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update: the lr during training

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alikia2x (寒寒) 2025-03-07 22:35:57 +08:00
parent ab6a91dd82
commit 638135dde6
Signed by: alikia2x
GPG Key ID: 56209E0CCD8420C6
1 changed files with 3 additions and 3 deletions
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filter/train.py
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@ -74,11 +74,11 @@ os.makedirs('./filter/checkpoints', exist_ok=True)
# 优化器 # 优化器
eval_interval = 20 eval_interval = 20
num_epochs = 20 num_epochs = 20
total_steps = samples_count * num_epochs / train_loader.batch_size total_steps = samples_count * num_epochs / batch_size
warmup_rate = 0.1 warmup_rate = 0.1
optimizer = optim.AdamW(model.parameters(), lr=5e-5, weight_decay=1e-5) optimizer = optim.AdamW(model.parameters(), lr=3e-5, weight_decay=1e-3)
cosine_annealing_scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=total_steps - int(total_steps * warmup_rate)) cosine_annealing_scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=total_steps - int(total_steps * warmup_rate))
warmup_scheduler = optim.lr_scheduler.LinearLR(optimizer, start_factor=0.4, end_factor=1.0, total_iters=int(total_steps * warmup_rate)) warmup_scheduler = optim.lr_scheduler.LinearLR(optimizer, start_factor=0.8, end_factor=1.0, total_iters=int(total_steps * warmup_rate))
scheduler = optim.lr_scheduler.SequentialLR(optimizer, schedulers=[warmup_scheduler, cosine_annealing_scheduler], milestones=[int(total_steps * warmup_rate)]) scheduler = optim.lr_scheduler.SequentialLR(optimizer, schedulers=[warmup_scheduler, cosine_annealing_scheduler], milestones=[int(total_steps * warmup_rate)])
criterion = nn.CrossEntropyLoss(weight=class_weights).to(device) criterion = nn.CrossEntropyLoss(weight=class_weights).to(device)