1Z0-1127-25 OCI Generative AI Service Practice Question
During fine-tuning, a user notices the loss does not decrease after several epochs. The dataset is a JSONL file with 500 prompt/completion pairs. What is the MOST likely cause?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The dataset is too small; T-Few fine-tuning generally needs at least 1000 examples
Fine-tuning with T-Few typically requires at least 1000 examples for meaningful learning. The dataset size is likely insufficient.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The JSONL format is incorrect because it lacks system prompts
Why it's wrong here
System prompts are optional; the format requires prompt/completion pairs, which the user has.
- ✗
The base model is not compatible with the T-Few technique
Why it's wrong here
T-Few is supported for compatible models like Command R; incompatibility would cause errors, not just no loss decrease.
- ✓
The dataset is too small; T-Few fine-tuning generally needs at least 1000 examples
Why this is correct
T-Few is efficient but still requires a minimum dataset size to learn effectively.
- ✗
The learning rate is too high, causing the model to diverge
Why it's wrong here
While possible, the most common issue with small datasets is insufficient data, not hyperparameters.
Go deeper
Related to this question
About these practice questions
This 1Z0-1127-25 question is part of Courseiva's 768-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This 1Z0-1127-25 practice question is part of Courseiva's free Oracle certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 1Z0-1127-25 exam.