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Batch Size for Sequential Data in A2C Value Loss
When calculating the value network loss in the Advantage Actor-Critic (A2C) algorithm for sequential data, the number of training samples, M, can be equated to the length of the sequence. For instance, if the input is a sequence containing T tokens, the batch size M can be set to T.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Batch Size for Sequential Data in A2C Value Loss
An agent is being trained using a reinforcement learning algorithm where the value network's loss is based on the mean squared temporal difference (TD) error. For a single transition, the agent moves from state
s_ttos_{t+1}, receiving a rewardr_t. The value network predicts the value of the current state asV(s_t)and the next state asV(s_{t+1}). Given the following values, calculate the squared TD error, which represents the loss for this single sample before averaging:- Reward
r_t= 2 - Discount factor
γ= 0.9 - Predicted value of current state
V(s_t)= 5.0 - Predicted value of next state
V(s_{t+1})= 4.0
- Reward
An agent is being trained using an algorithm where the value network's performance is measured by the mean squared difference between its predicted value for a state,
V(s_t), and a computed target value,r_t + γ * V(s_{t+1}). During a particular training batch, the network consistently produces predictionsV(s_t)that are significantly lower than the computed target values. What is the most direct effect on the network's parameters during the subsequent optimization step?Rationale for the Value Network Target
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An engineer is training a reinforcement learning agent to process text. The agent receives a single sequence of 64 tokens as input. To update its value network, the engineer calculates the squared temporal difference error for each of the 64 token-processing steps. The final loss is the average of these 64 squared errors. In the formula for the average, what number should the sum of the squared errors be divided by?
A2C Value Loss for Variable-Length Sequences
Value Loss Calculation for a Single Sequence