nas / PFMBench /tasks /configs /tape_stability.yaml
yuccaaa's picture
Add files using upload-large-folder tool
48cce71 verified
Output:
res_dir: "tasks/results/tape_stability"
ex_name: "tape_stability_adapter" # ${oc.env:EXP_NAME, 'default'}
offline: ${eval:"int(${oc.env:OFFLINE, '1'})"}
Data:
# TAPE_Stability
train_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/TAPE_Stability/mmseq_outdir/train.csv"
val_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/TAPE_Stability/mmseq_outdir/val.csv"
test_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/TAPE_Stability/mmseq_outdir/test.csv"
# train_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/saprot_tape_stab/train.csv"
# val_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/saprot_tape_stab/valid.csv"
# test_data_path: "/nfs_beijing/kubeflow-user/zhangyang_2024/workspace/protein_benchmark/datasets/saprot_tape_stab/test.csv"
Training:
epoch: 50 # end epoch
lr: 1e-4 # Learning rate
lr_scheduler: "cosine"
check_val_every_n_epoch: 1
seed: 2024
batch_size: 8
num_workers: 4
seq_len: 1024
Model:
pretrain_model_name: 'esm_650m'
finetune_type: 'adapter'
peft_type: 'lora'
lora_r: 8 # 低秩矩阵的秩
lora_alpha: 16 # LoRA 的 alpha 参数
lora_dropout: 0.1 # Dropout 防止过拟合
Task:
task_name: "tape_stability"
task_type: "regression"
num_classes: 1
# metric: "valid_spearman"
# direction: "max"
hydra:
output_subdir: null