darkpowerxo
a67eeb2e7d
- finetune.py: argparse CLI with all config flags, CSV data loading, chronological train/val split, and full training pipeline Usage: python -m peft.finetune --data_path data.csv --value_col y Multi-GPU: torchrun --nproc_per_node=4 -m peft.finetune ... - finetune.sh: env-var driven launch script for single/multi-GPU Usage: DATA_PATH=data.csv NUM_GPUS=4 bash peft/finetune.sh
74 lines
2.4 KiB
Bash
74 lines
2.4 KiB
Bash
#!/usr/bin/env bash
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# ============================================================================
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# Example launch script for TimesFM 2.5 PEFT fine-tuning.
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#
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# Single GPU:
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# bash peft/finetune.sh
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#
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# Multi-GPU (e.g. 4 GPUs):
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# NUM_GPUS=4 bash peft/finetune.sh
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# ============================================================================
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set -euo pipefail
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NUM_GPUS="${NUM_GPUS:-1}"
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# --- Data -------------------------------------------------------------------
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DATA_PATH="${DATA_PATH:-data.csv}" # path to your CSV
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ID_COL="${ID_COL:-}" # series-id column (long format), leave empty for wide
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VALUE_COL="${VALUE_COL:-}" # value column (long format), leave empty for wide
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CONTEXT_LEN="${CONTEXT_LEN:-512}"
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HORIZON_LEN="${HORIZON_LEN:-128}"
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STRIDE="${STRIDE:-32}"
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VAL_SPLIT="${VAL_SPLIT:-0.2}"
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# --- Adapter ----------------------------------------------------------------
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ADAPTER_TYPE="${ADAPTER_TYPE:-lora}" # lora | dora
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LORA_RANK="${LORA_RANK:-8}"
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LORA_ALPHA="${LORA_ALPHA:-16}"
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TARGET_MODULES="${TARGET_MODULES:-all}" # all | attention | ffn
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NUM_ADAPTER_LAYERS="${NUM_ADAPTER_LAYERS:-4}" # 0=all 20, advisor recommends 2-4
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# --- Training ---------------------------------------------------------------
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NUM_EPOCHS="${NUM_EPOCHS:-10}"
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BATCH_SIZE="${BATCH_SIZE:-32}"
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LR="${LR:-1e-4}"
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MIXED_PRECISION="${MIXED_PRECISION:-no}" # no | fp16 | bf16
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# --- Logging / checkpoint ---------------------------------------------------
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CHECKPOINT_DIR="${CHECKPOINT_DIR:-./peft_checkpoints}"
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# ============================================================================
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CMD_ARGS=(
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peft/finetune.py
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--data_path "$DATA_PATH"
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--context_len "$CONTEXT_LEN"
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--horizon_len "$HORIZON_LEN"
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--stride "$STRIDE"
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--val_split "$VAL_SPLIT"
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--adapter_type "$ADAPTER_TYPE"
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--lora_rank "$LORA_RANK"
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--lora_alpha "$LORA_ALPHA"
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--target_modules "$TARGET_MODULES"
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--num_adapter_layers "$NUM_ADAPTER_LAYERS"
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--train_output_head
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--num_epochs "$NUM_EPOCHS"
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--batch_size "$BATCH_SIZE"
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--learning_rate "$LR"
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--mixed_precision "$MIXED_PRECISION"
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--checkpoint_dir "$CHECKPOINT_DIR"
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)
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# Optional columns.
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[[ -n "$ID_COL" ]] && CMD_ARGS+=(--id_col "$ID_COL")
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[[ -n "$VALUE_COL" ]] && CMD_ARGS+=(--value_col "$VALUE_COL")
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if [[ "$NUM_GPUS" -gt 1 ]]; then
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echo "Launching multi-GPU training on $NUM_GPUS GPUs …"
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torchrun --nproc_per_node="$NUM_GPUS" "${CMD_ARGS[@]}"
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else
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echo "Launching single-GPU training …"
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python "${CMD_ARGS[@]}"
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fi
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