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checkpoint_mount="01H4KVBDMMN284JQ6G2N6GS2EV:checkpoint-10000"
for task in mnli mrpc qnli qqp rte sst2
do
EXP_NAME="${task}_fixed_eval_5k_data"
gantry run -y -n $EXP_NAME -t $EXP_NAME --allow-dirty \
--workspace ai2/tess2 \
--nfs \
--gpus 1 \
--priority normal \
--cluster ai2/allennlp-cirrascale \
--env 'HF_HOME=/net/nfs.cirrascale/allennlp/hamishi/.hf' \
--env 'PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python' \
--beaker-image 'ai2/pytorch2.0.0-cuda11.8-python3.10' \
--dataset "${checkpoint_mount}:/model" \
--venv 'base' \
--pip requirements.txt \
-- python -m sdlm.run_glue \
--model_name_or_path /model \
--dataset_name $task \
--output_dir /results \
--do_train \
--do_eval \
--max_seq_length 128 \
--skip_special_tokens False \
--per_device_train_batch_size 32 \
--per_device_eval_batch_size 32 \
--evaluation_strategy epoch \
--save_strategy steps \
--report_to tensorboard \
--overwrite_output_dir \
--pad_to_max_length \
--simplex_value 5 \
--max_train_samples 5000 \
--num_train_epochs 5 \
--num_diffusion_steps 5000 \
--num_inference_diffusion_steps 500 \
--conditional_generation seq2seq \
--learning_rate 3e-5 \
--gradient_accumulation_steps 1 \
--lr_scheduler_type cosine \
--beta_schedule squaredcos_improved_ddpm \
--top_p 0.99 \
--warmup_ratio 0.03 \
--logging_steps 50 \
--save_total_limit 1 \
--max_eval_samples 500
done
# # stsb needs longer sequences
task="stsb"
EXP_NAME="${task}_orig_100k_c4_roberta_base_fixed_shuffle_smol_data_pretrained_str_label"
gantry run -y -n $EXP_NAME -t $EXP_NAME --allow-dirty \
--workspace ai2/tess2 \
--nfs \
--gpus 1 \
--priority normal \
--cluster ai2/allennlp-cirrascale \
--env 'HF_HOME=/net/nfs.cirrascale/allennlp/hamishi/.hf' \
--env 'PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python' \
--beaker-image 'ai2/pytorch2.0.0-cuda11.8-python3.10' \
--venv 'base' \
--dataset "${checkpoint_mount}:/model" \
--pip requirements.txt \
-- python -m sdlm.run_glue \
--model_name_or_path /model \
--dataset_name $task \
--output_dir /results \
--do_train \
--do_eval \
--max_seq_length 256 \
--per_device_train_batch_size 32 \
--per_device_eval_batch_size 32 \
--skip_special_tokens False \
--evaluation_strategy epoch \
--save_strategy steps \
--report_to tensorboard \
--overwrite_output_dir \
--pad_to_max_length \
--simplex_value 5 \
--max_train_samples 1000 \
--num_train_epochs 3 \
--num_diffusion_steps 5000 \
--num_inference_diffusion_steps 500 \
--conditional_generation seq2seq \
--learning_rate 3e-5 \
--gradient_accumulation_steps 1 \
--lr_scheduler_type cosine \
--beta_schedule squaredcos_improved_ddpm \
--top_p 0.99 \
--warmup_ratio 0.03 \
--logging_steps 50 \
--save_total_limit 1 \
--max_eval_samples 500
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