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Menu iconMenu iconNLP with Transformers: Fundamentals and Core Applications
NLP with Transformers: Fundamentals and Core Applications

Project 1: Sentiment Analysis with BERT

8. Step 5: Evaluating the Model

After training, we’ll evaluate the model on the test set to assess its accuracy.

Code Example: Evaluation

# Evaluate the model
results = trainer.evaluate()
print(f"Evaluation Results: {results}")

8. Step 5: Evaluating the Model

After training, we’ll evaluate the model on the test set to assess its accuracy.

Code Example: Evaluation

# Evaluate the model
results = trainer.evaluate()
print(f"Evaluation Results: {results}")

8. Step 5: Evaluating the Model

After training, we’ll evaluate the model on the test set to assess its accuracy.

Code Example: Evaluation

# Evaluate the model
results = trainer.evaluate()
print(f"Evaluation Results: {results}")

8. Step 5: Evaluating the Model

After training, we’ll evaluate the model on the test set to assess its accuracy.

Code Example: Evaluation

# Evaluate the model
results = trainer.evaluate()
print(f"Evaluation Results: {results}")