Hello everybody, I’m planning on fine-tuning XLSR-Wav2Vec2 in Bemba. I’m happy to collaborate with anybody willing to join me. So I have created this thread so that we can share and discuss issues here.Summary dataset details:Language: Bemba (or Icibemba) language of ZambiaDataset:BembaSpeech(If interested, you can check out thepaperfor more details).Duration: The dataset has the total duration of 24hrs of read speech already preprocessed and partitioned into train, dev and test sets.Size: 2.8GbSubset [optional]: There is also a 17hrs subset of the BembaSpeechhereconsisting of audio files less than 10 seconds.Progress:So far, I just quickly tried to fine-tune on the 17hrs subset using the parameters that came with@patrickvonplaten`snotebookbut ran into vanishing/exploding problem. So yeah, need to twerk a few parameters. So get in touch if you are willing to join in… I`m happy to collaborate with anyone in the community.Cheers!
2021-03-21T16:10:41Z
Update on my trainings progress:So I have been training using the 17hrs subset [optional] of the BembaSpeech:train,devandtest.To test the waters, first I trained using the dev and test sets only. The trainign went on without a problem. However, when I decided to include the training and evaluate on the dev set… I started getting thenanresults.
2021-03-21T16:11:32Z
Hey Claytone, I would suggest to play around a bit withlearning_rateanddropout. I’d both try to reduce and increase the learning rate…and reduce dropout if you keep gettingnanfor the training loss
2021-03-21T16:15:26Z
Thank you@patrickvonplaten. I will try that too. Is there a restriction to what the model accepts as maximum and minimum durations (length) of the audio files? Just in case…
2021-03-21T16:22:52Z
csikasote:audioThere is no real restriction, but for input samples that have a duration longer than ~2 minutes you might get “out-of-memory” errors. See here a related issue:can't allocate memory error with wav2vec2 · Issue #10366 · huggingface/transformers · GitHub