base_model: Neko-Institute-of-Science/LLaMA-7B-4bit-128g base_model_config: Neko-Institute-of-Science/LLaMA-7B-4bit-128g model_type: LlamaForCausalLM tokenizer_type: LlamaTokenizer trust_remote_code: load_in_8bit: true gptq: true datasets: - path: vicgalle/alpaca-gpt4 type: alpaca dataset_prepared_path: last_run_prepared val_set_size: 0.02 adapter: lora_model_dir: sequence_len: 2048 max_packed_sequence_len: lora_r: 8 lora_alpha: 16 lora_dropout: 0.05 lora_target_modules: - q_proj - v_proj lora_fan_in_fan_out: false wandb_project: llama-7b-lora-int4 wandb_watch: wandb_run_id: wandb_log_model: output_dir: ./llama-7b-lora-int4 batch_size: 1 micro_batch_size: 1 num_epochs: 3 optimizer: adamw_bnb_8bit torchdistx_path: lr_scheduler: cosine learning_rate: 0.0000002 train_on_inputs: false group_by_length: false fp16: true bf16: false tf32: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 5 xformers_attention: flash_attention: gradient_checkpointing: true gptq_groupsize: 128 gptq_model_v1: false warmup_steps: 20 eval_steps: 110 save_steps: 660 debug: deepspeed: weight_decay: 0.0001 fsdp: fsdp_config: tokens: pad_token: "[PAD]" bos_token: "" eos_token: "" unk_token: ""