Error while training my first HF model
I want to train my first Hugginface model.The code below generates the following error. What am I doing wrong?## imports

from datasets import Dataset
from sklearn.datasets import fetch_20newsgroups
from sklearn.model_selection import train_test_split
from transformers import (
    AutoTokenizer,
    AutoModelForSequenceClassification,
    Trainer,
    TrainingArguments,
)

## data
# Load 20-newsgroup dataset and arrange it into a list of tuples
# data = [("description1", "category1"), ("description2", "category2"), ...]

newsgroups_train = fetch_20newsgroups(subset="train")
data = [
    (
        newsgroups_train.data[i],
        newsgroups_train.target_names[newsgroups_train.target[i]],
    )
    for i in range(len(newsgroups_train.data))
]


## Prepare the dataset
descriptions = [item[0] for item in data]
categories = [item[1] for item in data]

# Tokenizer and Model
model_name = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(
    model_name, num_labels=len(set(categories))
)


## Encoding data
def encode(examples):
    return tokenizer(examples["text"], truncation=True, padding="max_length")


## Train/Test split
(
    train_descriptions,
    test_descriptions,
    train_categories,
    test_categories,
) = train_test_split(descriptions, categories, test_size=0.2)
training_args = TrainingArguments("test_trainer")

def hugginface_dataset(text, labels):
    return Dataset.from_dict(
        {
            "text": text,
            "labels": labels,
        }
    )


train_dataset = hugginface_dataset(train_descriptions, train_categories)
test_dataset = hugginface_dataset(test_descriptions, test_categories)


## Define trainer
trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=encode(train_dataset),
    eval_dataset=encode(test_dataset),
    # compute_metrics=compute_metrics,
)


## Train the model
trainer.train()