# Sebeni MasterConfig example (Bambara / GRPO)
# Docs: https://seben.robotsmali.org/docs/hyperparams/

project_name: sebeni-bam-grpo
algorithm: grpo
# working_dir: ./runs/bam-grpo-001   # or /mnt/scratch/sebeni; CLI -w wins

model:
  model_name: HuggingFaceTB/SmolLM2-135M
  load_in_4bit: true
  use_peft: true
  lora_r: 16
  lora_alpha: 32
  lora_dropout: 0.1

data:
  default_lang: bam
  languages: [bam]
  source: null
  scheme: completion

trainer:
  framework: torch
  learning_rate: 5.0e-6
  per_device_train_batch_size: 2
  gradient_accumulation_steps: 8
  max_steps: 10
  num_train_epochs: 1.0
  beta: 0.1
  num_generations: 4
  temperature: 0.9
  warmup_ratio: 0.0
  weight_decay: 0.0
  lr_scheduler_type: cosine
  seed: 42
  bf16: false
  gradient_checkpointing: false
  use_cpu: false

distillation:
  enabled: true
  backend: algorithmic
  model: gemini-2.5-flash
  tau: 0.5
  hitl: false

reward:
  format_weight: 0.1
  morph_weight: 0.4
  rule_weight: 0.4
  lang_weight: 0.1

safety:
  enabled: true
