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README.md
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license: mit
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Classifier is fine-tuned from [deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on [this forecastability classification dataset](https://huggingface.co/datasets/noanabeshima/forecastability_classification_2) to predict if Claude 3.7 Sonnet thinks a [fineweb](https://huggingface.co/datasets/HuggingFaceFW/fineweb/viewer/default/train) document is 'forecastable', i.e. is a useful seed for generating pastcasting questions.
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Despite having a ROC AUC of .9625, only ~2% of fineweb documents are considered forecastable, so this classifier's precision/recall curves on random unseen fineweb documents look like this:
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license: mit
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To load the model use
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```
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model = AutoModel.from_pretrained('noanabeshima/forecastability-classifier-v1')
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tokenizer = AutoTokenizer.from_pretrained('noanabeshima/forecastability-classifier-v1')
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```
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Classifier is fine-tuned from [deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on [this forecastability classification dataset](https://huggingface.co/datasets/noanabeshima/forecastability_classification_2) to predict if Claude 3.7 Sonnet thinks a [fineweb](https://huggingface.co/datasets/HuggingFaceFW/fineweb/viewer/default/train) document is 'forecastable', i.e. is a useful seed for generating pastcasting questions.
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Despite having a ROC AUC of .9625, only ~2% of fineweb documents are considered forecastable, so this classifier's precision/recall curves on random unseen fineweb documents look like this:
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