base_model: Qwen/Qwen2.5-7B-Instruct | |
model_type: AutoModelForCausalLM | |
tokenizer_type: AutoTokenizer | |
trust_remote_code: true | |
load_in_8bit: false | |
load_in_4bit: true | |
strict: false | |
datasets: | |
- path: aaditya/mimicraw_clinicaltrial_train | |
type: alpaca | |
val_set_size: 0.05 | |
output_dir: . | |
sequence_len: 4096 | |
sample_packing: true | |
pad_to_sequence_len: true | |
adapter: qlora | |
lora_r: 256 | |
lora_alpha: 512 | |
lora_dropout: 0.05 | |
lora_target_linear: true | |
lora_target_modules: | |
- q_proj | |
- k_proj | |
- v_proj | |
- o_proj | |
- gate_proj | |
- down_proj | |
- up_proj | |
wandb_project: qwen_mimicrawclinicaltrail | |
wandb_entity: | |
wandb_watch: | |
wandb_name: | |
wandb_log_model: | |
gradient_accumulation_steps: 4 | |
micro_batch_size: 6 | |
num_epochs: 3 | |
optimizer: adamw_torch | |
lr_scheduler: cosine | |
learning_rate: 2e-6 | |
train_on_inputs: false | |
group_by_length: false | |
bf16: auto | |
fp16: false | |
tf32: false | |
gradient_checkpointing: true | |
early_stopping_patience: | |
resume_from_checkpoint: | |
logging_steps: 1 | |
xformers_attention: | |
flash_attention: true | |
warmup_steps: 100 | |
evals_per_epoch: 3 | |
eval_table_size: | |
saves_per_epoch: 1 | |
debug: | |
deepspeed: | |
weight_decay: 0.0 | |
fsdp: | |
fsdp_config: | |
save_total_limit: 4 | |