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finetune_config.yml

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+data:
+  dataset_name: manual_plus_executed_prompt_variance
+  from_langfuse: true
+  method: sft
+  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/Qwen2.5-7B-Instruct
+save:
+  gguf_quantization:
+  - q4_k_m
+  - q8_0
+  - q5_k_m
+  hub_repo: joaormedeiros/qwen-2.5-lite-recursive-v5-rules-iter-1
+  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: 5
+  optimizer: adamw_8bit
+  output_dir: outputs
+  report_to: tensorboard
+  seed: 3407
+  warmup_steps: 1
+  weight_decay: 0.01