关于在UCF101数据集上训练的问题

[xiezexun]

作者你好，看到你的论文和模型，我深受启发。我想在UCF101数据集上训练，但是遇到了以下问题：配置文件修改哪些内容？直接复制kenitecs400的配置文件可以吗？除了配置文件其他Python代码部分是否需要修改呢？

[Andy1621]

复制配置文件可以的，但是你需要调整相应的训练参数，python文件不需要修改，可以直接使用kinetics的数据集文件

[xiezexun]

感谢您的回复，我直接复制配置文件之后，修改了训练参数，但是训练ucf101的效果很不好，loss从头到尾一直在5.0左右波动，验证集的准确率也只有1%不到，不知道是哪里出了问题，恳请您给予解答。配置文件内容如下：
TRAIN:
ENABLE: True
DATASET: kinetics
BATCH_SIZE: 2
EVAL_PERIOD: 1
CHECKPOINT_PERIOD: 10
AUTO_RESUME: True
DATA:
USE_OFFSET_SAMPLING: True
DECODING_BACKEND: decord
NUM_FRAMES: 16
SAMPLING_RATE: 4
TRAIN_JITTER_SCALES: [256, 320]
TRAIN_CROP_SIZE: 224
TEST_CROP_SIZE: 224
INPUT_CHANNEL_NUM: [3]
PATH_PREFIX: ../../data/ucf101/videos
PATH_TO_DATA_DIR: ../data_list/ucf101/split1
TRAIN_JITTER_SCALES_RELATIVE: [0.08, 1.0]
TRAIN_JITTER_ASPECT_RELATIVE: [0.75, 1.3333]
UNIFORMERV2:
BACKBONE: 'uniformerv2_l14'
N_LAYERS: 4
N_DIM: 1024
N_HEAD: 16
MLP_FACTOR: 4.0
BACKBONE_DROP_PATH_RATE: 0.
DROP_PATH_RATE: 0.
MLP_DROPOUT: [0.5, 0.5, 0.5, 0.5]
CLS_DROPOUT: 0.5
RETURN_LIST: [20, 21, 22, 23]
NO_LMHRA: True
TEMPORAL_DOWNSAMPLE: False
AUG:
NUM_SAMPLE: 1
ENABLE: True
COLOR_JITTER: 0.4
AA_TYPE: rand-m7-n4-mstd0.5-inc1
INTERPOLATION: bicubic
RE_PROB: 0.
RE_MODE: pixel
RE_COUNT: 1
RE_SPLIT: False
BN:
USE_PRECISE_STATS: False
NUM_BATCHES_PRECISE: 200
SOLVER:
ZERO_WD_1D_PARAM: True
BASE_LR_SCALE_NUM_SHARDS: True
BASE_LR: 4e-4
COSINE_AFTER_WARMUP: True
COSINE_END_LR: 1e-6
WARMUP_START_LR: 1e-6
WARMUP_EPOCHS: 0.
LR_POLICY: cosine
MAX_EPOCH: 50
MOMENTUM: 0.9
WEIGHT_DECAY: 0.05
OPTIMIZING_METHOD: adamw
MODEL:
NUM_CLASSES: 101
ARCH: uniformerv2
MODEL_NAME: Uniformerv2
LOSS_FUNC: cross_entropy
DROPOUT_RATE: 0.5
USE_CHECKPOINT: False
CHECKPOINT_NUM: [0]
TEST:
ENABLE: True
DATASET: kinetics_sparse
BATCH_SIZE: 8
NUM_SPATIAL_CROPS: 1
NUM_ENSEMBLE_VIEWS: 1
DATA_LOADER:
NUM_WORKERS: 8
PIN_MEMORY: True
TENSORBOARD:
ENABLE: False
NUM_GPUS: 1
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: ../exp/ucf101

[Andy1621]

不知道是否解决？