UltraFeedback¶
Rank generations focusing on different aspects using an LLM
.
UltraFeedback: Boosting Language Models with High-quality Feedback.
Attributes¶
- aspect: The aspect to perform with the
UltraFeedback
model. The available aspects are: -helpfulness
: Evaluate text outputs based on helpfulness. -honesty
: Evaluate text outputs based on honesty. -instruction-following
: Evaluate text outputs based on given instructions. -truthfulness
: Evaluate text outputs based on truthfulness. Additionally, a custom aspect has been defined by Argilla, so as to evaluate the overall assessment of the text outputs within a single prompt. The custom aspect is: -overall-rating
: Evaluate text outputs based on an overall assessment.
Input & Output Columns¶
graph TD
subgraph Dataset
subgraph Columns
ICOL0[instruction]
ICOL1[generations]
end
subgraph New columns
OCOL0[ratings]
OCOL1[rationales]
OCOL2[model_name]
end
end
subgraph UltraFeedback
StepInput[Input Columns: instruction, generations]
StepOutput[Output Columns: ratings, rationales, model_name]
end
ICOL0 --> StepInput
ICOL1 --> StepInput
StepOutput --> OCOL0
StepOutput --> OCOL1
StepOutput --> OCOL2
StepInput --> StepOutput
Inputs¶
-
instruction (
str
): The reference instruction to evaluate the text outputs. -
generations (
List[str]
): The text outputs to evaluate for the given instruction.
Outputs¶
-
ratings (
List[float]
): The ratings for each of the provided text outputs. -
rationales (
List[str]
): The rationales for each of the provided text outputs. -
model_name (
str
): The name of the model used to generate the ratings and rationales.