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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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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: >- |
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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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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0027 |
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- Accuracy: 0.9994 |
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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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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.201 | 0.09 | 100 | 0.0444 | 0.9901 | |
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| 0.0319 | 0.19 | 200 | 0.0241 | 0.9938 | |
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| 0.0222 | 0.28 | 300 | 0.0249 | 0.9932 | |
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| 0.0094 | 0.38 | 400 | 0.0076 | 0.9984 | |
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| 0.0042 | 0.47 | 500 | 0.0062 | 0.9988 | |
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| 0.0076 | 0.57 | 600 | 0.0040 | 0.9988 | |
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| 0.0095 | 0.66 | 700 | 0.0040 | 0.9990 | |
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| 0.008 | 0.76 | 800 | 0.0040 | 0.9988 | |
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| 0.0086 | 0.85 | 900 | 0.0030 | 0.9993 | |
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| 0.0042 | 0.95 | 1000 | 0.0027 | 0.9994 | |
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### Framework versions |
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- Transformers 4.39.1 |
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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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