Model Card: LoRA Configuration Causal Language Model
Training Specifications
LoRA Configuration
- Configuration:
LoraConfig
- Parameters:
r
: 16lora_alpha
: 16lora_dropout
: 0.05bias
: nonetask_type
: CAUSAL_LMtarget_modules
: ['k_proj', 'gate_proj', 'v_proj', 'up_proj', 'q_proj', 'o_proj', 'down_proj']
- Parameters:
Model to Fine-Tune
- Function:
AutoModelForCausalLM.from_pretrained
- Parameters:
model_name
torch_dtype
: torch.float16load_in_4bit
: True
- Configurations:
use_cache
: False
- Parameters:
Reference Model
- Function:
AutoModelForCausalLM.from_pretrained
- Parameters:
model_name
torch_dtype
: torch.float16load_in_4bit
: True
- Parameters:
Training Arguments
- Function:
TrainingArguments
- Parameters:
per_device_train_batch_size
: 4gradient_accumulation_steps
: 4gradient_checkpointing
: Truelearning_rate
: 5e-5lr_scheduler_type
: "cosine"max_steps
: 200save_strategy
: "no"logging_steps
: 1output_dir
: new_modeloptim
: "paged_adamw_32bit"warmup_steps
: 100bf16
: Truereport_to
: "wandb"
- Parameters:
Create DPO Trainer
- Function:
DPOTrainer
- Parameters:
model
ref_model
args
: training_argstrain_dataset
: datasettokenizer
: tokenizerpeft_config
: peft_configbeta
: 0.1max_prompt_length
: 1024max_length
: 1536
- Parameters:
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