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authorvin <git@vineetk.net>2025-08-24 00:31:29 -0400
committervin <git@vineetk.net>2025-08-24 00:31:29 -0400
commit0f5fcee95648d706b792affee0658e2e652fd904 (patch)
tree68d358b64d76fdb6613f37ff6953a00694bcc2a1 /asr.py
parent48cdc65c0eafa08fc39b5bfa49ef7c42943ac91d (diff)
try finetuning encoder-decoder model like t5gemmaHEADmaster
Unfortunately once it finishes the finetuning process, it doesn't actually output anything. With decoder-only models like small gemma3, it also doesn't output anything meaningful. I'm tempted to just classify each token as an ad or not, finetune an encoder like some long-context BERT, and then a post-processing script to convert back to tokens and their timestamps. May end up being more performant and efficient too...
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