TypeError: 'bool' object is not callable

I’m training BART summarization model - following as per the documentation example. But I’m getting above mentioned error. Am I doing something wrong?

model_args = {
    "reprocess_input_data": True,
    "overwrite_output_dir": True,
    "max_seq_length": 128,
    "train_batch_size": 2,
    "num_train_epochs": 10,
    "save_eval_checkpoints": False,
    "save_model_every_epoch": False,
    "evaluate_during_training": True,
    "evaluate_generated_text": True,
    "evaluate_during_training_verbose": True,
    "use_multiprocessing": False,
    "max_length": 50,
    "manual_seed": 4,
}

from simpletransformers.seq2seq import Seq2SeqModel
 model = Seq2SeqModel(
    encoder_decoder_type="bart",
    encoder_decoder_name="facebook/bart-large",
    args=model_args,
)

model.train_model(train_df[:100], eval_data=eval_df[:100], use_cuda=True)

Error Trace

TypeError                                 
Traceback (most recent call last)
<ipython-input-16-724cb9663289> in <module>
      9 
     10 # Train the model
---> 11 model.train_model(train_df[:100], eval_data=eval_df[:100], use_cuda=True)

/opt/conda/lib/python3.7/site-packages/simpletransformers/seq2seq/seq2seq_model.py in train_model(self, train_data, output_dir, show_running_loss, args, eval_data, verbose, **kwargs)
    284             eval_data=eval_data,
    285             verbose=verbose,
--> 286             **kwargs,
    287         )
    288 

/opt/conda/lib/python3.7/site-packages/simpletransformers/seq2seq/seq2seq_model.py in train(self, train_dataset, output_dir, show_running_loss, eval_data, verbose, **kwargs)
    623                     verbose=verbose and args.evaluate_during_training_verbose,
    624                     silent=args.evaluate_during_training_silent,
--> 625                     **kwargs,
    626                 )
    627 

/opt/conda/lib/python3.7/site-packages/simpletransformers/seq2seq/seq2seq_model.py in eval_model(self, eval_data, output_dir, verbose, silent, **kwargs)
    719             preds = self.predict(to_predict)
    720 
--> 721             result = self.compute_metrics(eval_data["target_text"].tolist(), preds, **kwargs)
    722             self.results.update(result)
    723 

/opt/conda/lib/python3.7/site-packages/simpletransformers/seq2seq/seq2seq_model.py in compute_metrics(self, labels, preds, **kwargs)
    876         results = {}
    877         for metric, func in kwargs.items():
--> 878             results[metric] = func(labels, preds)
    879 
    880         return results

TypeError: 'bool' object is not callable

[ThilinaRajapakse]

Yeah, you can train a T5 model with any custom prefix. If you are doing a task that it has already been trained on, it might be best to use the original prefix though. For example, T5 is already trained for summarization. You can look at the paper (or the blog) for more details.

[ThilinaRajapakse]

use_cuda=True should be passed when creating the model, not to train_model.

E.g.

model = Seq2SeqModel(
    encoder_decoder_type="bart",
    encoder_decoder_name="facebook/bart-large",
    args=model_args,
    use_cuda=True
)

model.train_model(train_df[:100], eval_data=eval_df[:100])