Comments (4)
thank you!
from neural-audio-fp.
- It depends. Usually
train-loss < 0.3
when setting the Softmax temperature parameter, tau=0.05 (see 640_lamb.yaml). - With this setup,
validation-loss (red)
andtrain-loss (blue)
until the 100th epoch:
- On each epoch end, we perform a
mini-search-test
.Accuracy@1s
and@3s
would be a useful validation of the model. As in the figure below, the accuracy is about82.x@1s
or94.x@3s
.
from neural-audio-fp.
The learning curve is from the pre-trained model in #10 .
from neural-audio-fp.
The loss
and val_acc
are updated. Please see #26 (comment)
from neural-audio-fp.
Related Issues (20)
- Unable to open the file "../demo_template.ipynb" HOT 1
- Speed of generating fingereprints from custom source HOT 8
- Questions about inquiries HOT 8
- Could you please provide the checksum of fma_full only? HOT 8
- Why the loss computed during training is NanοΌ HOT 9
- permission denied for building Docker Custom Image HOT 5
- FileNotFoundError: [Errno 2] No such file or directory: './logs/emb/CHECKPOINT_NAME/CHECKPOINT_INDEX/query_shape.npy' HOT 4
- IS THIS REPOSITORY HELPFUL FOR FOLLOWING SITUATION HOT 1
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- positve pairs and negitive pairs? HOT 1
- question: my modle train loss:nan HOT 2
- Comparing short audio files HOT 1
- finetuning on short audios HOT 5
- Evaluation with custom dataset HOT 7
- Fingerprint generation from custom dataset HOT 2
- Reported train, val, test split sizes vs actual FMA size HOT 3
- Questions Regarding Custom Data Testing in Audio Fragment Identification HOT 1
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from neural-audio-fp.