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config:
(): colpali_engine.utils.train_colpali_engine_models.ColModelTrainingConfig
output_dir: !path ../../../models/biidefics2-8b-chatty
processor:
(): colpali_engine.utils.wrapper.AutoProcessorWrapper
pretrained_model_name_or_path: "HuggingFaceM4/idefics2-8b"
do_image_splitting: false
model:
(): colpali_engine.utils.wrapper.AutoColModelWrapper
pretrained_model_name_or_path: "HuggingFaceM4/idefics2-8b-chatty"
training_objective: "biencoder"
# attn_implementation: "flash_attention_2"
torch_dtype: !ext torch.bfloat16
quantization_config:
(): transformers.BitsAndBytesConfig
load_in_4bit: true
bnb_4bit_quant_type: "nf4"
bnb_4bit_compute_dtype: "float16"
bnb_4bit_use_double_quant: true
dataset_loading_func: !ext colpali_engine.utils.dataset_transformation.load_docvqa_dataset
max_length: 256
run_eval: true
loss_func:
(): colpali_engine.loss.colbert_loss.BiEncoderLoss
tr_args:
(): transformers.training_args.TrainingArguments
output_dir: null
overwrite_output_dir: true
num_train_epochs: 3
per_device_train_batch_size: 4
gradient_accumulation_steps: 8
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: 100
learning_rate: 5e-5
save_total_limit: 1
peft_config:
(): peft.LoraConfig
r: 8
lora_alpha: 8
lora_dropout: 0.1
init_lora_weights: "gaussian"
bias: "none"
task_type: "FEATURE_EXTRACTION"
target_modules: '.*(text_model|modality_projection|perceiver_resampler).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$'
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