🐛 Bug

Information

Model I am using TFBertForSequenceClassification

Language I am using the model on: English

The problem arises when using:

• the official example scripts: (give details below)

The tasks I am working on is:

• my own task or dataset: (give details below) To classify text and learn the model and package.

To reproduce

Steps to reproduce the behavior:

1. pip install transformers (currently 2.11.0)
2. run default code on website: https://huggingface.co/transformers/model_doc/bert.html#tfbertforsequenceclassification
3. I tried to follow this: https://github.com/huggingface/transformers/issues/4848; and the issue remains the same.

import tensorflow as tf
from transformers import BertTokenizer, TFBertForSequenceClassification

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = TFBertForSequenceClassification.from_pretrained('bert-base-uncased')
input_ids = tf.constant(tokenizer.encode("Hello, my dog is cute"))[None, :]  # Batch size 1
labels = tf.reshape(tf.constant(1), (-1, 1)) # Batch size 1
outputs = model(input_ids, labels=labels)
loss, logits = outputs[:2]

Environment info

• transformers version: 2.11.0
• Platform: Windows-10-10.0.18362-SP0
• Python version: 3.7.7
• PyTorch version (GPU?): not installed (NA)
• Tensorflow version (GPU?): 2.2.0 (True)
• Using GPU in script?: Yes
• Using distributed or parallel set-up in script?: No