# Model Documentation Evaluation Template

# Metadata
model_name: "FastwebMIIA"
model_link: "https://huggingface.co/Fastweb/FastwebMIIA-7B"
organization: "Fastweb"
org_link: "https://www.fastweb.it/"
evaluation_date: "2026-07-22"
public_summary_link: "https://www.fastweb.it/grandi-aziende/artificial-intelligence/fastweb-miia/documentazione-trasparenza-ai/sintesi%20contenuti%20training.pdf"
public_summary_date: "2026-03-23"
public_summary_location: "https://www.fastweb.it/"
model_publication_date: "2026-03-23"
category: "New model" # New model, fine-tuned model
archive_file_name: "Sintesi_2026_07_22.pdf"

# Requirement assessments
# Each requirement should be assessed once with a score from 0-10
# Leave blank for N/A, and assign a max score of 0
S1: # Document-level requirements
  D1: # Clarity
    score: 8
    max_score: 11
    notes: ""

  D2: # Completeness
    score: 1
    max_score: 4
    notes: ""

  D3: # Consistency
    score: 7
    max_score: 7
    notes: ""

  D4: # Correctness
    score: 4
    max_score: 5
    notes: ""

  D5: # Accessibility
    score: 7
    max_score: 10
    notes: ""

  D6: # Comprehension
    score: 6
    max_score: 9
    notes: ""

S2: # General information
  D1: # Clarity
    score: 25
    max_score: 39
    notes: ""

  D2: # Completeness
    score: 48
    max_score: 67
    notes: ""

  D3: # Consistency
    score: 8
    max_score: 8
    notes: ""

  D4: # Correctness
    score: 19
    max_score: 21
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 0
    notes: ""

  D6: # Comprehension
    score: 10
    max_score: 11
    notes: ""

S3: # Public datasets
  D1: # Clarity
    score: 0
    max_score: 92
    notes: ""

  D2: # Completeness
    score: 48
    max_score: 140
    notes: ""

  D3: # Consistency
    score: 3
    max_score: 3
    notes: ""

  D4: # Correctness
    score: 16
    max_score: 20
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 20
    notes: ""

  D6: # Comprehension
    score: 16
    max_score: 16
    notes: ""

S4: # Private datasets
  D1: # Clarity
    score: 16
    max_score: 72
    notes: ""

  D2: # Completeness
    score: 36
    max_score: 88
    notes: ""

  D3: # Consistency
    score: 3
    max_score: 3
    notes: ""

  D4: # Correctness
    score: 40
    max_score: 44
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 20
    notes: ""

  D6: # Comprehension
    score: 16
    max_score: 16
    notes: ""

S5: # Scraped/crawled data
  D1: # Clarity
    score: 0
    max_score: 0
    notes: ""

  D2: # Completeness
    score: 0
    max_score: 3
    notes: ""

  D3: # Consistency
    score: 3
    max_score: 3
    notes: ""

  D4: # Correctness
    score: 0
    max_score: 3
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 0
    notes: ""

  D6: # Comprehension
    score: 0
    max_score: 0
    notes: ""

S6: # User data
  D1: # Clarity
    score: 0
    max_score: 0
    notes: ""

  D2: # Completeness
    score: 8
    max_score: 8
    notes: ""

  D3: # Consistency
    score: 3
    max_score: 3
    notes: ""

  D4: # Correctness
    score: 8
    max_score: 8
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 0
    notes: ""

  D6: # Comprehension
    score: 0
    max_score: 0
    notes: ""

S7: # Synthetic & other
  D1: # Clarity
    score: 0
    max_score: 36
    notes: ""

  D2: # Completeness
    score: 15
    max_score: 30
    notes: ""

  D3: # Consistency
    score: 6
    max_score: 6
    notes: ""

  D4: # Correctness
    score: 15
    max_score: 18
    notes: ""

  D5: # Accessibility
    score: 0
    max_score: 0
    notes: ""

  D6: # Comprehension
    score: 6
    max_score: 12
    notes: ""

S8: # Data processing
  D1: # Clarity
    score: 18
    max_score: 18
    notes: ""

  D2: # Completeness
    score: 15
    max_score: 18
    notes: ""

  D3: # Consistency
    score: 3
    max_score: 3
    notes: ""

  D4: # Correctness
    score: 33
    max_score: 36
    notes: ""

  D5: # Accessibility
    score: 15
    max_score: 15
    notes: ""

  D6: # Comprehension
    score: 69
    max_score: 69
    notes: ""


general_notes: "The public summary for the FastwebMIIA models can be found <a href=\"https://www.fastweb.it/grandi-aziende/artificial-intelligence/fastweb-miia/documentazione-trasparenza-ai/sintesi%20contenuti%20training.pdf\" target=\"_blank\"> on Fastweb's site</a>. The summary very approximately matches the structure of the template, and is provided in Italian. Several fields are missing or consolidated, causing significant loss of transparency. The summary indicates dataset as crawlers, causing further loss of scores. For the rest, the template provides a summary for which good-faith is evident and which describes data processing in detail. We assessed its score to be <span class=\"openness partial\">50.06%</span> with Grade <strong>C</strong> for <strong><i>transparency</i></strong>, and <span class=\"openness open\">73.23%</span> with Grade <strong>C+</strong> for <strong><i>usefulness</i></strong>."