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Running
on
Zero
Running
on
Zero
File size: 2,322 Bytes
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# Please log in to huggingface first
LIBRITTSR_WAV_DIR='' # downloaded libritts-r wav dir
OTHER_WAV_DIR='' # downloaded other wav dirs
OUTPUT_DIR="./output_finetuning_captts/" # output dir, to save checkpoints
TEMPORY_SAVE_TO_DISK="./audio_code_finetuning_captts/" # dac codec saved dir
SAVE_TO_DISK="./dataset_finetuning_captts/" # huggingface metadata saved dir
WANDB_KEY='' # your wandb key for logging
PRETRAINED_MODEL_PATH="" # your pretrained model path
export CUDA_LAUNCH_BLOCKING=1
export TORCH_USE_CUDA_DSA=1
accelerate launch ./training/finetune_captts.py \
--model_name_or_path ${PRETRAINED_MODEL_PATH} \
--feature_extractor_name "parler-tts/dac_44khZ_8kbps" \
--description_tokenizer_name ${PRETRAINED_MODEL_PATH} \
--prompt_tokenizer_name ${PRETRAINED_MODEL_PATH} \
--report_to "wandb" \
--wandb_key ${WANDB_KEY} \
--overwrite_output_dir true \
--train_dataset_name "OpenSound/CapSpeech" \
--train_split_name "train_SFT_CapTTS" \
--eval_dataset_name "OpenSound/CapSpeech" \
--eval_split_name "validation_SFT_CapTTS" \
--librittsr_dir ${LIBRITTSR_WAV_DIR} \
--other_dir ${OTHER_WAV_DIR} \
--max_eval_samples 96 \
--per_device_eval_batch_size 32 \
--target_audio_column_name "audio_path" \
--description_column_name "caption" \
--source_column_name "source" \
--prompt_column_name "text" \
--max_duration_in_seconds 20 \
--min_duration_in_seconds 3 \
--max_text_length 600 \
--preprocessing_num_workers 32 \
--do_train true \
--num_train_epochs 5 \
--gradient_accumulation_steps 6 \
--gradient_checkpointing false \
--per_device_train_batch_size 4 \
--learning_rate 0.0001 \
--adam_beta1 0.9 \
--adam_beta2 0.99 \
--weight_decay 0.01 \
--lr_scheduler_type "constant_with_warmup" \
--warmup_steps 1000 \
--logging_steps 200 \
--freeze_text_encoder true \
--per_device_eval_batch_size 4 \
--audio_encoder_per_device_batch_size 24 \
--dtype "float16" \
--seed 456 \
--output_dir ${OUTPUT_DIR} \
--temporary_save_to_disk ${TEMPORY_SAVE_TO_DISK} \
--save_to_disk ${SAVE_TO_DISK} \
--dataloader_num_workers 32 \
--do_eval \
--evaluation_strategy steps \
--eval_steps 2000 \
--save_steps 2000 \
--group_by_length true
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