22810c97b7
* use warmup_ratio as a better default than warmup steps since it's data dependent * replace remainder of warmup_steps
87 lines
2.1 KiB
YAML
87 lines
2.1 KiB
YAML
# An example finetuning Saleforce's XGen-7b model with 8k context using qlora
|
|
# on Tim Dettmer's Guanaco dataset.
|
|
base_model: Salesforce/xgen-7b-8k-base
|
|
# optionally might have model_type or tokenizer_type
|
|
model_type: AutoModelForCausalLM
|
|
tokenizer_type: AutoTokenizer
|
|
# Automatically upload checkpoint and final model to HF
|
|
# hub_model_id: username/custom_model_name
|
|
|
|
trust_remote_code: true
|
|
|
|
load_in_8bit: false
|
|
# enable 4bit for QLoRA
|
|
load_in_4bit: true
|
|
gptq: false
|
|
push_dataset_to_hub:
|
|
datasets:
|
|
- path: timdettmers/openassistant-guanaco
|
|
data_files:
|
|
- openassistant_best_replies_train.jsonl
|
|
type: "completion"
|
|
dataset_prepared_path:
|
|
val_set_size: 0.05
|
|
# enable QLoRA
|
|
adapter: qlora
|
|
lora_model_dir:
|
|
sequence_len: 8192
|
|
max_packed_sequence_len:
|
|
|
|
# hyperparameters from QLoRA paper Appendix B.2
|
|
# "We find hyperparameters to be largely robust across datasets"
|
|
lora_r: 64
|
|
lora_alpha: 16
|
|
# 0.1 for models up to 13B
|
|
# 0.05 for 33B and 65B models
|
|
lora_dropout: 0.05
|
|
# add LoRA modules on all linear layers of the base model
|
|
lora_target_linear: true
|
|
|
|
wandb_project:
|
|
wandb_entity:
|
|
wandb_watch:
|
|
wandb_name:
|
|
wandb_log_model:
|
|
output_dir: ./outputs/qlora-out
|
|
|
|
# QLoRA paper Table 9
|
|
# - 16 for 7b & 13b
|
|
# - 32 for 33b, 64 for 64b
|
|
# Max size tested on A6000
|
|
# - 7b: 40
|
|
# - 40b: 4
|
|
# decrease if OOM, increase for max VRAM utilization
|
|
micro_batch_size: 1
|
|
gradient_accumulation_steps: 1
|
|
num_epochs: 4
|
|
# Optimizer for QLoRA
|
|
optimizer: paged_adamw_32bit
|
|
torchdistx_path:
|
|
lr_scheduler: cosine
|
|
# QLoRA paper Table 9
|
|
# - 2e-4 for 7b & 13b
|
|
# - 1e-4 for 33b & 64b
|
|
learning_rate: 0.00002
|
|
bf16: auto
|
|
tf32: false
|
|
gradient_checkpointing: true
|
|
# stop training after this many evaluation losses have increased in a row
|
|
# https://huggingface.co/transformers/v4.2.2/_modules/transformers/trainer_callback.html#EarlyStoppingCallback
|
|
early_stopping_patience: 3
|
|
resume_from_checkpoint:
|
|
auto_resume_from_checkpoints: true
|
|
logging_steps: 1
|
|
xformers_attention: true
|
|
flash_attention:
|
|
gptq_groupsize:
|
|
gptq_model_v1:
|
|
warmup_ratio: 0.1
|
|
evals_per_epoch: 4
|
|
saves_per_epoch: 1
|
|
weight_decay: 0.0
|
|
special_tokens:
|
|
eos_token: "<|endoftext|>"
|
|
bos_token: "<|endoftext|>"
|
|
unk_token: "<|endoftext|>"
|
|
pad_token: "<|endoftext|>"
|