Setting up the reward trainer
Your project continues and you now have the model and config objects ready to start training the reward model.
The training and evaluation datasets have been preloaded as train_data and eval_data. The RewardTrainer has been imported from trl.
Cet exercice fait partie du cours
Reinforcement Learning from Human Feedback (RLHF)
Instructions
- Initialize the
RewardTrainer()by assigning the model, tokenizer, training dataset, evaluation dataset, and reward configuration to its attributes.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
tokenizer = AutoTokenizer.from_pretrained("openai-gpt")
model = AutoModelForSequenceClassification.from_pretrained('openai-gpt')
config = RewardConfig(output_dir='output_dir', max_length=60)
# Initialize the reward trainer
trainer = ____