Metrieken voor taal­taken: perplexity en BLEU

Introductie tot LLM’s in Python

Jasmin Ludolf

Senior Data Science Content Developer, DataCamp

LLM‑taken en metrieken

 

Evaluatiemetrieken voor taaltaken

Introductie tot LLM’s in Python

Perplexity

  • Vermogen van een model om het volgende woord nauwkeurig en zeker te voorspellen
  • Lagere perplexity = hogere zekerheid
input_text = "Latest research findings in Antarctica show"

generated_text = "Latest research findings in Antarctica show that the ice sheet 
is melting faster than previously thought."


# Encode the prompt, generate text and decode it
input_text_ids = tokenizer.encode(input_text, return_tensors="pt")
output = model.generate(input_text_ids, max_length=20)
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
Introductie tot LLM’s in Python

Perplexity‑output

perplexity = evaluate.load("perplexity", module_type="metric")
results = perplexity.compute(predictions=generated_text, model_id="gpt2")

print(results)

{'perplexities': [245.63299560546875, 520.3106079101562, ....], 
 'mean_perplexity': 2867.7229790460497}

print(results["mean_perplexity"])

2867.7229790460497
  • Vergelijk met baseline‑resultaten
Introductie tot LLM’s in Python

BLEU

  • Meet vertaal­kwaliteit t.o.v. menselijke referenties

  • Predictions: outputs van het LLM

  • References: menselijke referenties
bleu = evaluate.load("bleu")


input_text = "Latest research findings in Antarctica show"
references = [["Latest research findings in Antarctica show significant ice loss due to 
               climate change.", "Latest research findings in Antarctica show that the ice 
               sheet is melting faster than previously thought."]]
generated_text = "Latest research findings in Antarctica show that the ice sheet is melting 
               faster than previously thought."
Introductie tot LLM’s in Python

BLEU‑output

results = bleu.compute(predictions=[generated_text], references=references)
print(results)

{'bleu': 1.0, 
 'precisions': [1.0, 1.0, 1.0, 1.0], 
 'brevity_penalty': 1.0, 
 'length_ratio': 1.2142857142857142, 
 'translation_length': 17, 
 'reference_length': 14}
  • Score 0‑1: dichter bij 1 = hogere overeenkomst
Introductie tot LLM’s in Python

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Introductie tot LLM’s in Python

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