alpha =float(current_epoch) / (warmup_epoch)# warmup过程中lr倍率因子大小从warmup_factor -> 1returnwarmup_factor * (1- alpha) + alpha# 对于alpha的一个线性变换,alpha是关于x的一个反比例函数变化else:# warmup后lr的倍率因子从1 -> 0# 参考deeplab_v2: Learning rate policyreturn(1- (current...
num_train_steps = steps_per_epoch * epochs num_warmup_steps = 0 num_cycles = 0.5 scheduler = get_cosine_schedule_with_warmup(optimizer, num_warmup_steps=num_warmup_steps, num_training_steps=num_train_steps, num_cycles=num_cycles) criterion = nn.BCEWithLogitsLoss(reduction='none') best...
scheduler = get_cosine_schedule_with_warmup(optimizer, num_warmup_steps=len(train_loader),num_training_steps=EPOCHS*len(train_loader)) # AdamW它是 Adam 优化器的一种变体。它的作用是基于梯度更新神经网络的参数,使得损失函数最小化。 # 学习率先线性warmup一个epoch,然后cosine式下降。 # 这里给个小...
optimizer = AdamW(model.parameters(), lr=2e-5, weight_decay=1e-4) #AdamW优化器 scheduler = get_cosine_schedule_with_warmup(optimizer, num_warmup_steps=len(train_loader), num_training_steps=EPOCHS*len(train_loader)) # 学习率先线性warmup一个epoch,然后cosine式下降。 8 定义训练函数和验证测...
from transformers import BertModel, BertConfig, BertTokenizer, AdamW, get_cosine_schedule_with_warmup warnings.filterwarnings('ignore') 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 超参数配置: bert_path = "bert_model/s" # 该文件夹下存放三个文件('vocab.txt', 'pytorch_model.bin', 'config....
🐛 Bug If you're using a lr scheduler that needs access to the number of batches in the train dataset like @huggingface's get_linear_schedule_with_warmup, there's currently no way to access the dataset in configure_optimizers() because it...
scheduler = get_cosine_schedule_with_warmup( optimizer, args.warmup * args.iteration, args.total_steps) if args.use_ema: ema_model = ModelEMA(args, model, args.ema_decay, device) start_epoch = 0 if args.resume: logger.info("==> Resuming from checkpoint..") assert os.path.isfile(...
9 CosineAnnealingWarmRestarts 10 ReduceLROnPlateau 11 CyclicLR 12 OneCycleLR 13 warm up 14 ChainedScheduler 15 SequentialLR 1 LambdaLR 以自定义一个函数作为乘法因子控制衰减。 公式: 函数: 代码语言:javascript 复制 """ 将每个参数组的学习率设置为初始 lr 乘以给定函数.当 last_epoch=-1时,设置 lr ...
"will result in PyTorch skipping the first value of the learning rate schedule. " "See more details at " "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning) self._step_count += 1 class _enable_get_lr_call: ...
Learning rate schedule - we use cosine LR schedule For bigger batch sizes (512 and up) we use linear warmup of the learning rate during the first couple of epochs according toTraining ImageNet in 1 hour. Warmup length depends on the total training length. ...