scripts/finetune_llm_speech_decoder.sh

#!/bin/bash

# it currently supports for batch = 1 only.

MODEL_PATH=/data1/speech/anhnmt2/Speech2Speech/LLaMA-Omni/models/llm/Qwen2.5-3B-Instruct
SPEECH_ENCODER=/data1/speech/anhnmt2/Speech2Speech/LLaMA-Omni/models/speech_encoder/whisper-medium
SPEECH_ADAPTER=/data1/speech/anhnmt2/Speech2Speech/half-streaming-speech-nlp/checkpoints/omni_whisper-medium_Qwen2.5-3B_pretrained-asr/speech_projector.bin
PROMPT_VERSION=qwen
DATA_PATH=/data1/speech/anhnmt2/dataset/s2s/english/qna/train_20250106_fc_mixed_tgt_units.jsonl
DEV_PATH=/data1/speech/anhnmt2/dataset/s2s/english/qna/dev_20250106_fc_mixed_tgt_units.jsonl
CACHE_DIR="../output/cached_sft_speech_decoder_all_20250103"

deepspeed ../omni_speech/train/train_mem.py \
    --deepspeed zero2.json \
    --model_name_or_path $MODEL_PATH \
    --version $PROMPT_VERSION \
    --data_path $DATA_PATH \
    --dev_path $DEV_PATH \
    --cache_dir $CACHE_DIR \
    --speech_encoder $SPEECH_ENCODER  \
    --mel_size 80 \
    --speech_encoder_hidden_size 1024 \
    --speech_encoder_type whisper \
    --pretrain_speech_projector $SPEECH_ADAPTER \
    --bf16 True \
    --output_dir ../checkpoints/omni_whisper-medium_Qwen2.5-3B_pretrained-sft-fc_speech_decoder_fixed_all \
    --num_train_epochs 3 \
    --per_device_train_batch_size 1 \
    --per_device_eval_batch_size 1 \
    --gradient_accumulation_steps 4 \
    --evaluation_strategy "steps" \
    --save_strategy "steps" \
    --eval_steps 2000 \
    --save_steps 2000 \
    --save_total_limit 1 \
    --learning_rate 1e-5 \
    --weight_decay 0. \
    --warmup_ratio 0.03 \
    --lr_scheduler_type "cosine" \
    --logging_steps 1 \
    --tf32 True \
    --model_max_length 1024 \
    --gradient_checkpointing True \
    --dataloader_num_workers 8 \
    --has_tgt_units True \
    --ctc_loss_weight 2.0


# MODEL_PATH=/data1/speech/anhnmt2/Speech2Speech/half-streaming-speech-nlp/checkpoints/omni_whisper-medium_Qwen2.5-3B_pretrained-sft-fc
# SPEECH_ENCODER=/data1/speech/anhnmt2/Speech2Speech/LLaMA-Omni/models/speech_encoder/whisper-medium
# PROMPT_VERSION=qwen
# DATA_PATH=/data1/speech/anhnmt2/dataset/s2s/english/qna/moss/moss_100K_phase3_tgt_units_processed.jsonl
# # DEV_PATH=/data1/speech/anhnmt2/dataset/s2s/english/qna/dev_20250106_fc_mixed_tgt_units.jsonl
# CACHE_DIR="../output/cached_sft_speech_decoder_all_20250103"

# deepspeed ../omni_speech/train/train_mem.py \
#     --deepspeed zero2.json \
#     --model_name_or_path $MODEL_PATH \
#     --version $PROMPT_VERSION \
#     --data_path $DATA_PATH \
#     --cache_dir $CACHE_DIR \
#     --speech_encoder $SPEECH_ENCODER  \
#     --mel_size 80 \
#     --speech_encoder_hidden_size 1024 \
#     --speech_encoder_type whisper \
#     --bf16 True \
#     --output_dir ../checkpoints/omni_whisper-medium_Qwen2.5-3B_pretrained-sft-fc_speech_decoder_all \
#     --num_train_epochs 5 \
#     --per_device_train_batch_size 1 \
#     --per_device_eval_batch_size 1 \
#     --gradient_accumulation_steps 4 \
#     --evaluation_strategy "no" \
#     --save_strategy "steps" \
#     --save_steps 10000 \
#     --save_total_limit 1 \
#     --learning_rate 1e-4 \
#     --weight_decay 0. \
#     --warmup_ratio 0.03 \
#     --logging_steps 1 \
#     --tf32 True \
#     --model_max_length 2048 \
#     --gradient_checkpointing True \
#     --dataloader_num_workers 8 \
#     --has_tgt_units True \
#     --ctc_loss_weight 10.0