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CACHE_DIR="path/to/pretrained/weight"
RESUME="audio_language.pt"
ANNOTATION="path/to/data"
# this script is for 512 total batch_size (n(16) GPUs * batch_size(32) * accum_freq(1))
cd /path/to/LanguageBind
TORCH_DISTRIBUTED_DEBUG=DETAIL HF_DATASETS_OFFLINE=1 TRANSFORMERS_OFFLINE=1 torchrun --nnodes=2 --nproc_per_node 8 \
-m main \
--train-data ${ANNOTATION} \
--train-num-samples 4800000 \
--clip-type "al" --num_mel_bins 126 --target_length 1036 --audio_sample_rate 16000 --audio_mean -4.2677393 --audio_std 4.5689974 \
--lock-text --lock-image --text-type "polish_mplug" \
--init-temp 0.07 --learn-temp \
--model "ViT-L-14" --cache-dir ${CACHE_DIR} \
--convert_to_lora --lora_r 16 \
--lr 1e-3 --coef-lr 1 \
--beta1 0.9 --beta2 0.98 --wd 0.2 --eps 1e-6 \
--num-frames 1 --force-patch-dropout 0.1 \
--epochs 16 --batch-size 16 --accum-freq 4 --warmup 2000 \
--precision "amp" --workers 10 --video-decode-backend "imgs" \
--save-frequency 1 --log-every-n-steps 20 --report-to "tensorboard" --resume ${RESUME} \
--do_eval \
--val_a_cls_data "ESC50" "VGGSound" "Audioset" \
--val_al_ret_data "Clotho" "Audiocaps"
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