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README.md
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@@ -84,7 +84,9 @@ The primary limitation encountered was improving stance classification accuracy
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Another limitation of this approach is that I was only training on the stance classification task. Given that the minimally invasive approach of PEFT did not have much impact, it could be worth exploring more impactful approaches like full fine-tuning. In that case, there is a risk that training the entire model will damage its ability to reason logically.
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Statement: This had the effect of taking the fringe religious doctrine of NI and making it much more common and American evangelical teaching but also taught a lot of churches that private education is a massive cash cow money laundry tax dodge on top of being a church
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Response: The author supports the claim by linking private education institutions to financial irregularities, including money laundering and tax evasion, suggesting that these institutions could indeed face future scrutiny and investigations. This aligns with the claim that private education may be at risk due to such practices.
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Example of the model perhaps confusing sentiment and stance, and struggling with slang:
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Statement: Let s aim to recycle and reuse as much as we can. . . . . noplastic plasticfree plasticpollution environment environmentalawareness environmentalfriendly savetheplanet plasticpollution noplasticbags noplasticwaste makeachange makeachangetoday
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Response: The author is in favor of reducing plastic pollution by promoting recycling, reusing, and minimizing plastic use. Phrases like "make a change today" and "save the planet" indicate a strong commitment to addressing environmental issues related to plastic pollution.
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Example of getting the right answer for the wrong reason:
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Statement: Two young Russian men decided to flee military mobilization and took the boat across the Bering Strait to a small American island off the coast of Alaska. They have now applied for asylum as refugees. Will the U.S. see a new wave of migrants in the north? 99 582 2,367
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Another limitation of this approach is that I was only training on the stance classification task. Given that the minimally invasive approach of PEFT did not have much impact, it could be worth exploring more impactful approaches like full fine-tuning. In that case, there is a risk that training the entire model will damage its ability to reason logically.
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Lastly, I include some examples of poor responses from the model to demonstrate its limitations:
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1) Great Example of Why “None” is hard:
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Statement: This had the effect of taking the fringe religious doctrine of NI and making it much more common and American evangelical teaching but also taught a lot of churches that private education is a massive cash cow money laundry tax dodge on top of being a church
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Response: The author supports the claim by linking private education institutions to financial irregularities, including money laundering and tax evasion, suggesting that these institutions could indeed face future scrutiny and investigations. This aligns with the claim that private education may be at risk due to such practices.
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2) Example of the model perhaps confusing sentiment and stance, and struggling with slang:
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Statement: Let s aim to recycle and reuse as much as we can. . . . . noplastic plasticfree plasticpollution environment environmentalawareness environmentalfriendly savetheplanet plasticpollution noplasticbags noplasticwaste makeachange makeachangetoday
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Response: The author is in favor of reducing plastic pollution by promoting recycling, reusing, and minimizing plastic use. Phrases like "make a change today" and "save the planet" indicate a strong commitment to addressing environmental issues related to plastic pollution.
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3) Example of getting the right answer for the wrong reason:
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Statement: Two young Russian men decided to flee military mobilization and took the boat across the Bering Strait to a small American island off the coast of Alaska. They have now applied for asylum as refugees. Will the U.S. see a new wave of migrants in the north? 99 582 2,367
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