默认SimpleTransformers设置失败，并显示ValueError str

Question

我正在尝试使用SimpleTransformers默认设置进行多任务学习。

我使用的是他们网站here中的示例

代码如下：

import logging

import pandas as pd
from simpletransformers.t5 import T5Model, T5Args

logging.basicConfig(level=logging.INFO)
transformers_logger = logging.getLogger("transformers")
transformers_logger.setLevel(logging.WARNING)


train_data = [
    ["binary classification", "Anakin was Luke's father" , 1],
    ["binary classification", "Luke was a Sith Lord" , 0],
    ["generate question", "Star Wars is an American epic space-opera media franchise created by George Lucas, which began with the eponymous 1977 film and quickly became a worldwide pop-culture phenomenon", "Who created the Star Wars franchise?"],
    ["generate question", "Anakin was Luke's father" , "Who was Luke's father?"],
]
train_df = pd.DataFrame(train_data)
train_df.columns = ["prefix", "input_text", "target_text"]

eval_data = [
    ["binary classification", "Leia was Luke's sister" , 1],
    ["binary classification", "Han was a Sith Lord" , 0],
    ["generate question", "In 2020, the Star Wars franchise's total value was estimated at US$70 billion, and it is currently the fifth-highest-grossing media franchise of all time.", "What is the total value of the Star Wars franchise?"],
    ["generate question", "Leia was Luke's sister" , "Who was Luke's sister?"],
]
eval_df = pd.DataFrame(eval_data)
eval_df.columns = ["prefix", "input_text", "target_text"]

model_args = T5Args()
model_args.num_train_epochs = 200
model_args.no_save = True
model_args.evaluate_generated_text = False
model_args.evaluate_during_training = False
model_args.evaluate_during_training_verbose = False
model_args.use_multiprocessing = False
model_args.use_multiprocessing_for_evaluation = False

model = T5Model("t5", "t5-base", args=model_args)


def count_matches(labels, preds):
    print(labels)
    print(preds)
    return sum([1 if label == pred else 0 for label, pred in zip(labels, preds)])


model.train_model(train_df, show_running_loss=True)

我现在甚至没有使用eval_df (尽管我计划在我的真实代码中使用它)，因为它在他们的代码中没有正确设置。在这个非常简单的设置中，我认为这个库可以正常工作。但是，在两个系统(一个是Windows，一个是Linux，都是最新版本的SimpleTransformers)上尝试之后，我得到了以下错误：

  File "C:\Users\name\AppData\Local\Programs\Python\Python38\lib\site-packages\simpletransformers\t5\t5_utils.py", line 175, in <listcomp>       
    preprocess_data(d) for d in tqdm(data, disable=args.silent)
  File "C:\Users\name\AppData\Local\Programs\Python\Python38\lib\site-packages\simpletransformers\t5\t5_utils.py", line 81, in preprocess_data   
    batch = tokenizer.prepare_seq2seq_batch(
  File "C:\Users\name\AppData\Local\Programs\Python\Python38\lib\site-packages\transformers\tokenization_utils_base.py", line 3282, in prepare_seq2seq_batch
    labels = self(
  File "C:\Users\name\AppData\Local\Programs\Python\Python38\lib\site-packages\transformers\tokenization_utils_base.py", line 2262, in __call__  
    raise ValueError(
ValueError: text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).

我使用的是精确的设置，并且所有的输入DataFrames都有字符串。

有人能帮我找出这个基本设置失败的原因吗？谢谢。

Answer 1

在示例代码中，如果您更改

train_data = [
    ["binary classification", "Anakin was Luke's father" , 1],
    ["binary classification", "Luke was a Sith Lord" , 0],
    ["generate question", "Star Wars is an American epic space-opera media franchise created by George Lucas, which began with the eponymous 1977 film and quickly became a worldwide pop-culture phenomenon", "Who created the Star Wars franchise?"],
    ["generate question", "Anakin was Luke's father" , "Who was Luke's father?"],
]

至

train_data = [
    ["binary classification", "Anakin was Luke's father" , '1'],
    ["binary classification", "Luke was a Sith Lord" , '0'],
    ["generate question", "Star Wars is an American epic space-opera media franchise created by George Lucas, which began with the eponymous 1977 film and quickly became a worldwide pop-culture phenomenon", "Who created the Star Wars franchise?"],
    ["generate question", "Anakin was Luke's father" , "Who was Luke's father?"],
]

错误不再发生-所以它是由于标签不是str类型造成的。