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Overview

This is a fork of :

Differences from original

HuggingFace Chat Templates

Dataset format option is removed. Only datasets that are compatible with Huggingface chat templates are accepted. For more info about chat templates see Chat Templates

epochs instead of steps

This modification comes from jondurbin/qlora. --max_steps parameter is removed in favor of --num_train_epochs (defaults to 3)

Full, non-(q)lora fine-tune example

Example used for the llama-2 7b airoboros, version 3.0:

export BASE_DIR=/workspace
export WANDB_API_KEY=[redacted]
export WANDB_PROJECT=airoboros-l2-7b-3.0

torchrun --nnodes=1 --nproc_per_node=7 $BASE_DIR/qlora/train.py \
  --model_name_or_path $BASE_DIR/llama-2-7b-hf \
  --working_dir $BASE_DIR/$WANDB_PROJECT-checkpoints \
  --output_dir $BASE_DIR/$WANDB_PROJECT \
  --num_train_epochs 5 \
  --logging_steps 1 \
  --save_strategy steps \
  --save_steps 15 \
  --save_total_limit 1 \
  --data_seed 11422 \
  --evaluation_strategy steps \
  --eval_dataset_size 0.02 \
  --eval_steps 5 \
  --max_new_tokens 4096 \
  --dataloader_num_workers 3 \
  --logging_strategy steps \
  --optim adamw_torch \
  --do_train \
  --full_finetune \
  --bits 16 \
  --bf16 \
  --dataset $BASE_DIR/conversations.json \
  --dataset_format airoboros_chat \
  --model_max_len 4096 \
  --per_device_train_batch_size 12 \
  --learning_rate 2e-5 \
  --lr_scheduler_type cosine \
  --warmup_ratio 0.005 \
  --weight_decay 0.0 \
  --seed 11422 \
  --report_to wandb \
  --deepspeed deepspeed-7b.json \
  --gradient_checkpointing \
  --use_flash_attention_2

deepspeed-7b.json

{
  "gradient_accumulation_steps": "auto",
  "gradient_clipping": "auto",
  "train_batch_size": "auto",
  "train_micro_batch_size_per_gpu": "auto",
  "bf16": {
    "enabled": true
  },
  "zero_optimization": {
    "stage": 2,
    "contiguous_gradients": true,
    "overlap_comm": true,
    "reduce_scatter": true,
    "reduce_bucket_size": 5e8,
    "allgather_bucket_size": 5e8
  }
}

QLoRA example

Script used for llama-2 70b airoboros, version 3.0:

export BASE_DIR=/workspace
export WANDB_API_KEY=[redacted]
export WANDB_PROJECT=airoboros-l2-70b-3.0

accelerate launch $BASE_DIR/qlora/train.py \
  --model_name_or_path $BASE_DIR/llama-2-70b-hf \
  --working_dir $BASE_DIR/$WANDB_PROJECT-checkpoints \
  --output_dir $BASE_DIR/$WANDB_PROJECT-peft \
  --merged_output_dir $BASE_DIR/$WANDB_PROJECT \
  --num_train_epochs 5 \
  --logging_steps 1 \
  --save_strategy steps \
  --save_steps 75 \
  --save_total_limit 3 \
  --data_seed 11422 \
  --evaluation_strategy steps \
  --per_device_eval_batch_size 2 \
  --eval_dataset_size 0.01 \
  --eval_steps 75 \
  --max_new_tokens 4096 \
  --dataloader_num_workers 3 \
  --logging_strategy steps \
  --do_train \
  --lora_r 64 \
  --lora_alpha 16 \
  --lora_modules all \
  --bf16 \
  --bits 4 \
  --double_quant \
  --quant_type nf4 \
  --lr_scheduler_type constant \
  --dataset $BASE_DIR/conversations.json \
  --dataset_format airoboros_chat \
  --model_max_len 4096 \
  --per_device_train_batch_size 2 \
  --learning_rate 0.00008 \
  --adam_beta2 0.999 \
  --max_grad_norm 0.3 \
  --lora_dropout 0.0 \
  --weight_decay 0.0 \
  --seed 11422 \
  --report_to wandb \
  --gradient_checkpointing \
  --use_flash_attention_2 \
  --ddp_find_unused_parameters False