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PaddleSpeech/examples/tiny/s0/local/tune.sh

34 lines
551 B

#!/bin/bash
Support paddle 2.x (#538) * 2.x model * model test pass * fix data * fix soundfile with flac support * one thread dataloader test pass * export feasture size add trainer and utils add setup model and dataloader update travis using Bionic dist * add venv; test under venv * fix unittest; train and valid * add train and config * add config and train script * fix ctc cuda memcopy error * fix imports * fix train valid log * fix dataset batch shuffle shift start from 1 fix rank_zero_only decreator error close tensorboard when train over add decoding config and code * test process can run * test with decoding * test and infer with decoding * fix infer * fix ctc loss lr schedule sortagrad logger * aishell egs * refactor train add aishell egs * fix dataset batch shuffle and add batch sampler log print model parameter * fix model and ctc * sequence_mask make all inputs zeros, which cause grad be zero, this is a bug of LessThanOp add grad clip by global norm add model train test notebook * ctc loss remove run prefix using ord value as text id * using unk when training compute_loss need text ids ord id using in test mode, which compute wer/cer * fix tester * add lr_deacy refactor code * fix tools * fix ci add tune fix gru model bugs add dataset and model test * fix decoding * refactor repo fix decoding * fix musan and rir dataset * refactor io, loss, conv, rnn, gradclip, model, utils * fix ci and import * refactor model add export jit model * add deploy bin and test it * rm uselss egs * add layer tools * refactor socket server new model from pretrain * remve useless * fix instability loss and grad nan or inf for librispeech training * fix sampler * fix libri train.sh * fix doc * add license on cpp * fix doc * fix libri script * fix install * clip 5 wer 7.39, clip 400 wer 7.54, 1.8 clip 400 baseline 7.49
4 years ago
if [ $# != 1 ];then
echo "usage: tune ckpt_path"
exit 1
fi
# grid-search for hyper-parameters in language model
python3 -u ${BIN_DIR}/tune.py \
--device 'gpu' \
--nproc 1 \
--config conf/deepspeech2.yaml \
--num_batches=-1 \
--batch_size=128 \
--beam_size=500 \
--num_proc_bsearch=12 \
--num_alphas=45 \
--num_betas=8 \
--alpha_from=1.0 \
--alpha_to=3.2 \
--beta_from=0.1 \
--beta_to=0.45 \
--cutoff_prob=1.0 \
--cutoff_top_n=40 \
--checkpoint_path ${1}
if [ $? -ne 0 ]; then
echo "Failed in tuning!"
exit 1
fi
exit 0