qwerrwe / configs /llama_65B_alpaca.yml
winglian's picture
fix lora target module, require explicit flash attention, fix min logging steps, don't use adam8bit for int4, hash prepared datasets, support hf hub datasets
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base_model: huggyllama/llama-65b
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: true
datasets:
- path: data/alpaca_data_gpt4.jsonl
type: alpaca
- path: data/vicuna_cleaned.jsonl
type: sharegpt
- path: data/gpt4-instruct-similarity-0.6-dataset.jsonl
type: gpteacher
- path: data/roleplay-similarity_0.6-instruct-dataset.jsonl
type: gpteacher
dataset_prepared_path: last_run_prepared
val_set_size: 0.04
adapter: lora
lora_model_dir:
sequence_len: 2048
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-65b-lora
wandb_watch:
wandb_run_id:
wandb_log_model: checkpoint
output_dir: ./lora-llama-alpaca
batch_size: 128
micro_batch_size: 16
num_epochs: 5
learning_rate: 0.00003
train_on_inputs: false
group_by_length: false
bf16: true
tf32: true
early_stopping_patience:
resume_from_checkpoint:
local_rank: