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Very similar to #67, except it allows for dropout before the first purchase: https://github.com/CamDavidsonPilon/lifetimes/blob/master/lifetimes/fitters/modified_beta_geo_fitter.py
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What's the reasoning behind the extra dropout layer after projection?
Karpathy's implementation has 2 dropout layers:
1. `attn_dropout`
2. `resid_dropout`
Karpathy's 2nd dropout layer
https…
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This is a great project, Open source training from scratch, simple and easy to use, especially suitable for ordinary people.
The currently sota algorithm models are highly similar to llama3. I hope…
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Here we list a few things that need to be made more explicit in the docs:
- The usage of `set_trainable` to change between feature and variational parameters in blocks. Maybe can be added in the [P…
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### 🐛 Describe the bug
https://github.com/pytorch/pytorch/pull/100064 caused 3% perf drop and 4% memory drop in HF training because of disabled low memory dropout
### Versions
master
cc @ezy…
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Thank you very much for sharing the whole implementation! I am curious about `dropout step` in this figure, may I ask some questions?
![image](https://user-images.githubusercontent.com/14788650/5874…
luzai updated
2 years ago
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I search "dropout" in the project. I only find this in lstm model .
I think add some structure to prevent from overfitting is necessary.
In my train of cross_encoder model, i find this have negative e…
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Hi, Thanks for sharing the code for your paper.
Could you please tell me where I must use the dropout layers in a resnet50 for a classification task on 224x224 resolution images? Do you have some i…
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# Single-Device-Abstract DDP
## Motivation
In current PyTorch DDP, when training a model with Dropout operations, the final results obtained from distributed training will not be consistent with t…
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I would like to build a neural network with a tunable number of layers. While I can tune the number of neurons per layer, I’m encountering issues when it comes to dynamically changing the number of la…