#为保存val_acc最大时模型的权重 mc=ModelCheckpoint(filepath,monitor='val_acc',verbose=1,save_best_only=True,mode='max') callbacks_list=[mc] model.fit(train_data,y_train,epochs=20, batch_size=32,validation_data=(test_data,y_test),callbacks=callbacks_list) 1 2 3 4 5 6 7 8 9 10 ...
('LR_SCHEDULER', 'default', 'LinearLR') not found in ast index file 2023-06-26 20:32:28,194 - modelscope - INFO - Stage: before_run: (ABOVE_NORMAL) OptimizerHook (LOW ) LrSchedulerHook (LOW ) CheckpointHook (VERY_LOW ) TextLoggerHook --- Stage: before_train_epoch: (LOW ) Lr...
tensorflow.python.framework.errors_impl.NotFoundError: Object s3://qsl/output/qsl_1025/output/V0006//checkpoints/model.ckpt_temp_82e93a330c904f7ead139a83b4a37207/part-00000-of-00001.index does not exist [Op:MergeV2Checkpoints] 在obs中生成的checkpoint文件如下: -model.ckpt_temp_82e93a330c904...
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder...
checkpointstore.blob com.azure.ai.formrecognizer.documentanalysis.administration com.azure.ai.formrecognizer.documentanalysis com.azure.ai.formrecognizer com.azure.ai.formrecognizer.documentanalysis.models com.azure.ai.formrecognizer.documentanalysis.administration.models com.azure.ai.formrecognizer.models com....
🐛 Describe the bug Hello, when I am using DDP to train a model, I found that using multi-task loss and gradient checkpointing at the same time can lead to gradient synchronization failure between GPUs, which in turn causes the parameters...
export QUANT_WEIGHT_PATH=/home/quant_weight # Single-chip quantization export ENABLE_QUANT=1 python3 generate_weights.py --model_path ${CHECKPOINT} python3 main.py --mode precision_dataset --model_path ${CHECKPOINT} --ceval_dataset ${DATASET} --batch 8 --device 0 # Dual-chip ...
"," use checkpoint-3 as final checkpoint","2024-10-29 17:03:47,719 - INFO - transfer for inference succeeded, start to deliver it for inference","2024-10-29 17:09:43,322 - INFO - start to save checkpoint","2024-10-29 17:11:24,689 - INFO - finetune-job succeeded","2024-10...
When each training epoch completes a checkpoint is generated. A checkpoint is a fully functional version of a model which can both be deployed and used as the target model for subsequent fine-tuning jobs. Checkpoints can be particularly useful, as they can provide a snapshot of your model pr...
At the end of training, the model checkpoint with the lowest mean cross-modal retrieval rank on the validation set was selected for testing. Before computing the cosine similarity between vector embeddings, we always divide them by their norms to ensure that they have the same magnitude. This ...