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u107/coqui
coqui is a machine learning model from u107. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
- v51 - language: uk - Epoch: 9 - Loss: 5.813825 - Test: WER: 0.163878, CER: 0.033506, loss: 4.564916 - v50 - language: uk-RU - Epoch: 9 - Loss: 8.292612 - v49 - language: uk-RU - Epoch: 8 - Loss: 30.810781 - Test: WE…
Downloads · 30 days
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From the Hugging Face model README
docker run --gpus all --ulimit memlock=-1 --ulimit stack=67108864 --shm-size=18gb -it --rm -v ${PWD}/ds:/ds -v ${PWD}/../../datasets:/datasets ghcr.io/coqui-ai/stt-train:latest
#!/usr/bin/env python
import os
from coqui_stt_training.util.config import initialize_globals_from_args
from coqui_stt_training.train import train
from coqui_stt_training.evaluate import test
# only one GPU for only one training sample
# os.environ["CUDA_VISIBLE_DEVICES"] = "0"
# os.environ["TF_ENABLE_DEPRECATION_WARNINGS"] = "1"
# TF_ENABLE_DEPRECATION_WARNINGS=1 python /ds/train_uk.py
# CUDA_VISIBLE_DEVICES=0 python /ds/train_uk.py
initialize_globals_from_args(
# drop_source_layers=1,
# load_train='last',
use_allow_growth=True,
bytes_output_mode=True,
force_initialize_learning_rate=False,
# load_train="auto",
# load_evaluate="auto",
#
load_cudnn=False,
train_cudnn=True,
n_hidden=1024,
epochs=5,
learning_rate=0.01,
dropout_rate=0.5,
# shuffle_batches=True,
show_progressbar=True,
early_stop=False,
# alphabet_config_path="/ds/alphabet.txt",
train_files=['/ds/train_uk.sdb'],
train_batch_size=32,
dev_files=['/ds/dev_uk.sdb'],
dev_batch_size=32,
test_files=['/ds/test_uk.sdb'],
test_batch_size=12,
feature_cache='/ds/tmp/feature_cache_sdb',
checkpoint_dir='/ds/ckpt_sdb',
# load_checkpoint_dir='/ds/coqui-stt-1.4.0-checkpoint',
# save_checkpoint_dir='/ds/ckpt_sdb',
scorer_path='',
export_dir='/ds/export_train_sdb',
export_tflite=False,
export_language='Ukraine (uk-UA)',
export_author_id="Vadim",
export_model_name="ds_uk",
export_model_version="0.0.1",
# audio_sample_rate=16000,
# max_to_keep=5,
# plateau_epochs=3,
# checkpoint_secs=1200,
# use_allow_growth=True,
)
train()
test()