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MiguelAFH
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Jun 2, 2025
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| if __name__ == "__main__": | ||
| # Step 1: Process the zip file | ||
| zip_path = "/share/pi/nigam/data/medhelm/release/v2/benchmark_output_unredacted_20250512_060221.zip" |
Collaborator
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Let's use the /share/pi/nigam/data/medhelm/release/v2/benchmark_output_unredacted_20250531_192811.zip instead. It shouldn't change the results, but just to make sure we are using the latest.
| not_sorry_count = 0 | ||
| for item in data: | ||
| text = item.get("predicted_text", "") | ||
| if "sorry" in text.lower(): |
Collaborator
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Instead of just using the word sorry, let's not count the instances where the following strings appears in text.lower():
sorry to hearsorry for your
In such cases, the model is being empathetic in its response.
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