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Right now we search through Fourier degrees and regressor hyperparameters, why not search through the period space too? (The answer is because it's extremely slow, but this could actually be another p…
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I tried to fine tune the code generation tasks on specific domains using lora for the 220M, 770M, 2B, 6B models. When I kept the hyperparameters consistent (target_modules I set to default parameters …
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Hi! Thank you for your effort for the excellent and interesting work of DreamVideo.
I have tried to train my own DreamVideo using the previously released ModelScopeT2V model weight, but got quite poo…
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The reason is sklearn.clone will lead to issues if the hyperparameters are not well used.
Problem can be reproduced by cloning models:
This includes:
* COD
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``` py
from pytorch_lightning import LightningModule
class Transformer(LightningModule):
self.save_hyperparameters()
self.hello_there = torch.nn.Module()
model = Transformer…
jl749 updated
2 years ago
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I failed to reproduce the experimental results in your paper. For example, on the A-W dataset of office31, the best result is only 92.70. I used the default hyperparameters, and the only thing I chang…
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Currently using some arbitrary values for the hyperparameters. I've marked what needs to be changed like [THIS].
Code to produce the figure is [here](https://github.com/maxbiostat/R0_uncertainty/b…
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Thanks for the great work!
Does thresholds_for_classes introduce additional hyperparameters?
https://github.com/tianzhi0549/FCOS/blob/dd4ca761f439a48a8c3003d1be74e9f85c050534/demo/fcos_demo.py#L57…
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Hi! Thanks for the amazing work!
When I reproduced the code, the value of the loss function appears to be nan during the finetuning process:
```
batch: 0, GD_loss: 8.13, RD_loss: 7.95, reversed_…
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Let is assume I have a dataset with 3 independent valiables/predictors/features. So far I used code along those lines successfully:
```
hyperparameters = {
'max_depth': '10',
'nu…