@othiele hi
I was train model but WER is constant is any way to decrease WER
Here is my training result:
Epoch 3 | Training | Elapsed Time: 0:00:21 | Steps: 49 | Loss: 1.624806
Epoch 3 | Validation | Elapsed Time: 0:00:05 | Steps: 13 | Loss: 3.249443 |
Dataset: 10000_data_set/dev.csv
I Early stop triggered as (for last 4 steps) validation loss: 3.249443 with
standard deviation: 0.094293 and mean: 3.145775
I FINISHED optimization in 0:01:52.091116
I Restored variables from best validation checkpoint at
10000_512_checkpoint/best_dev-21290, step 21290
Testing model on 10000_data_set/test.csv
Test epoch | Steps: 9 | Elapsed Time: 0:00:44
Test on 10000_data_set/test.csv - WER: 0.225941, CER: 0.049616, loss:
4.468176
Command is :
python3.6 DeepSpeech.py
–train_files 10000_data_set/train.csv
–checkpoint_dir 10000_512_checkpoint/
–epochs 60
–dev_files 10000_data_set/dev.csv
–test_files 10000_data_set/test.csv
–n_hidden 512
–learning_rate 0.0001
–export_dir 10000_512_export
–early_stop False
–use_seq_length False
–earlystop_nsteps 3
–estop_mean_thresh 0.1
–estop_std_thresh 0.1
–dropout_rate 0.25
–train_batch_size 80
–dev_batch_size 80
–test_batch_size 45
–report_count 50
–use_cudnn True \
@elpimous_robot
is it required to give full path of wav file in csv
directory structure
wav_file_folder:
-all_wav[10000 wav file]
-train.csv
-test.csv
-dev.csv
in same directory