Upload Main_200014
Browse files- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_005000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_010000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_015000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_020000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_025000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_030000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_035000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_040000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_045000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_050000.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/cfg.txt +55 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/tensorboard/events.out.tfevents.1768807194.brev-5x9knwe1p.3708293.0 +3 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/timemoe_base.py +126 -0
- Main_200014/50a47da570c7010fe8e0a1c34a78d536/training_log_20260119071944.log +114 -0
Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_005000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_010000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_015000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_020000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_025000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_030000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_035000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_040000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_045000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_050000.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/cfg.txt
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DESCRIPTION: TimeMoE Base
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DEVICE: gpu
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DEVICE_NUM: 3
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RUNNER: <class 'baselines.TimeMoE4.runner.runner.TimeMoERunner'>
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MODEL:
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NAME: TimeMoE4
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ARCH: <class 'baselines.TimeMoE4.arch.timemoe.TimeMoE4'>
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PARAM:
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model_id: baselines/TimeMoE/ckpt/TimeMoE-50M
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from_pretrained: False
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context_length: 4079
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trust_remote_code: True
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DTYPE: bfloat16
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METRICS:
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FUNCS:
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TRAIN:
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COMPILE_MODEL: True
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NUM_ITERATIONS: 200014
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CKPT_SAVE_DIR: checkpoints/TimeMoE4/Main_200014
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CKPT_SAVE_STRATEGY: 5000
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LOSS: fake_loss
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OPTIM:
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TYPE: AdamW
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PARAM:
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lr: 0.001
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betas: (0.9, 0.95)
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fused: True
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LR_SCHEDULER:
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TYPE: CosineWarmup
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PARAM:
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num_warmup_steps: 10000
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num_training_steps: 200014
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CLIP_GRAD_PARAM:
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max_norm: 1.0
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DATA:
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BATCH_SIZE: 85
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SHUFFLE: True
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PIN_MEMORY: True
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PREFETCH: True
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GRAD_ACCUMULATION_STEPS: 1
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VAL:
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INTERVAL: 5000
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DATA:
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BATCH_SIZE: 170
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EVAL:
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USE_GPU: True
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DATASET:
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NAME: Main
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TYPE: <class 'baselines.TimeMoE4.data.mix_dataset_v2.MixedSourceDataset_v2'>
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PARAM:
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num_valid_samples: 1000
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INFERENCE:
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GENERATION_PARAMS:
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normalize: True
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MD5: 50a47da570c7010fe8e0a1c34a78d536
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/tensorboard/events.out.tfevents.1768807194.brev-5x9knwe1p.3708293.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:40697a2fea2646111cad3d0310712e4422d6e6d9f69d51c3c65912b2a7002091
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size 11234316
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Main_200014/50a47da570c7010fe8e0a1c34a78d536/timemoe_base.py
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# 采样概率变化
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import os
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import sys
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from easydict import EasyDict
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sys.path.append(os.path.abspath(__file__ + '/../../..'))
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from ..arch import TimeMoE4
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from ..data import MixedSourceDataset_v2
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from ..runner import TimeMoERunner
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from ..loss import fake_loss
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############################## Hot Parameters ##############################
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# Dataset & Metrics configuration
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# Model architecture and parameters
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pretrained = False # Whether to use a pretrained model
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MODEL_ARCH = TimeMoE4
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MODEL_PARAM = {
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'model_id': "baselines/TimeMoE/ckpt/TimeMoE-50M",
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'from_pretrained': pretrained,
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'context_length': 4079,
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'trust_remote_code': True,
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}
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DATA_NAME = "Main"
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# N = 20_000_000
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# batch size = 16*8
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# 20_000_000 / 16 / 8 = 156250 iterations
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# 20_000_000 * 4096 / 16 / 8 / 4096 = 156_250
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NUM_ITERATIONS = 200_014 # 总轮数 20_000_000 * 4096 / 16 / 4 / 4096 = 312,500
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VAL_ITERATION_INTERVAL = 5_000 # 每VAL_ITERATION_INTERVAL执行一次验证
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############################## General Configuration ##############################
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CFG = EasyDict()
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# General settings
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CFG.DESCRIPTION = 'TimeMoE Base'
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CFG.DEVICE = 'gpu'
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CFG.DEVICE_NUM = 3
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# Runner
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CFG.RUNNER = TimeMoERunner
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############################## Model Configuration ################################
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CFG.MODEL = EasyDict()
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CFG.MODEL.NAME = MODEL_ARCH.__name__
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CFG.MODEL.ARCH = MODEL_ARCH
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CFG.MODEL.PARAM = MODEL_PARAM
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CFG.MODEL.DTYPE= 'bfloat16'
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# CFG.MODEL.DTYPE= 'float32'
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############################## Metrics Configuration ##############################
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CFG.METRICS = EasyDict()
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# Metrics settings
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CFG.METRICS.FUNCS = EasyDict({})
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############################## Training Configuration ##############################
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CFG.TRAIN = EasyDict()
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CFG.TRAIN.COMPILE_MODEL = True
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CFG.TRAIN.NUM_ITERATIONS = NUM_ITERATIONS
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CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
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'checkpoints',
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MODEL_ARCH.__name__,
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'_'.join([DATA_NAME, str(CFG.TRAIN.NUM_ITERATIONS)])
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)
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CFG.TRAIN.CKPT_SAVE_STRATEGY = VAL_ITERATION_INTERVAL * 1 # 保存策略,每VAL_ITERATION_INTERVAL * 5保存一次模型
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CFG.TRAIN.LOSS = fake_loss
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# Optimizer settings
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CFG.TRAIN.OPTIM = EasyDict()
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CFG.TRAIN.OPTIM.TYPE = "AdamW"
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CFG.TRAIN.OPTIM.PARAM = {
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"lr": 1e-3,
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"betas": (0.9, 0.95),
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# "betas": (0.9, 0.98),
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| 78 |
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"fused": True,
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# "weight_decay": 1e-1,
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}
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# Learning rate scheduler settings
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CFG.TRAIN.LR_SCHEDULER = EasyDict()
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CFG.TRAIN.LR_SCHEDULER.TYPE = "CosineWarmup"
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CFG.TRAIN.LR_SCHEDULER.PARAM = {
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'num_warmup_steps': 10_000, # 10k
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'num_training_steps': NUM_ITERATIONS,
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}
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CFG.TRAIN.CLIP_GRAD_PARAM = {
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'max_norm': 1.0
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}
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# Train data loader settings
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| 92 |
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CFG.TRAIN.DATA = EasyDict()
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CFG.TRAIN.DATA.BATCH_SIZE = 85 # 16 / 4
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CFG.TRAIN.DATA.SHUFFLE = True # has to be False
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CFG.TRAIN.DATA.PIN_MEMORY = True
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CFG.TRAIN.DATA.PREFETCH = True
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CFG.TRAIN.GRAD_ACCUMULATION_STEPS = 1
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# CFG.TRAIN.DATA.NUM_WORKERS = 4
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############################## Validation Configuration ##############################
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| 101 |
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CFG.VAL = EasyDict()
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| 102 |
+
CFG.VAL.INTERVAL = VAL_ITERATION_INTERVAL
|
| 103 |
+
CFG.VAL.DATA = EasyDict()
|
| 104 |
+
CFG.VAL.DATA.BATCH_SIZE = 170 # 32 / 8
|
| 105 |
+
|
| 106 |
+
############################## Evaluation Configuration ##############################
|
| 107 |
+
|
| 108 |
+
CFG.EVAL = EasyDict()
|
| 109 |
+
# Evaluation parameters
|
| 110 |
+
CFG.EVAL.USE_GPU = True # Whether to use GPU for evaluation. Default: True
|
| 111 |
+
|
| 112 |
+
############################## Dataset Configuration ##############################
|
| 113 |
+
CFG.DATASET = EasyDict()
|
| 114 |
+
# Dataset settings
|
| 115 |
+
CFG.DATASET.NAME = DATA_NAME
|
| 116 |
+
CFG.DATASET.TYPE = MixedSourceDataset_v2
|
| 117 |
+
CFG.DATASET.PARAM = EasyDict({
|
| 118 |
+
'num_valid_samples': 1000
|
| 119 |
+
})
|
| 120 |
+
|
| 121 |
+
############################## Inference Configuration ##############################
|
| 122 |
+
CFG.INFERENCE = EasyDict()
|
| 123 |
+
CFG.INFERENCE.GENERATION_PARAMS = EasyDict({
|
| 124 |
+
'normalize': not pretrained
|
| 125 |
+
})
|
| 126 |
+
|
Main_200014/50a47da570c7010fe8e0a1c34a78d536/training_log_20260119071944.log
ADDED
|
@@ -0,0 +1,114 @@
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|
|
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|
|
|
| 1 |
+
2026-01-19 07:19:44,428 - easytorch-training - INFO - Initializing training.
|
| 2 |
+
2026-01-19 07:19:44,429 - easytorch-training - INFO - Set clip grad, param: {'max_norm': 1.0}
|
| 3 |
+
2026-01-19 07:19:44,429 - easytorch-training - INFO - Building training data loader.
|
| 4 |
+
2026-01-19 07:19:54,179 - easytorch-training - INFO - MixedSourceDataset initialized for 'train' mode.
|
| 5 |
+
2026-01-19 07:19:54,179 - easytorch-training - INFO - - real: 3201174 samples
|
| 6 |
+
2026-01-19 07:19:54,179 - easytorch-training - INFO - - synth: 2000000 samples
|
| 7 |
+
2026-01-19 07:19:54,180 - easytorch-training - INFO - Train dataset length: 3201174
|
| 8 |
+
2026-01-19 07:19:54,182 - easytorch-training - INFO - Set optim: AdamW (
|
| 9 |
+
Parameter Group 0
|
| 10 |
+
amsgrad: False
|
| 11 |
+
betas: (0.9, 0.95)
|
| 12 |
+
capturable: False
|
| 13 |
+
differentiable: False
|
| 14 |
+
eps: 1e-08
|
| 15 |
+
foreach: None
|
| 16 |
+
fused: True
|
| 17 |
+
lr: 0.001
|
| 18 |
+
maximize: False
|
| 19 |
+
weight_decay: 0.01
|
| 20 |
+
)
|
| 21 |
+
2026-01-19 07:19:54,182 - easytorch-training - INFO - Set lr_scheduler: <basicts.runners.optim.lr_schedulers.CosineWarmup object at 0x753064a97dd0>
|
| 22 |
+
2026-01-19 07:19:54,184 - easytorch-training - INFO - Initializing validation.
|
| 23 |
+
2026-01-19 07:19:54,184 - easytorch-training - INFO - Building val data loader.
|
| 24 |
+
2026-01-19 07:19:54,463 - easytorch-training - INFO - Worker 0 initialized for cauker_univariate.
|
| 25 |
+
2026-01-19 07:20:20,862 - easytorch-training - INFO - MixedSourceDataset initialized for 'valid' mode.
|
| 26 |
+
2026-01-19 07:20:20,862 - easytorch-training - INFO - - real: 1000 samples
|
| 27 |
+
2026-01-19 07:20:20,862 - easytorch-training - INFO - Valid dataset length: 1000
|
| 28 |
+
2026-01-19 07:20:20,863 - easytorch-training - INFO - Number of parameters: 12628992
|
| 29 |
+
2026-01-19 07:20:20,863 - easytorch-training - INFO - Training with 3 GPUs, batch size per GPUs: 85, grad_accumulation_steps: 1
|
| 30 |
+
2026-01-19 07:20:20,863 - easytorch-training - INFO - Effective batch size: 255
|
| 31 |
+
2026-01-19 08:26:13,305 - easytorch-training - INFO - Iteration 5000 / 200014
|
| 32 |
+
2026-01-19 08:26:13,725 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.79 (s), train/lr: 2.50e-04, train/loss: 3.9592, train/grad_norm: 6.1824, train/amp_scale: 1.0000]
|
| 33 |
+
2026-01-19 08:26:13,725 - easytorch-training - INFO - Start validation.
|
| 34 |
+
2026-01-19 08:26:27,598 - easytorch-training - INFO - Result <val>: [val/time: 13.70 (s), val/loss: 3.3753]
|
| 35 |
+
2026-01-19 08:26:27,704 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 36 |
+
2026-01-19 08:26:27,815 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_005000.pt saved
|
| 37 |
+
2026-01-19 08:26:27,816 - easytorch-training - INFO - The estimated training finish time is 2026-01-21 03:25:10
|
| 38 |
+
2026-01-19 09:20:49,426 - easytorch-training - INFO - Iteration 10000 / 200014
|
| 39 |
+
2026-01-19 09:20:49,846 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.65 (s), train/lr: 7.50e-04, train/loss: 3.2398, train/grad_norm: 2.2217, train/amp_scale: 1.0000]
|
| 40 |
+
2026-01-19 09:20:49,846 - easytorch-training - INFO - Start validation.
|
| 41 |
+
2026-01-19 09:20:56,465 - easytorch-training - INFO - Result <val>: [val/time: 6.44 (s), val/loss: 3.3116]
|
| 42 |
+
2026-01-19 09:20:56,596 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 43 |
+
2026-01-19 09:20:56,713 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_010000.pt saved
|
| 44 |
+
2026-01-19 09:20:56,714 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 23:32:28
|
| 45 |
+
2026-01-19 10:15:17,743 - easytorch-training - INFO - Iteration 15000 / 200014
|
| 46 |
+
2026-01-19 10:15:18,161 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.65 (s), train/lr: 9.99e-04, train/loss: 3.1413, train/grad_norm: 1.9954, train/amp_scale: 1.0000]
|
| 47 |
+
2026-01-19 10:15:18,161 - easytorch-training - INFO - Start validation.
|
| 48 |
+
2026-01-19 10:15:24,759 - easytorch-training - INFO - Result <val>: [val/time: 6.42 (s), val/loss: 3.2741]
|
| 49 |
+
2026-01-19 10:15:24,887 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 50 |
+
2026-01-19 10:15:25,004 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_015000.pt saved
|
| 51 |
+
2026-01-19 10:15:25,005 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 22:14:45
|
| 52 |
+
2026-01-19 11:08:50,142 - easytorch-training - INFO - Iteration 20000 / 200014
|
| 53 |
+
2026-01-19 11:08:50,559 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.64 (s), train/lr: 9.96e-04, train/loss: 3.0921, train/grad_norm: 2.0023, train/amp_scale: 1.0000]
|
| 54 |
+
2026-01-19 11:08:50,559 - easytorch-training - INFO - Start validation.
|
| 55 |
+
2026-01-19 11:08:57,149 - easytorch-training - INFO - Result <val>: [val/time: 6.42 (s), val/loss: 3.2675]
|
| 56 |
+
2026-01-19 11:08:57,264 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 57 |
+
2026-01-19 11:08:57,374 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_020000.pt saved
|
| 58 |
+
2026-01-19 11:08:57,375 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 21:26:35
|
| 59 |
+
2026-01-19 12:01:38,196 - easytorch-training - INFO - Iteration 25000 / 200014
|
| 60 |
+
2026-01-19 12:01:38,617 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.63 (s), train/lr: 9.89e-04, train/loss: 3.0706, train/grad_norm: 1.9924, train/amp_scale: 1.0000]
|
| 61 |
+
2026-01-19 12:01:38,617 - easytorch-training - INFO - Start validation.
|
| 62 |
+
2026-01-19 12:01:45,244 - easytorch-training - INFO - Result <val>: [val/time: 6.45 (s), val/loss: 3.2473]
|
| 63 |
+
2026-01-19 12:01:45,377 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 64 |
+
2026-01-19 12:01:45,497 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_025000.pt saved
|
| 65 |
+
2026-01-19 12:01:45,497 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 20:51:47
|
| 66 |
+
2026-01-19 12:55:14,438 - easytorch-training - INFO - Iteration 30000 / 200014
|
| 67 |
+
2026-01-19 12:55:14,860 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.64 (s), train/lr: 9.79e-04, train/loss: 3.0554, train/grad_norm: 2.0358, train/amp_scale: 1.0000]
|
| 68 |
+
2026-01-19 12:55:14,861 - easytorch-training - INFO - Start validation.
|
| 69 |
+
2026-01-19 12:55:21,487 - easytorch-training - INFO - Result <val>: [val/time: 6.45 (s), val/loss: 3.2401]
|
| 70 |
+
2026-01-19 12:55:21,614 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 71 |
+
2026-01-19 12:55:21,732 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_030000.pt saved
|
| 72 |
+
2026-01-19 12:55:21,733 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 20:33:56
|
| 73 |
+
2026-01-19 13:49:00,480 - easytorch-training - INFO - Iteration 35000 / 200014
|
| 74 |
+
2026-01-19 13:49:00,899 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.64 (s), train/lr: 9.66e-04, train/loss: 3.0499, train/grad_norm: 2.0126, train/amp_scale: 1.0000]
|
| 75 |
+
2026-01-19 13:49:00,900 - easytorch-training - INFO - Start validation.
|
| 76 |
+
2026-01-19 13:49:07,719 - easytorch-training - INFO - Result <val>: [val/time: 6.64 (s), val/loss: 3.2354]
|
| 77 |
+
2026-01-19 13:49:07,840 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 78 |
+
2026-01-19 13:49:07,951 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_035000.pt saved
|
| 79 |
+
2026-01-19 13:49:07,952 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 20:22:07
|
| 80 |
+
2026-01-19 14:43:01,179 - easytorch-training - INFO - Iteration 40000 / 200014
|
| 81 |
+
2026-01-19 14:43:01,597 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.65 (s), train/lr: 9.49e-04, train/loss: 3.0318, train/grad_norm: 2.0432, train/amp_scale: 1.0000]
|
| 82 |
+
2026-01-19 14:43:01,597 - easytorch-training - INFO - Start validation.
|
| 83 |
+
2026-01-19 14:43:08,189 - easytorch-training - INFO - Result <val>: [val/time: 6.42 (s), val/loss: 3.2270]
|
| 84 |
+
2026-01-19 14:43:08,316 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 85 |
+
2026-01-19 14:43:08,434 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_040000.pt saved
|
| 86 |
+
2026-01-19 14:43:08,434 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 20:14:28
|
| 87 |
+
2026-01-19 15:36:00,962 - easytorch-training - INFO - Iteration 45000 / 200014
|
| 88 |
+
2026-01-19 15:36:01,379 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.63 (s), train/lr: 9.29e-04, train/loss: 3.0320, train/grad_norm: 2.0299, train/amp_scale: 1.0000]
|
| 89 |
+
2026-01-19 15:36:01,380 - easytorch-training - INFO - Start validation.
|
| 90 |
+
2026-01-19 15:36:07,990 - easytorch-training - INFO - Result <val>: [val/time: 6.44 (s), val/loss: 3.2236]
|
| 91 |
+
2026-01-19 15:36:08,124 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_best_val_loss.pt saved
|
| 92 |
+
2026-01-19 15:36:08,245 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_045000.pt saved
|
| 93 |
+
2026-01-19 15:36:08,246 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 20:04:00
|
| 94 |
+
2026-01-19 16:29:58,457 - easytorch-training - INFO - Iteration 50000 / 200014
|
| 95 |
+
2026-01-19 16:29:58,876 - easytorch-training - INFO - Result <train>: [train/iter_time: 0.64 (s), train/lr: 9.07e-04, train/loss: 3.0149, train/grad_norm: 2.0357, train/amp_scale: 1.0000]
|
| 96 |
+
2026-01-19 16:29:58,876 - easytorch-training - INFO - Start validation.
|
| 97 |
+
2026-01-19 16:30:05,501 - easytorch-training - INFO - Result <val>: [val/time: 6.45 (s), val/loss: 3.2239]
|
| 98 |
+
2026-01-19 16:30:05,621 - easytorch-training - INFO - Checkpoint checkpoints/TimeMoE4/Main_200014/50a47da570c7010fe8e0a1c34a78d536/TimeMoE4_050000.pt saved
|
| 99 |
+
2026-01-19 16:30:05,622 - easytorch-training - INFO - The estimated training finish time is 2026-01-20 19:59:29
|
| 100 |
+
2026-01-19 17:17:11,237 - easytorch-training - ERROR - Traceback (most recent call last):
|
| 101 |
+
File "/home/nvidia/miniconda3/envs/zxx/lib/python3.11/site-packages/easytorch/launcher/launcher.py", line 31, in training_func
|
| 102 |
+
runner.train(cfg)
|
| 103 |
+
File "/lp-dev/zhouxx/BasicTS/basicts/runners/base_iteration_runner.py", line 200, in train
|
| 104 |
+
self.train_iters(iteration=iteration, dataloader=self.train_data_loader)
|
| 105 |
+
File "/lp-dev/zhouxx/BasicTS/basicts/runners/base_utsf_runner.py", line 281, in train_iters
|
| 106 |
+
self.backward(loss, accumulating=accumulating)
|
| 107 |
+
File "/lp-dev/zhouxx/BasicTS/basicts/runners/base_utsf_runner.py", line 337, in backward
|
| 108 |
+
grad_norm = sum(
|
| 109 |
+
^^^^
|
| 110 |
+
File "/lp-dev/zhouxx/BasicTS/basicts/runners/base_utsf_runner.py", line 338, in <genexpr>
|
| 111 |
+
param.grad.data.norm(2).item() ** 2 for param in self.model.parameters() if param.grad is not None
|
| 112 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 113 |
+
KeyboardInterrupt
|
| 114 |
+
|