Comments (5)
Yes, the dataset is the whole dataset I used to train the shared checkpoint. The testset loss is 0.25 in my experiment.
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Thanks for your reply! My test loss is 1.24 with the "chord" words. Did you get 0.25 without "chord"?
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Both shared checkpoint losses are 0.25.
from remi.
Got it. Thank you!
from remi.
Hello,
I have tried to train transformer-xl from scratch. However, the generating result is not as good as yours. The theme of one generated midi file is not consistent, which means the latest slice of sequence hears different from the prompt. Therefore,could you tell me if the dataset you provide is the whole dataset? or if you used other bigger dataset for pre-training and used the provided one only for finetuning?
My experiment setting is: n_layers: 12 x_len: 512 m_len:512 ff:2048
And could you tell me the testset cross-entropy loss you got in your experiment?
Thank you!
Hello, excuse me, I want to know how you started from scratch
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Related Issues (20)
- Issues with evaluation (std and salience for beat/downbeat) HOT 6
- questions about model.py HOT 1
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- MIDI files end up their last note pushed up a position HOT 6
- Checkpoints saved with a NAN value HOT 2
- i can't train from scratch after remove line 99 HOT 1
- How can I train my MIDI dataset
- Process finished with exit code -1073741571 (0xC00000FD)
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- style question
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