How to get embeddings from Finetuned BERT classification model?
So I have the code below which finetunes the BERT model for sequence classification. How can I get the finetuned embeddings? I know how to get the pre-trained embeddings but here I want the embeddings AFTER finetuning.from transformers import TFDistilBertForSequenceClassification, TFTrainer, TFTrainingArguments

training_args = TFTrainingArguments(
    output_dir='./results',          # output directory
    num_train_epochs=3,              # total number of training epochs
    per_device_train_batch_size=16,  # batch size per device during training
    per_device_eval_batch_size=64,   # batch size for evaluation
    warmup_steps=500,                # number of warmup steps for learning rate scheduler
    weight_decay=0.01,               # strength of weight decay
    logging_dir='./logs',            # directory for storing logs
    logging_steps=10,
    eval_steps = 10,
)

with training_args.strategy.scope():
    model = TFDistilBertForSequenceClassification.from_pretrained("distilbert-base-uncased")

trainer = TFTrainer(
    model=model,                         # the instantiated 🤗 Transformers model to be trained
    args=training_args,                  # training arguments, defined above
    train_dataset=train_dataset,         # training dataset
    eval_dataset=val_dataset,
    compute_metrics=compute_metrics
)

trainer.train()