# Model Documentation Evaluation Template

# Metadata
model_name: "SmolLM3-3B"
model_link: "https://huggingface.co/HuggingFaceTB/SmolLM3-3B"
organization: "HuggingFace"
org_link: "https://huggingface.co/HuggingFaceTB"
evaluation_date: "2026-03-31"
public_summary_link: "https://huggingface.co/spaces/hfmlsoc/smollm3-eu-data-transparency"
public_summary_date: "2025-07-25"
public_summary_location: "https://huggingface.co/hfmlsoc/spaces"
model_publication_date: "2025-07-08"
category: "Fine-tuned model" # New model, fine-tuned model
archive_file_name: "SmolLM_33B_2025_11_12.pdf"
previous_versions:
  - "2026-01-12"

# 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: 7.5
    max_score: 11
    notes: "Document should have the correct structure, and be in a well-defined, structured, and interoperable format.<br/><br/>Document should clearly indicate whether it is the latest version or if it is outdated and a replacement is made available.<br/><br/>Document should provide link to all versions of the document."

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

  D3: # Consistency
    score: 5.5
    max_score: 8
    notes: "Document should be consistent across versions. Each document version should have a unique version number."

  D4: # Correctness
    score: 3
    max_score: 6
    notes: "Document should have assured integrity and provide a link to the authoritative source of the document. The date of last update should be correct and accurate."

  D5: # Accessibility
    score: 8.5
    max_score: 13
    notes: "Document must be easy to find, support sharing and exporting, and be provided in the same context as the model."

  D6: # Comprehension
    score: 6
    max_score: 12
    notes: "Document should clearly indicate changes from previous version, or otherwise where notice of updates or changes will be provided. Links to previous versions should be accessible for intended stakeholders."

S2: # General information
  D1: # Clarity
    score: 21
    max_score: 40
    notes: ""

  D2: # Completeness
    score: 54
    max_score: 65
    notes: ""

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

  D4: # Correctness
    score: 17
    max_score: 23
    notes: ""

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

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

S3: # Public datasets
  D1: # Clarity
    score: 44
    max_score: 52
    notes: ""

  D2: # Completeness
    score: 108
    max_score: 108
    notes: ""

  D3: # Consistency
    score: 23
    max_score: 23
    notes: ""

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

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

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

S4: # Private datasets
  D1: # Clarity
    score: 0
    max_score: 0
    notes: ""

  D2: # Completeness
    score: 2
    max_score: 2
    notes: ""

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

  D4: # Correctness
    score: 2
    max_score: 2
    notes: ""

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

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

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

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

  D3: # Consistency
    score: 0
    max_score: 0
    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: 0
    max_score: 0
    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: 25
    max_score: 37
    notes: ""

  D2: # Completeness
    score: 19
    max_score: 31
    notes: ""

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

  D4: # Correctness
    score: 13
    max_score: 31
    notes: ""

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

  D6: # Comprehension
    score: 0
    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 HuggingFace's SmolLM3-3B model is available on its platform as a <a href=\"https://huggingface.co/spaces/hfmlsoc/smollm3-eu-data-transparency\" target=\"_blank\">webpage</a>. In general, the structure of the template was preserved with clear indication of section numbers, consistent field labels, and explicitly indicating yes/no where applicable. Other than issues with accessibility, we found no major issues with the public summary. It scored <span class=\"openness open\">82.50%</span> and received a grade of <strong>B+</strong> for <strong><i>Transparency</i></strong>, and <span class=\"openness open\">86.01%</span> with grade <strong>B+</strong> for <strong><i>Usefulness</i></strong>, which meant that the summary was of a moderate but good quality. SmolLM scored particularly well on its disclosure of public data sources, a key disclosure demanded by Article 53(1)(d), and a good indicator of transparency in the model development process."