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Create ribonanzanet_sec_struct/config.yaml
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# Model hyperparameters
learning_rate: 0.001 # The learning rate for the optimizer
batch_size: 2 # Number of samples per batch
test_batch_size: 8 # Number of samples per batch
epochs: 40 # Total training epochs
optimizer: "ranger" # Optimization algorithm
dropout: 0.05 # Dropout regularization rate
weight_decay: 0.0001
k: 5
ninp: 256
nlayers: 9
nclass: 2
ntoken: 5 #AUGC + padding/N token
nhead: 8
use_bpp: False
bpp_file_folder: "../../input/bpp_files/"
gradient_accumulation_steps: 2
use_triangular_attention: false
pairwise_dimension: 64
use_grad_checkpoint: true
# Other configurations
fold: 0
nfolds: 6
input_dir: "../../input/"
gpu_id: "0"