atropos/environments/letter_counting_environment/config.yaml
2026-01-02 14:10:02 +00:00

72 lines
2.4 KiB
YAML

# Tinker-Atropos Configuration - Letter Counting Environment
# This environment uses adaptive difficulty (curriculum learning) with 10 tiers
# Evaluation uses static dataset from HuggingFace: NousResearch/Letter-Counting-Eval
# Environment configuration
env:
# Base environment config
group_size: 8
batch_size: 256
max_batches_offpolicy: 3
tokenizer_name: "Qwen/Qwen3-8B"
use_wandb: true
rollout_server_url: "http://localhost:8000"
wandb_name: "letter-counting-env"
ensure_scores_are_not_same: true
max_token_length: 8192
max_num_workers: 24
worker_timeout: 3600 # 1 hour - needed for high difficulty levels
total_steps: 5000
steps_per_eval: 5
inference_weight: 1.0
data_path_to_save_groups: null
eval_limit_ratio: 0.1
# Generation configuration
generation_temperature: 1.0
eval_temperature: 0.6
max_generation_tokens: 15360
# Training filtering (CRITICAL for stable training):
# - Groups with >80% success rate are SKIPPED (too easy, no learning signal)
# - Groups with <20% success rate are SKIPPED (too hard, no learning signal)
# - Groups with all identical scores are SKIPPED (no variance)
difficulty_window_size: 150 # Number of recent groups to track (larger = more stable)
difficulty_increase_threshold: 0.8 # Increase difficulty if success rate > this (also skip group)
difficulty_decrease_threshold: 0.2 # Decrease difficulty if success rate < this (also skip group)
min_difficulty_level: 1 # Minimum difficulty (1 = easiest)
max_difficulty_level: 10 # Maximum difficulty (10 = 500 chars, 50 letters)
starting_difficulty_level: 4 # Start at medium difficulty
# Logging configuration
debug_logging: true
suppress_base_env_logs: true
# Data dumping configuration (for creating offline training datasets)
dump_rollouts: false
dump_batch_size: 100
# OpenAI-compatible server configuration
openai:
- model_name: "Qwen/Qwen3-8B"
base_url: "http://localhost:8001/v1"
api_key: "x"
weight: 1.0
num_requests_for_eval: 256
# Tinker-specific example configuration
tinker:
lora_rank: 32
learning_rate: 0.00004
max_token_trainer_length: 16864
checkpoint_dir: "./temp/"
save_checkpoint_interval: 0
# Wandb configuration for trainer
wandb_project: "tinker-letter-counting"
wandb_group: null
wandb_run_name: "tinker-letter-counting-run"
# Standard Atropos flags
slurm: false
testing: false