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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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configuration: training_args = DPOConfig( output_dir="llava-lora-12-04", bf16=True, gradient_checkpointing=True, per_device_train_batch_size=8, per_device_eval_batch_size=1, gradient_accumulation_steps=32, evaluation_strategy="steps", eval_steps=1, learning_rate=1e-5, beta=0.1, warmup_ratio=0.1, lr_scheduler_type="cosine", num_train_epochs=2, dataset_num_proc=32, # tokenization will use 32 processes dataloader_num_workers=32, # data loading will use 32 workers logging_steps=1, )
#Define LoRA configuration with specified rank lora_config = LoraConfig( r=64, # Set rank to 64 lora_alpha=128, # Set scaling factor to 128 target_modules="all-linear", # Target all linear layers )
trainer = DPOTrainer( model, ref_model=None, # not needed when using peft args=training_args, train_dataset=train_dataset, eval_dataset=eval_dataset, tokenizer=processor, peft_config=lora_config, )
