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Why is the model's accuracy so low when using residue embeddings from pre-trained model?
I’m using a pre-trained model esm3-sm-open-v1
to extract residue embeddings via link. However, the precision of my model is unexpectedly low. For reference, here’s a small snippet of the residue embeddings (shape: [num_tokens, embedding_dim]):
tensor([[ 175.0000, 102.5000, -99.0000, ..., -106.5000, -35.5000,
86.0000],
[ 205.0000, 103.5000, -139.0000, ..., -328.0000, -224.0000,
134.0000],
[ 130.0000, 49.2500, -26.2500, ..., -202.0000, -161.0000,
134.0000],
...,
[ 65.0000, -75.0000, 54.5000, ..., -62.0000, -26.2500,
-102.5000],
[ 173.0000, -60.0000, 205.0000, ..., 43.0000, -89.0000,
-115.5000],
[ -6.0000, 170.0000, 113.0000, ..., -44.0000, -115.0000,
43.7500]])