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README.md
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@@ -37,7 +37,8 @@ This was unexpected, and weird, and probably would bear further investigation.
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The model was much worse at correctly identifying positive sentiment (57% accuracy) than it was at
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identifying negative sentiment (93% accuracy) - see Confusion Matrix, below. This performance on
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negative sentiment is good - State of the Art for SST2 overall is 97%
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Since the training dataset was balanced across positive and negative examples, this mismatch seems likely
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to have been present in the base model, although this was not confirmed. Next steps for improvement
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The model was much worse at correctly identifying positive sentiment (57% accuracy) than it was at
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| 39 |
identifying negative sentiment (93% accuracy) - see Confusion Matrix, below. This performance on
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| 40 |
+
negative sentiment is good - State of the Art for SST2 overall is 97%
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(achieved by [T5-11B](https://huggingface.co/google-t5/t5-11b)).
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Since the training dataset was balanced across positive and negative examples, this mismatch seems likely
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to have been present in the base model, although this was not confirmed. Next steps for improvement
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