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Deep Learning Practice Quiz 1: 13 July 2025 (May 2025 term)

Question 1

+2 marksOne correct option

A start-up is building a new language model for a low-resource language with many compound words and complex morphology. They are debating tokenization strategies. Which of the following approaches is most likely to offer the best balance between vocabulary size, handling OOV words, and capturing morphological variants effectively for this scenario?

  1. A

    Character-level tokenization

  2. B

    Word-level tokenization with a fixed vocabulary of 50,000 common words.

  3. C

    Subword tokenization (e.g., BPE or SentencePiece) trained on the available corpus.

  4. D

    Using only pre-defined special tokens and treating all other text as raw byte sequences.

Question 2

+2 marksOne correct option

When fully fine-tuning a large pre-trained Transformer model (e.g., >1 Billion parameters), which of the following contributes LEAST significantly to the GPU memory bottleneck compared to the others?

  1. A

    Storing the model parameters themselves.

  2. B

    Storing the gradients for each parameter.

  3. C

    Storing the optimizer states (e.g., momentum and variance for Adam).

  4. D

    Storing the input batch data (token IDs).

Question 3

+2 marksOne correct option

A research team wants their pre-trained language model to generate more helpful and harmless responses without extensive task-specific dataset collection. They have a collection of prompts and human-preferred responses. Which of the following techniques directly aligns with this goal and data?

  1. A

    Pre-training the model on a larger, more diverse text corpus.

  2. B

    Full fine-tuning on multiple downstream classification tasks.

  3. C

    Instruction Tuning using prompt-completion pairs or reformatting existing datasets into an instructional format.

  4. D

    Implementing Parameter-Efficient Fine-Tuning (PEFT) techniques like LoRa.

13 more questions in this paper

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More on the Deep Learning Practice Quiz 1 13 Jul 2025 paper

The IIT Madras BS Deep Learning Practice (Deep Learning Practice) Quiz 1 paper sat on 13 Jul 2025, in the May 2025 term: 16 questions for 50 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

FeatureDeep Learning Practice Quiz 1 13 Jul 2025 at a glance
TermMay 2025 term
SubjectDeep Learning Practice
Course codeBSDA5013
Questions16
Marks50
Duration120 min
MCQ8
MSQ3
Numerical5
Official paperIIT M DEGREE AN EXAM QDB2 13 July 2025
Negative markingNo negative marking.
Updated

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