config:
  (): colpali_engine.utils.train_colpali_engine_models.ColModelTrainingConfig
  output_dir: !path ../../../models/train_colpali_docmatix_hardneg_ib_3b-mix-448
  processor:
    () : colpali_engine.utils.wrapper.AutoProcessorWrapper
    pretrained_model_name_or_path: "./models/paligemma-3b-mix-448"
    max_length: 50
  model:
    (): colpali_engine.utils.wrapper.AutoColModelWrapper
    pretrained_model_name_or_path: "./models/paligemma-3b-mix-448"
    training_objective: "colbertv1"
    # attn_implementation: "eager"
    torch_dtype:  !ext torch.bfloat16
#    device_map: "auto"
#    quantization_config:
#      (): transformers.BitsAndBytesConfig
#      load_in_4bit: true
#      bnb_4bit_quant_type: "nf4"
#      bnb_4bit_compute_dtype:  "bfloat16"
#      bnb_4bit_use_double_quant: true

  dataset_loading_func: !ext colpali_engine.utils.dataset_transformation.load_docmatix_ir_negs
  eval_dataset_loader: !import ../data/test_data.yaml

  max_length: 50
  run_eval: true
  add_suffix: true
  loss_func:
    (): colpali_engine.loss.colbert_loss.ColbertPairwiseNegativeCELoss
    in_batch_term: true
  tr_args: !import ../tr_args/default_neg_tr_args.yaml
  peft_config:
    (): peft.LoraConfig
    r: 32
    lora_alpha: 32
    lora_dropout: 0.1
    init_lora_weights: "gaussian"
    bias: "none"
    task_type: "FEATURE_EXTRACTION"
    target_modules: '(.*(language_model).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$|.*(custom_text_proj).*$)'
    # target_modules: '(.*(language_model).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$|.*(custom_text_proj).*$)'