti-aging compound derived from a rare Amazonian plant known only to indigenous tribes. Initial trials on laboratory mice have yielded astonishing results, with subjects exhibiting signs of reversed aging and enhanced vitality."
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- example_title: "Dr. Bennett"
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- - text: "Apples are orange"
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- example_title: "Oranges are Apples"
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- - text: "Donald Trump is the 45th president of the United States."
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- example_title: "True News"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -24,7 +46,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # Fake-News-Detector
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- This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0096
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  - Accuracy: 0.9976
@@ -76,4 +98,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.38.2
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  - Pytorch 2.2.0+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.1
 
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  - name: Fake-News-Detector
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  results: []
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  widget:
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+ - text: >-
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+ In a shocking turn of events, reports have surfaced suggesting that a
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+ clandestine meeting of world leaders took place on Mars to discuss plans for
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+ the colonization of the Red Planet. According to anonymous sources within
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+ the highest echelons of government, the summit was organized by a coalition
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+ of space agencies and private corporations aiming to expedite humanity's
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+ expansion beyond Earth. The meeting purportedly took place in a hidden
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+ underground facility on Mars, accessible only to a select few individuals
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+ privy to the ambitious project.
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+ example_title: Mars Meeting
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+ - text: >-
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+ In a groundbreaking revelation that has sent shockwaves through the
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+ scientific community, Dr. Rachel Bennett, a renowned researcher at the
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+ prestigious Cambridge Institute of Biotechnology, claims to have unlocked
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+ the elusive secret to eternal youth. According to Dr. Bennett, years of
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+ tireless research have culminated in the discovery of a revolutionary
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+ anti-aging compound derived from a rare Amazonian plant known only to
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+ indigenous tribes. Initial trials on laboratory mice have yielded
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+ astonishing results, with subjects exhibiting signs of reversed aging and
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+ enhanced vitality.
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+ example_title: Dr. Bennett
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+ - text: Apples are orange
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+ example_title: Oranges are Apples
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+ - text: Donald Trump is the 45th president of the United States.
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+ example_title: True News
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+ datasets:
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+ - AlexanderHolmes0/true-fake-news
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+ language:
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+ - en
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+ pipeline_tag: text-classification
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # Fake-News-Detector
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+ This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the [true-fake-news](https://huggingface.co/datasets/AlexanderHolmes0/true-fake-news) dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0096
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  - Accuracy: 0.9976
 
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  - Transformers 4.38.2
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  - Pytorch 2.2.0+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.1