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description: Train VAE on SNLI Dataset
auth:
# which virtual cluster you belong to (msrlabs, resrchprojvc6, etc.). Everyone has access to "pnrsy".
vc: msrlabs
# physical cluster to use (cam, gcr, rr1) or Azure clusters (eu1, eu2, etc.)
# cluster: rr2, eu2, eu1 et1
cluster: eu2
# docker environment (vm) in which your job will run. we provide "generic" dockers
# with the main deep learning toolkit installed (PyTorch, TF, Chainer, etc.)
docker:
# image: philly/jobs/custom/generic-docker:py27
# registry: phillyregistry.azurecr.io
image: chunyl/pytorch-transformers:v0
registry: index.docker.io
storage:
_default:
#use_phillyfs: True
storage_account_name: textae
container_name: bigtextae
mount_path: /mnt/_default
code:
# local directory of the code. this will be uploaded to the server.
# $CONFIG_DIR is expanded to the directory of this config file
code_upload: False
remote_dir: code/
local_dir: $CONFIG_DIR/code
#data:
# data upload is not required for this example
#data_upload: False
search:
job_template:
name: exp_{experiment_name:s}_b{bs_option:.0f}_beta_{beta_option:.2f}_d_{dim_target_kl_option:.2f}_r0_{ratio_zero_option:.2f}_ra_{ratio_increase_option:.2f}
sku: G4 # G4 # G1
command:
- pip install --user --editable .
- pip install --user azure
- pip install --user tqdm
- python examples/big_ae/run_lm_vae_training.py --use_philly --num_train_epochs 20.0 --beta {beta_option} --dim_target_kl {dim_target_kl_option} --ratio_zero {ratio_zero_option} --ratio_increase {ratio_increase_option} --dataset Snli --per_gpu_train_batch_size {bs_option} --per_gpu_eval_batch_size 1 --block_size 100 --output_dir ../output/philly_vae_snli_epoch20_b{beta_option}_d{dim_target_kl_option}_r0{ratio_zero_option}_ra{ratio_increase_option} --encoder_model_type bert --encoder_model_name_or_path bert-base-cased --decoder_model_type gpt2 --decoder_model_name_or_path gpt2 --do_train --train_data_file ../data/datasets/snli_data/train.txt --do_eval --eval_data_file ../data/datasets/snli_data/test.txt --overwrite_output_dir --save_steps 2000 --logging_steps 100
max_trials: 50
type: grid
params:
- name: bs_option
spec: discrete
values: [10] #
- name: beta_option
spec: discrete
values: [0.25,1.0] #
- name: dim_target_kl_option
spec: discrete
values: [0.01,0.05,0.25,0.5,1] #
- name: ratio_zero_option
spec: discrete
values: [0.5] #
- name: ratio_increase_option
spec: discrete
values: [0.25] #
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