train_df=data_train,text_column="Cleaned",label_columns=col
,val_df=data_test,maxlen=500,preprocess_mode="distilbert") 下面是错误 OSError: Model name 'distilbert-base-uncased' was not found in tokenizers model name list (distilbert-base-uncased, <
我已经创建了一个简单的模型来使用DistilBERT进行文本分类。问题是我不知道如何在训练时进行交叉验证。下面提供了我的代码实现。 有没有人可以帮我在培训的同时实现交叉验证? 提前谢谢你。#Load distil bert model
model = TFDistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased
根据的教程,我正在尝试对huggingface的distilbert实现进行微调,以便在自定义数据集上进行多类分类(100类)。TFDistilBertForSequenceClassification
model = TFDistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased
under a tree and an apple hits my head.")但是,我得到以下错误:
No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-englishValueError: Could