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Reviewed the baseline code + some of the synthetic code - Couple of places with local homedirs. :)
projects/roscoe/baselines/scores.py
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) | ||
# Path here to fine-tuend BART Model | ||
self.scorer.load( | ||
"/private/home/mpchen/BARTScore/train/reproduce/trained/bart_6000.pth" |
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Ahhh we might need to upload this to the AWS bucket as well and provide a URL to it here (or otherwise download it)
projects/roscoe/baselines/scores.py
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# sacrebleu>=1.4.8# | ||
# torch>=1.4.0 | ||
prism = SourceFileLoader( | ||
"prism", "/private/home/aslic/Evaluation/BARTScore/SUM/prism.py" |
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Ditto here - this one also needs to be a const to the file...
projects/roscoe/baselines/scores.py
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class PrismBaselineScorer(BaselineScorer): | ||
def __init__(self): | ||
self.scorer = prism.Prism( | ||
model_dir='/private/home/aslic/Evaluation/BARTScore/SUM/models/m39v1/', |
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aslic
projects/roscoe/baselines/scores.py
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class BleurtBaselineScorer(BaselineScorer): | ||
def __init__(self): | ||
self.scorer = bleurt_score.BleurtScorer( | ||
"/private/home/aslic/Evaluation/BARTScore_old/bleurt/bleurt/test_checkpoint" |
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lol, another part where we might just need to have the model checkpoint path installed
Thanks for putting together this (behemoth!) of a diff. :) |
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Accepting to unblock (also see comment about where the fine-tune model is uploaded)
device=DEFAULT_DEVICE, checkpoint='facebook/bart-large-cnn' | ||
) | ||
# Path here to fine-tuend BART Model | ||
self.scorer.load(BART_SCORE_REPO + "/train/reproduce/trained/bart_6000.pth") |
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Patch description
This is a set of scripts and data to support paper "ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning".
New repository "projects/roscoe" contains the code and reproduction steps for our paper.
New tasks support data loading, as well as synthetic perturbations described in paper.
Fixed protobuf dependency issue that was failing CircleCI builds
Testing steps