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I have attempted to reproduce the results of the few-shot classification task on the PASCAL VOC dataset.
I managed to achieve comparable outcomes when utilizing the fine-tuned tokens you previously s…
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I'm trying to differentiate through `predict_fn` provided by https://github.com/google/neural-tangents. This is doable with `jax.grad`, but not with `eagerpy.value_and_grad`.
ybj14 updated
4 years ago
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反向传播(backpropagation):计算cost function关于w和b的偏微分。
要想应用反向传播,cost function需要满足两个条件:
1. The cost function can be written as an average C=1/n*∑C_x over cost functions C_x for individual training examp…
hysic updated
7 years ago
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Hello,
I have a PersistentModel with MultilayerPerceptron and I trained this model before. I have another dataset which has more than 500.000 rows. I want to train a model that already trained before…
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The loss may be negative number in the model. The reason is that the reinforce loss is often to be a negative number since the reward is the larger the better. But I am very confusing about how negati…
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I am working on a project where I sample a set of n-dimensional points from a Gaussian distribution (of learnt parameters) as follows and then evaluate those points based on a loss function to update …
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It's nice that we can intervene on a model's state PyTree, which in Feedbax is an `equinox.Module` object that is modified out-of-place by the model itself, which is an instance of [`AbstractStagedMod…
mlprt updated
2 months ago
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A niche case for some extensions is to use a bookworm word count index as an input to a batched machine learning process. I sometimes want to train a neural network on word counts, for example.
A `SE…