RoBERTa分类RuntimeError:形状'[-1，9]‘对于大小为8的输入无效

Question

    m = MultiLabelBinarizer()

    X = pd.read_csv('data/data.csv', sep=None, engine='python')
    X = X.dropna()

    Y_train = m.fit_transform(X['labels'])
    Y_train2 = [list(i) for i in Y_train]

    data = pd.DataFrame({'text': pd.Series(X[text_col]), 'labels': Y_train2})
    data = data.dropna()

    train_df, eval_df = train_test_split(data, test_size=0.2)

    numLabels = len(pd.unique(X['labels])) # count of the labels

    model = MultiLabelClassificationModel('roberta', 'roberta-base', num_labels=numLabels, use_cuda=False)

    model.train_model(pd.DataFrame(train_df))

我的标签列的数据结构是：[0,1,0,0,0,1,0, 0，1,1,0,0,1,0,0，0，0，0，0，0，0，0，0，0，0，1...]对于每一行，在label-column中都有一个类似于0,1,0,0,0,1,0,0的标签列表

对于文本，每行有一个文本(报纸文章)。

(从该来源获得：https://github.com/ThilinaRajapakse/simpletransformers#minimal-start-for-multilabel-classification)

如果我只用4个条目训练模型，就可以对模型进行训练。但是当我想用整个数据集来训练它时，它告诉我: RuntimeError: shape '-1，9‘对于大小为8的输入是无效的：

 File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/simpletransformers/classification/multi_label_classification_model.py", line 121, in train_model
    return super().train_model(train_df, multi_label=multi_label, eval_df=eval_df, output_dir=output_dir, show_running_loss=show_running_loss, args=args)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/simpletransformers/classification/classification_model.py", line 208, in train_model
    global_step, tr_loss = self.train(train_dataset, output_dir, multi_label=multi_label, show_running_loss=show_running_loss, eval_df=eval_df, **kwargs)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/simpletransformers/classification/classification_model.py", line 306, in train
    outputs = model(**inputs)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/nn/modules/module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/simpletransformers/custom_models/models.py", line 117, in forward
    loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1, self.num_labels))
RuntimeError: shape '[-1, 9]' is invalid for input of size 8

我不知道8的尺寸是从哪里来的，也不知道现在该怎么做，因为它只有很少的条目。有人能帮上忙吗？

Answer 1

0,1,0,0,0,1,0,0 -它是8个大小，但你的模型期望大小为9。这意味着，你的numLabels = 9。如果你有9个类，那么标签列中的标签列表应该是这样的: 0,1,0,0,0,1,0,0,0。但我认为你只需要通过num_labels作为8