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#!/bin/bash
FAIRSEQ= # Setup your fairseq directory
config_dir=${FAIRSEQ}/examples/mr_hubert/config
config_name=mr_hubert_base_librispeech
# override configs if need
max_tokens=3200000
max_sample_size=1000000
max_update=50000
# Prepared Data Directory
data_dir=librispeech
# -- data_dir
# -- train.tsv
# -- train.ltr
# -- valid.tsv
# -- valid.ltr
# -- dict.ltr.txt
exp_dir=exp # Target experiments directory
ratios="[1, 2]" # Default label rate ratios
hubert_path=/path/of/your/hubert.pt
_opts=
# If use slurm, uncomment this line and modify the job submission at
# _opts="${_opts} hydra/launcher=submitit_slurm +hydra.launcher.partition=${your_slurm_partition} +run=submitit_reg"
# If want to set additional experiment tag, uncomment this line
# _opts="${_opts} hydra.sweep.subdir=${your_experiment_tag}"
python ${FAIRSEQ}/fairseq_cli/hydra_train.py \
-m --config-dir ${config_dir} --config-name ${config_name} ${_opts} \
task.data=${data_dir} +task.max_sample_size=${max_sample_size} \
task.label_dir=${data_dir} \
task.label_rate_ratios='${ratios}' \
dataset.max_tokens=${max_tokens} \
optimization.max_update=${max_update} \
model.multires_hubert_path=${hubert_path} \
hydra.sweep.dir=${exp_dir} &