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config:
(): custom_colbert.utils.train_custom_colbert_models.ColModelTrainingConfig
output_dir: !path ../../../models/without_tabfquad_no_pairwise/train_colpali-3b-mix-448
processor:
() : custom_colbert.utils.wrapper.AutoProcessorWrapper
pretrained_model_name_or_path: "./models/paligemma-3b-mix-448"
max_length: 50
model:
(): custom_colbert.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 custom_colbert.utils.dataset_transformation.load_train_set
eval_dataset_loader: !import ../data/test_data.yaml
max_length: 50
run_eval: true
add_suffix: true
loss_func:
(): custom_colbert.loss.colbert_loss.ColbertLoss
tr_args: !import ../tr_args/default_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).*$|.*(custom_text_proj).*$)'
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