# Model Documentation Evaluation Template

# Metadata
model_name: "FIBO"
model_link: "https://huggingface.co/briaai/FIBO"
organization: "Bria AI"
org_link: "https://bria.ai/"
evaluation_date: "2026-08-04"
public_summary_link: "https://drive.google.com/file/d/1z3JFPBQCRKdj5F-Qfgp4TaNITWcMZtOi/view" 
public_summary_date: "2026-08-02"
public_summary_location: "https://bria.ai/security-and-compliance"
model_publication_date: "2026-03-30"
category: "New model" # New model, fine-tuned model
archive_file_name: "FIBO_2026_08_03.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: 10
    max_score: 11
    notes: ""

  D2: # Completeness
    score: 4
    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: 8
    max_score: 9
    notes: ""

S2: # General information
  D1: # Clarity
    score: 38
    max_score: 48
    notes: ""

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

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

  D4: # Correctness
    score: 27
    max_score: 27
    notes: ""

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

  D6: # Comprehension
    score: 14
    max_score: 14
    notes: ""

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

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

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

  D4: # Correctness
    score: 1
    max_score: 1
    notes: ""

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

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

S4: # Private datasets
  D1: # Clarity
    score: 32
    max_score: 32
    notes: ""

  D2: # Completeness
    score: 37
    max_score: 85
    notes: ""

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

  D4: # Correctness
    score: 18
    max_score: 21
    notes: ""

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

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

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

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

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

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

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

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

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

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

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

S8: # Data processing
  D1: # Clarity
    score: 19
    max_score: 19
    notes: ""

  D2: # Completeness
    score: 19
    max_score: 19
    notes: ""

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

  D4: # Correctness
    score: 37
    max_score: 37
    notes: ""

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

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


general_notes: "The training data summary for FIBO provides an excellent summary for a model trained entirely on licensed data. The summary adheres to the structure of the template, and provides information to the requisite level of detail. Points are lost primarily due to the general description of non-publicly known private datasets obtained from third parties not going into the levels of detail encouraged by the template. The summary scores <span class=\"openness open\">87.01%</span> with a grade of <strong>B+</strong> for <i>transparency</i>, and <span class=\"openness open\">97.2%</span> with a grade of <strong>A+</strong> for <i>usefulness</i>."