mirror of
https://github.com/SakanaAI/doc-to-lora.git
synced 2026-07-23 17:01:04 +02:00
31 lines
1.3 KiB
Bash
31 lines
1.3 KiB
Bash
#!/bin/bash
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#SBATCH --job-name=gemma_llama_instruct
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#SBATCH --partition=a3
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#SBATCH --nodes=1
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#SBATCH --gpus=4
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#SBATCH --output=outputs/%x-%j.out
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#SBATCH --error=outputs/%x-%j.out
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# module load
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# module load cuda/12.1
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# module load cudnn/8.9.7
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# module load nccl/cuda-12.1/2.18.3
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# module load hpcx/2.20
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# export OMP_NUM_THREADS=24
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# export TRITON_CACHE_DIR=/tmp/.triton/
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. ~/miniconda3/etc/profile.d/conda.sh
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conda activate /home/rujikorn_sakana_ai/.conda/envs/ctx-to-lora
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# eval "$@"
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accelerate launch --num_processes=4 --gradient_accumulation_steps=8 --gradient_clipping=1.0 \
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--gpu_ids all --main_process_port 29562 intx_sft.py configs/pretrain_all_xl.yaml \
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--model_name_or_path=google/gemma-2-2b-it --num_train_epochs=5.1 --per_device_train_batch_size=32 \
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--gradient_accumulation_steps=8 --per_device_eval_batch_size=32 --exp_setup=hyper_lora --aggregator_type=perceiver \
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--target_modules=down_proj \
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--num_blocks=1 --num_self_attends_per_block=8 --num_latent_factor=16 \
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--eval_steps=5000 --save_steps=5000 --learning_rate=2e-5 --lora_dropout=0.0 \
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--neftune_noise_alpha=5 --use_light_weight_lora=False \
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--load_best_model_at_end=True --metric_for_best_model=pwc_loss --add_negative_prompt=False \
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--add_repeat_prompt=True \
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--use_sequence_packing=True --ctx_encoder_model_name_or_path=meta-llama/Llama-3.2-3B-Instruct
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