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#!/bin/bash |
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MODEL_PATH=/data1/speech/anhnmt2/Speech2Speech/LLaMA-Omni/models/llm/Qwen2.5-3B-Instruct |
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SPEECH_ENCODER=/data1/speech/anhnmt2/Speech2Speech/LLaMA-Omni/models/speech_encoder/whisper-medium |
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PROMPT_VERSION=qwen |
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DATA_PATH=/data1/speech/anhnmt2/dataset/s2s/english/asr/dataset/train_asr_eng_5M.jsonl |
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DEV_PATH=/data1/speech/anhnmt2/dataset/s2s/english/asr/dataset/dev_asr_libri_spgi.jsonl |
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CACHE_DIR="../output/cached_asr_full" |
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AUGMENT_PATH="/data1/speech/anhnmt2/dataset/s2s/augment/noise_list_non_speech.txt" |
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deepspeed ../omni_speech/train/train_mem.py \ |
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--deepspeed zero2.json \ |
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--model_name_or_path $MODEL_PATH \ |
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--version $PROMPT_VERSION \ |
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--data_path $DATA_PATH \ |
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--dev_path $DEV_PATH \ |
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--cache_dir $CACHE_DIR \ |
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--speech_encoder $SPEECH_ENCODER \ |
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--mel_size 80 \ |
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--speech_encoder_hidden_size 1024 \ |
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--speech_encoder_type whisper \ |
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--bf16 True \ |
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--output_dir ../checkpoints/omni_whisper-medium_Qwen2.5-3B_pretrained-asr-5M \ |
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--num_train_epochs 4 \ |
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--tune_speech_projector True \ |
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--per_device_train_batch_size 16 \ |
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--per_device_eval_batch_size 4 \ |
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--gradient_accumulation_steps 2 \ |
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--evaluation_strategy "steps" \ |
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--save_strategy "steps" \ |
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--eval_steps 2000 \ |
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--save_steps 2000 \ |
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--save_total_limit 1 \ |
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--learning_rate 1e-3 \ |
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--weight_decay 0. \ |
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--warmup_ratio 0.03 \ |
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--lr_scheduler_type "cosine" \ |
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--logging_steps 1 \ |
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--tf32 True \ |
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--model_max_length 4096 \ |
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--gradient_checkpointing True \ |
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--dataloader_num_workers 8 |
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