TypeError: __init__() got an unexpected keyword argument 'evaluate_during_training'
I got this error while training. I have used Seq2SeqTrainingArguments class from transformers:


```
import logging
from dataclasses import dataclass, field
from typing import Optional

from seq2seq_trainer import arg_to_scheduler
from transformers import TrainingArguments


logger = logging.getLogger(__name__)


@dataclass
class Seq2SeqTrainingArguments(TrainingArguments):
    """
    Parameters:
        label_smoothing (:obj:`float`, `optional`, defaults to 0):
            The label smoothing epsilon to apply (if not zero).
        sortish_sampler (:obj:`bool`, `optional`, defaults to :obj:`False`):
            Whether to SortishSamler or not. It sorts the inputs according to lenghts in-order to minimizing the padding size.
        predict_with_generate (:obj:`bool`, `optional`, defaults to :obj:`False`):
            Whether to use generate to calculate generative metrics (ROUGE, BLEU).
    """

    label_smoothing: Optional[float] = field(
        default=0.0, metadata={"help": "The label smoothing epsilon to apply (if not zero)."}
    )
    sortish_sampler: bool = field(default=False, metadata={"help": "Whether to SortishSamler or not."})
    predict_with_generate: bool = field(
        default=False, metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}
    )
    adafactor: bool = field(default=False, metadata={"help": "whether to use adafactor"})
    encoder_layerdrop: Optional[float] = field(
        default=None, metadata={"help": "Encoder layer dropout probability. Goes into model.config."}
    )
    decoder_layerdrop: Optional[float] = field(
        default=None, metadata={"help": "Decoder layer dropout probability. Goes into model.config."}
    )
    dropout: Optional[float] = field(default=None, metadata={"help": "Dropout probability. Goes into model.config."})
    attention_dropout: Optional[float] = field(
        default=None, metadata={"help": "Attention dropout probability. Goes into model.config."}
    )
    lr_scheduler: Optional[str] = field(
        default="linear",
        metadata={"help": f"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys())}"},
    )

```
When i pass the arguments in this method:

```
training_args = Seq2SeqTrainingArguments(
    output_dir="./",
    per_device_train_batch_size=batch_size,
    per_device_eval_batch_size=batch_size,
    predict_with_generate=True,
    evaluate_during_training=True,
    do_train=True,
    do_eval=True,
    logging_steps=2,  
    save_steps=16, 
    eval_steps=500, 
    warmup_steps=500,  
    #max_steps=1500, # delete for full training
    overwrite_output_dir=True,
    save_total_limit=1,
    fp16=True, 
)

# instantiate trainer
trainer = Seq2SeqTrainer(
    model=roberta_shared,
    args=training_args,
    compute_metrics=compute_metrics,
    train_dataset=train_data,
    eval_dataset=val_data,
)
trainer.train()
````
Error:

TypeError: __init__() got an unexpected keyword argument 'evaluate_during_training'

I don't know what i am doing wrong
As the error mentions, there is no `evaluate_during_training` argument. I have no idea where you found it.
You can find the list of arguments of this class in the [documentation](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments).<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.