target_model:
  id: Nanthasit/sakthai-plus-1.5b
  pipeline_tag: text-generation
  library_name: transformers
  base_model: Qwen/Qwen2.5-1.5B-Instruct
  downloads: 244
  likes: 0
  private: false
  gated: false
  last_modified: "2026-07-31T11:09:05.000Z"
  model_age_days: 1.00
  model_type: llm
  has_weights: true

architecture:
  base_model_type: qwen2
  base_architectures: ["Qwen2ForCausalLM"]
  base_hidden_size: 1536
  base_num_hidden_layers: 28
  base_num_attention_heads: 12
  base_num_key_value_heads: 2
  base_intermediate_size: 8960
  base_vocab_size: 151936
  base_max_position_embeddings: 32768
  base_total_parameters: 1540000000
  base_dtype: bfloat16
  tie_word_embeddings: true

repo_summary:
  siblings_count: 20
  total_repo_bytes: 3098940902
  total_gb: 2.886
  has_weights: true
  weight_file_count: 1
  weight_bytes: 3087467144
  weight_files: ["model.safetensors"]
  config_present: true
  tokenizer_present: true
  chat_template_present: true
  readme_present: true
  readme_size_bytes: 18052
  weight_note: "Single merged full-weight checkpoint (2.88 GiB, bf16) — no PEFT dependency at inference. Standard Qwen2.5 layout: config.json, generation_config.json, tokenizer.json, tokenizer_config.json, chat_template.jinja, README.md."

benchmarks:
  model_index_count: 1
  metrics_count: 9
  all_verified: false
  pending_metrics: 8
  entries:
    - dataset: lighteval
      metric: winogrande
      value: 59.6
      verified: false
      note: "entry in .eval_results/lighteval.yaml — not re-run, unverified"
    - dataset: lighteval
      metric: gsm8k
      value: 50.9
      verified: false
      note: "entry in .eval_results/lighteval.yaml — not re-run, unverified"
    - dataset: lighteval
      metric: hellaswag
      value: 34.0
      verified: false
      note: "entry in .eval_results/lighteval.yaml — not re-run, unverified"
    - dataset: sakthai-bench-v2
      metric: selection_accuracy
      value: 84.8
      verified: false
      note: "entry in .eval_results/sakthai-bench-v2.yaml — not re-run, unverified"
    - dataset: sakthai-bench-v2
      metric: arguments_accuracy
      value: 33.7
      verified: false
      note: "entry in .eval_results/sakthai-bench-v2.yaml — not re-run, unverified"
    - dataset: sakthai-bench-v2
      metric: strict_accuracy
      value: 33.7
      verified: false
      note: "entry in .eval_results/sakthai-bench-v2.yaml — not re-run, unverified"
    - dataset: llama.cpp tool-calling (3-trial, q4_k_m)
      metric: tool_call_success
      value: 1.0
      verified: true
      note: ".eval_results/benchmark-20260731_043634.yaml — send_email prompt, 3/3 tool calls"
    - dataset: llama.cpp tool-calling (3-trial, q4_k_m)
      metric: valid_json
      value: 1.0
      verified: true
      note: ".eval_results/benchmark-20260731_043634.yaml — 3/3 valid JSON tool args"
    - dataset: llama.cpp tool-calling (3-trial, q4_k_m)
      metric: correct_answer
      value: 1.0
      verified: true
      note: ".eval_results/benchmark-20260731_043634.yaml — 3/3 correct answers, avg 20.7 tps (CPU, 2 threads)"
    - dataset: sakthai-bench-v2 (model-index)
      metric: tool_calling_accuracy
      value: 1.0
      verified: false
      note: "model-index entry: 'Tool Calling Accuracy (3/3)' from send_email scenario — single-trial, unverified"
  notes: >
    README frontmatter now includes a model-index entry (Tool Calling
    Accuracy 1.0 on send_email scenario, unverified). 3 additional unverified
    lighteval scores (winogrande 59.6, gsm8k 50.9, hellaswag 34.0) and
    3 sakthai-bench-v2 scores (selection 84.8, arguments 33.7, strict 33.7)
    exist in .eval_results/ but are NOT in the model-index. One verified
    3-trial llama.cpp q4_k_m tool-calling run (3/3, 20.7 tps) is present.
    Card text still says 'Benchmarks are pending' — stale relative to the
    10 metric entries across 3 evaluation sources.

training:
  dataset: Nanthasit/sakthai-combined-v10
  dataset_size: 2965
  dataset_note: "v7 + v8 combined (2,965 rows, published as sakthai-combined-v10; card also cites sakthai-combined-v7 at 2,309 rows)"
  training_method: "rsLoRA (rank-stabilized) merged to full weights via TRL SFTTrainer"
  eval_split: "5% held-out validation set (benchmarks pending confirmation)"
  lora_config:
    r: 16
    alpha: 32
    dropout: 0.05
    target_modules: [q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj]
  optimizer: "AdamW (8-bit)"
  learning_rate: 0.0002
  epochs: 3
  precision: bf16
  hardware: "Free T4 GPU (Kaggle / Colab / HF Inference), $0 budget"
  framework: "TRL + Transformers"
  key_improvements:
    - "rsLoRA instead of standard LoRA — better rank utilization"
    - "All 7 linear modules adapted (vs 4 in v1)"
    - "Dropout reduced 0.1 to 0.05"
    - "48% more training data (v7 + v8)"
    - "Merged full-weight checkpoint — no PEFT dependency at inference"

card_quality:
  license: apache-2.0
  base_model_documented: true
  base_model: Qwen/Qwen2.5-1.5B-Instruct
  tags_count: 19
  tags: [qwen2.5, sakthai, house-of-sak, tool-calling, function-calling, agent, instruct, finetuned, sft, rslora, text-generation, merged, conversational, assistant, safetensors, benchmark, eval-results, cpu-inference, rsLoRA]
  datasets_cited: ["Nanthasit/sakthai-combined-v7", "Nanthasit/sakthai-combined-v10"]
  model_index_present: true
  model_index_entries: 1
  model_index_note: "1 entry: Tool Calling Accuracy 1.0 (send_email scenario, unverified)"
  readme_size_bytes: 18052
  widget_example: "Tool-calling (email): Send an email to Beer with the subject 'Plus 1.5B status'"
  widget_present: true
  inference_config: true
  deductions:
    - "README states 'Benchmarks are pending' but .eval_results/ already carries 10 metric entries across 3 evaluation sources — card text lags repo state"
    - "model-index has only 1 of 10 available metrics — 9 unindexed, so they don't render on the Hub widget"
    - "lighteval scores (winogrande, gsm8k, hellaswag) and sakthai-bench-v2 scores all marked unverified — need multi-trial re-run"
  score: 85

health_score:
  overall: 64.2
  components:
    popularity: 2.4
    momentum: 100.0
    benchmarks: 50.0
    card_quality: 85.0
    repo_hygiene: 95.0
  weights:
    popularity: 0.20
    momentum: 0.20
    benchmarks: 0.25
    card_quality: 0.20
    repo_hygiene: 0.15

sibling_comparison:
  rank_by_downloads: 13
  total_author_models: 22
  max_sibling_downloads: 1855
  models_with_positive_downloads: 17
  velocity_rank: 3
  max_sibling_velocity: 330.4
  our_velocity: 244.0

eval_type: metadata_cron
eval_note: >
  Re-eval (run 27) for sakthai-plus-1.5b. Since first eval (18h ago):
  0 to 244 downloads (+244), velocity 244.0/day (3rd fastest among 19
  models). Health score improved from 38.2 to 64.2 (+26.0) driven by
  momentum (0 to 100) and card improvements (readme grew from 8,079 to
  18,052 bytes, model-index added, tags increased 12 to 19, widget added).
  Card still claims 'Benchmarks are pending' despite 10 metric entries in
  .eval_results/ — this is the most impactful improvement opportunity.
  Rank 13/22 by downloads (up from 12/19 as the ecosystem grew from 19 to
  22 resolved models). Next cycle: reconcile card text with .eval_results/
  state, run multi-trial sakthai-bench-v2, and expand model-index to all
  10 metrics.

eval_metadata:
  model: Nanthasit/sakthai-plus-1.5b
  eval_date: "2026-07-31"
  eval_time: "23:00:00Z"
  schema: llm_cron_v1
  age_days: 1.00
  days_since_last_update: 0.72
  download_velocity: 244.0
  cron_run: 27