datacollatorfortokenclassificationdatacollatorfortokenclassification 'datacollatorfortokenclassification'是一个用于分类任务的数据收集器,它可以将来自不同来源的数据进行整合和统一处理,以便于后续的数据预处理和模型训练。该数据收集器主要包括以下几个方面的功能: 1.数据整合:将来自不同来源的数据整合到一起,包括文本...
DataCollatorMixin类 DataCollatorForTokenClassification类 DataCollatorMixin类 classDataCollatorMixin:def__call__(self,features,return_tensors=None):ifreturn_tensorsisNone:return_tensors=self.return_tensorsifreturn_tensors=="pd":returnself.paddle_call(features)elifreturn_tensors=="np":returnself.numpy...
"default_data_collator", "DataCollator", "DefaultDataCollator", "DataCollatorForTokenClassification", "DataCollatorForSeq2Seq", "DataCollatorForLanguageModeling", "DataCollatorForWholeWordMask", ] InputDataClass = NewType("InputDataClass", Any) ...
# 改用DistributedSampler data_collator = DataCollatorForTokenClassification(tokenizer=tokenizer) train_sampler = torch.utils.data.distributed.DistributedSampler(tokenized_datasets["train"]) train_dataloader = DataLoader(tokenized_datasets["train"], collate_fn=data_collator, batch_size=32, shuffle=(train_...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - transformers/src/transformers/data/data_collator.py at v4.37.2 · huggingface/transformers
fromdatasetsimportDataset, Features,Sequence, ClassLabel, Value, Array2D, Array3DimportpandasaspdfromPILimportImagefromtransformersimportAutoProcessorfromtransformers.data.data_collatorimportdefault_data_collator img_dict = {}# specify names of any 2 local jpeg imagesfiles = ['file1','file2']forfile...
@dataclass class DataCollatorWithPadding: """ Data collator that will dynamically pad the inputs to the longest sequence in the batch. Args: tokenizer (`paddlenlp.transformers.PretrainedTokenizer`): The tokenizer used for encoding the data. """ tokenizer: PretrainedTokenizerBase padding: Union[...
We also define how to process the training data insidedata_collatoron line 91. The first two elements within the collator areinput_ids- the tokenized prompt andattention_mask- a simple 1/0 vector which denote which part of the tokenized vector is prompt and which part is the padding. ...
(tokenizer=tokenizer,file_path=val_file,block_size=128)# Define the data collator for batchingdata_collator=DataCollatorForLanguageModeling(tokenizer=tokenizer,mlm=False)# Set up the training argumentstraining_args=TrainingArguments(output_dir="path/to/output",overwrite_output_dir=True,num_train_...
DataCollatorForTokenClassification类适用于序列标注任务(token classification),比如命名实体识别(NER),每个token都会对应一个预测label,当一个序列的token比label多时,对额外的label位置添加-100处理,使得在计算交叉熵损失时,-100位置的label损失为0不用考虑。