I’m trying out this Hugging Face tutorial

I’m trying to use a trainer to train my mode. The code errors out at this point:

from datasets import load_dataset
from transformers import AutoTokenizer, AutoModelForSequenceClassification, DataCollatorWithPadding, TrainingArguments, Trainer

checkpoint = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
raw_datasets = load_dataset("glue", "mrpc")

def tokenize_function(example):
    return tokenizer(example["sentence1"], example["sentence2"], truncation=True)

tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)

data_collator = DataCollatorWithPadding(tokenizer=tokenizer)

training_args = TrainingArguments("test-trainer")

model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=2)

#The above code works upto here
#The following line fails
trainer = Trainer(
    model,
    training_args,
    train_dataset=tokenized_datasets["train"],
    eval_dataset=tokenized_datasets["validation"], 
    tokenizer=tokenizer,
)

The error is displayed as:

File "tutorial.py", line 21, in <module>
    trainer = Trainer(
              ^^^^^^^^
  File "/opt/miniconda3/envs/py3env/lib/python3.12/site-packages/transformers/trainer.py", line 388, in __init__
    self.create_accelerator_and_postprocess()
  File "/opt/miniconda3/envs/py3env/lib/python3.12/site-packages/transformers/trainer.py", line 4364, in create_accelerator_and_postprocess
    self.accelerator = Accelerator(**args)
                       ^^^^^^^^^^^^^^^^^^^
TypeError: Accelerator.__init__() got an unexpected keyword argument 'use_seedable_sampler'

Versions:

Python: 3.12.3
Transformer: 4.40.2
Datasets: 2.19.1
Accelerate: 0.21.0

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