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# tulu command.
# WARNING: eval uses alpaca eval. this costs $$.
CMD="
accelerate launch -m sdlm.run_tulu_ar \
--dataset_name allenai/tulu-v2-sft-mixture \
--per_device_train_batch_size 2 \
--per_device_eval_batch_size 2 \
--evaluation_strategy epoch \
--do_train \
--do_eval \
--num_train_epochs 2 \
--report_to tensorboard \
--overwrite_output_dir \
--max_seq_length 512 \
--generation_max_length 512 \
--simplex_value 5 \
--num_diffusion_steps 5000 \
--lr_scheduler_type cosine \
--learning_rate 2e-5 \
--conditional_generation "seq2seq" \
--is_causal true \
--warmup_ratio 0.03 \
--logging_steps 50 \
--save_total_limit 1 \
--pad_to_max_length \
--bf16 \
--optim adamw_torch_fused \
--gradient_checkpointing \
--use_flash_attention2 \
--save_strategy steps \
--gradient_checkpointing \
--num_diffusion_steps 0 \
--tokenizer_padding_side "left" \
--include_inputs_for_metrics \
--preprocessing_num_workers 16 \
--model_revision 26bca36bde8333b5d7f72e9ed20ccda6a618af24 \
"
# for ai2/jupiter-cirrascale-2 cluster
if [ ! -z "${BEAKER}" ]; then
gantry run -y -n mistral_tulu_ar_baseline_512 -t mistral_tulu_ar_baseline_512 --allow-dirty \
--workspace ai2/tess2 \
--gpus 8 \
--priority preemptible \
--budget ai2/allennlp \
--preemptible \
--no-nfs \
--cluster ai2/jupiter-cirrascale-2 \
--env 'HF_HOME=/net/weka/reviz/jaket/.hf' \
--env 'PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python' \
--env 'IS_ALPACA_EVAL_2=False' \
--env-secret OPENAI_API_KEY=OPENAI_API_KEY \
--env-secret HF_TOKEN=HF_TOKEN \
--beaker-image 'ai2/pytorch2.0.0-cuda11.8-python3.10' \
--venv 'base' \
--pip requirements.txt \
-- ${CMD} \
--model_name_or_path mistralai/Mistral-7B-v0.1 \
--save_steps 1000 \
--max_eval_samples 1000 \
--gradient_accumulation_steps 8 \
--output_dir /results
else
${CMD} \
--model_name_or_path mistralai/Mistral-7B-v0.1 \
--eval_steps 10 \
--save_steps 10 \
--max_eval_samples 16 \
--gradient_accumulation_steps 1 \
--num_inference_diffusion_steps 10 \
--output_dir outputs/test
fi
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