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run_zero_shot.sh
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run_zero_shot.sh
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# # Wav2Vec 2.0 Multilingual
# CUDA_VISIBLE_DEVICES=0 python zero_shot.py \
# --model_name_or_path=CAiRE/wav2vec2-large-xlsr-53-cantonese \
# --train_manifest_path=data/ubc_cantonese_english_asr/preprocessed_train_metadata.csv \
# --valid_manifest_path=data/ubc_cantonese_english_asr/preprocessed_valid_metadata.csv \
# --test_manifest_path=data/ubc_cantonese_english_asr/preprocessed_test_metadata.csv \
# --cache_dir_name ./baselines/cache/CAiRE/wav2vec2-large-xlsr-53-cantonese \
# --preprocessing_num_workers=16 \
# --audio_column_name=audio_path --text_column_name=text_path \
# --eval_accumulation_steps=10 \
# --per_device_train_batch_size=8 --per_device_eval_batch_size=16 \
# --dataloader_num_workers=8 --dataloader_pin_memory --group_by_length \
# --seed=14045 --num_train_epochs=5 --learning_rate=5e-5 --output_dir=./baselines/eval/zero-shot/yue \
# --lang="cs-eng,cs-yue,eng,yue"
CUDA_VISIBLE_DEVICES=7 python zero_shot.py \
--model_name_or_path=scottykwok/wav2vec2-large-xlsr-cantonese \
--train_manifest_path=data/ubc_cantonese_english_asr/preprocessed_train_metadata.csv \
--valid_manifest_path=data/ubc_cantonese_english_asr/preprocessed_valid_metadata.csv \
--test_manifest_path=data/ubc_cantonese_english_asr/preprocessed_test_metadata.csv \
--cache_dir_name ./baselines/cache/scottykwok/wav2vec2-large-xlsr-cantonese \
--preprocessing_num_workers=16 \
--audio_column_name=audio_path --text_column_name=text_path \
--eval_accumulation_steps=30 \
--per_device_train_batch_size=8 --per_device_eval_batch_size=8 \
--dataloader_num_workers=8 --dataloader_pin_memory --group_by_length \
--seed=14045 --num_train_epochs=5 --learning_rate=5e-5 --output_dir=./baselines/eval/zero-shot/scotty \
--lang="cs-eng,cs-yue,eng,yue"
# CUDA_VISIBLE_DEVICES=4 python harmonize_train.py --model=CAiRE/wav2vec2-large-xlsr-53-cantonese \
# --name="Wav2Vec2" \
# --train-manifest-list=data/ubc_cantonese_english_asr/preprocessed_train_metadata.csv \
# --valid-manifest-list=data/ubc_cantonese_english_asr/preprocessed_valid_metadata.csv \
# --test-manifest-list=data/ubc_cantonese_english_asr/preprocessed_test_metadata.csv \
# --num-workers 4 --logging-strategy steps --logging-steps 10 --report-to "tensorboard" --lr 1e-20 --meta-lr 1e-20 \
# --k-train=4 --k-valid=4 --epochs 50 --save-every 10 --save-total-limit 3 --evaluate-every 5 \
# --lang="cs-yue,cs-eng,yue,eng" --loss="ctc" \
# --cache-dir="cache_z/CAiRE/wav2vec2-large-xlsr-53-cantonese" --dropout 0.1 --clip \
# --output-dir="save_z" \
# --cuda --verbose --copy-grad
# CUDA_VISIBLE_DEVICES=6 python harmonize_train.py --model=CAiRE/wav2vec2-large-xlsr-53-cantonese \
# --name="Wav2Vec2" \
# --train-manifest-list=data/ubc_cantonese_english_asr/preprocessed_train_metadata.csv \
# --valid-manifest-list=data/ubc_cantonese_english_asr/preprocessed_valid_metadata.csv \
# --test-manifest-list=data/ubc_cantonese_english_asr/preprocessed_test_metadata.csv \
# --num-workers 4 --logging-strategy steps --logging-steps 10 --report-to "tensorboard" --lr 1e-20 --meta-lr 1e-20 \
# --k-train=4 --k-valid=4 --epochs 50 --save-every 10 --save-total-limit 3 --evaluate-every 5 \
# --lang="cs-yue,cs-eng,yue,eng" --loss="ctc" \
# --cache-dir="cache_z/CAiRE/wav2vec2-large-xlsr-53-cantonese" --dropout 0.1 --clip \
# --output-dir="save_z" \
# --cuda --verbose --copy-grad --pcgrad