finetune_config.yml

data:
  dataset_name: valid_consolidated
  from_hub: false
  from_langfuse: true
  input_file: input/executed/executed_filtered_valid_consolidated.jsonl
  num_proc: 2
  seed: 3407
  split: train
  test_size: 0.2
logging:
  file: finetune.log
model:
  adapter: null
  dtype: null
  load_in_4bit: true
  lora:
    alpha: 16
    bias: none
    dropout: 0
    gradient_checkpointing: unsloth
    loftq_config: null
    r: 16
    random_state: 3407
    target_modules:
    - q_proj
    - k_proj
    - v_proj
    - o_proj
    - gate_proj
    - up_proj
    - down_proj
    use_rslora: false
  max_seq_length: 2048
  name: Qwen/Qwen2.5-14B-Instruct
save:
  gguf_quantization:
  - q4_k_m
  - q8_0
  - q5_k_m
  hub_repo: joaormedeiros/qwen-2.5-recursive-v1
  local_dir: lora_model
  private: true
  push_to_hub: true
  save_mode: all_training_files
test_inference:
  enabled: true
  input: 1, 1, 2, 3, 5, 8
  instruction: Continue the fibonnaci sequence.
training:
  batch_size:
    eval: 2
    train: 4
  eval_steps: 100
  gradient_accumulation_steps: 4
  learning_rate: 0.0002
  logging_steps: 1
  lr_scheduler: linear
  num_epochs: 1
  optimizer: adamw_8bit
  output_dir: outputs
  report_to: tensorboard
  seed: 3407
  warmup_steps: 1
  weight_decay: 0.01