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I fine-tuned t5 models and now want to evaluate the trained model on a specific dataset/Task which can be easily done using eval mode. But the problem is, I also need other information (like row_id and other important columns) including targets and predictions. Is there a way to pass the whole example into the metrics function?
Currently, I am getting predictions from seqio.Task using eval mode and reading and evaluating the prediction file outside the seqio pipeline. Is there a way I can do my custom evaluation inside the pipeline only instead of reading the generated prediction file separately?
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Hi,
I fine-tuned t5 models and now want to evaluate the trained model on a specific dataset/Task which can be easily done using
eval
mode. But the problem is, I also need other information (like row_id and other important columns) including targets and predictions. Is there a way to pass the wholeexample
into the metrics function?Currently, I am getting predictions from
seqio.Task
usingeval
mode and reading and evaluating the prediction file outside theseqio pipeline
. Is there a way I can do my custom evaluation inside the pipeline only instead of reading the generated prediction file separately?Thanks.
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