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#!/bin/bash
model_name_or_path=$1
reward_model_name_or_path=$2
guidance_scale=$3
eval_name=$4
accelerate launch \
--mixed_precision bf16 -m sdlm.run_tulu \
--model_name_or_path $model_name_or_path \
--dataset_name allenai/tulu-v2-sft-mixture \
--per_device_train_batch_size 2 \
--per_device_eval_batch_size 2 \
--do_train false \
--do_eval true \
--load_states_in_eval_from_model_path false \
--log_level info \
--evaluation_strategy steps \
--report_to tensorboard \
--overwrite_output_dir \
--max_seq_length 2048 \
--min_eval_seq_length 512 \
--simplex_value 5 \
--num_diffusion_steps 5000 \
--lr_scheduler_type cosine \
--learning_rate 1e-5 \
--pad_to_max_length \
--beta_schedule squaredcos_improved_ddpm \
--weight_decay 0.01 \
--top_p 0.99 \
--max_steps 100000 \
--warmup_ratio 0.05 \
--logging_steps 50 \
--save_total_limit 1 \
--conditional_generation ul2 \
--self_condition "logits_mean" \
--self_condition_mix_before_weights \
--bf16 \
--optim adamw_torch_fused \
--gradient_checkpointing \
--use_flash_attention2 \
--is_causal false \
--line_by_line true \
--mask_padding_in_loss false \
--ddp_find_unused_parameters false \
--without_compute_metrics true \
--classifier_model_name_or_path $reward_model_name_or_path \
--guidance_scale ${guidance_scale} \
--use_gumbel_softmax false \
--do_hard_sample false \
--eval_dataset_name $eval_name \
--max_eval_samples 1500 \
--num_inference_diffusion_steps 100 \
--output_dir outputs/${model_name_or_path}_${guidance_scale}
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