ColPali
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vidore-experimental
colpali-v1.2 / training_config.yml
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config:
(): colpali_engine.utils.train_colpali_engine_models.ColModelTrainingConfig
output_dir: !path ../../../models/right_pad/train_colpali_hardneg_long
processor:
() : colpali_engine.utils.wrapper.AutoProcessorWrapper
pretrained_model_name_or_path: "./models/colpaligemma-3b-pt-448-base" # "./models/paligemma-3b-mix-448"
max_length: 50
model:
(): colpali_engine.utils.wrapper.AllPurposeWrapper
class_to_instanciate: !ext colpali_engine.models.paligemma_colbert_architecture.ColPali
pretrained_model_name_or_path: "./models/colpaligemma-3b-pt-448-base"
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_train_set_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:
(): transformers.training_args.TrainingArguments
output_dir: null
overwrite_output_dir: true
num_train_epochs: 5
per_device_train_batch_size: 4
# 6 x 8 gpus = 48 batch size
# gradient_accumulation_steps: 4
per_device_eval_batch_size: 4
eval_strategy: "steps"
# dataloader_num_workers: 8
# bf16: true
save_steps: 500
logging_steps: 10
eval_steps: 50
warmup_steps: 1000
learning_rate: 5e-5
save_total_limit: 1
resume_from_checkpoint: true
# optim: "paged_adamw_8bit"
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).*$|.*(custom_text_proj).*$)'