RATs40K Adapter for ChatTime

This folder adapts ChatTime to the RATs40K univariate anomaly QA task.

It intentionally uses the numeric Observation field only. It does not use FigurePath, so the resulting baseline should be compared with numeric-only Time-RA settings rather than VLM image-input settings.

Required inputs

MODEL_PATH: local ChatTime model directory. This is required by default.
PYTHON_BIN: Python executable. The shell scripts default to /dev/shm/suiqk/conda_envs/scalerag-ts-v4/bin/python.
DATA_PATH: defaults to /mnt/share01/sqk/datasets/RATs40K/RATs-Uni-TSImage_Reason.json.

The scripts do not download HuggingFace weights unless ALLOW_HF_DOWNLOAD=1 is set explicitly.

The default precision is FP16 because the configured four-GPU machine uses Tesla V100 GPUs. SFT defaults to regular FP16 LoRA with LOAD_IN_4BIT=0, PER_DEVICE_TRAIN_BATCH_SIZE=1, and GRADIENT_ACCUMULATION_STEPS=16.

Evaluation defaults to EVAL_BATCH_SIZE=4 per GPU. With four GPUs, the maximum global evaluation batch size is 16.

The task prompt is aligned with Time-RA's univariate USER_DETECTION_PROMPT; ChatTime still receives the normalized/discretized series through its native ### Input section. Evaluation checks prompt token lengths and fails instead of truncating. Defaults are MAX_INPUT_TOKENS=3936, MAX_NEW_TOKENS=160, and MAX_SEQ_LENGTH=4096 for SFT.

Zero-shot

cd /mnt/share01/sqk/ChatTime
MODEL_PATH=/mnt/share01/sqk/models/ChatTime-1-7B-Chat \
bash rats40k_adapter/run_zeroshot_4gpu.sh

SFT + Eval

cd /mnt/share01/sqk/ChatTime
MODEL_PATH=/mnt/share01/sqk/models/ChatTime-1-7B-Chat \
bash rats40k_adapter/run_sft_4gpu.sh

Zero-shot Then SFT + Eval

cd /mnt/share01/sqk/ChatTime
bash rats40k_adapter/run_zeroshot_then_sft_4gpu.sh

Saved Results

Zero-shot outputs: /mnt/share01/sqk/ChatTime/rats40k_adapter/outputs/pipeline_20260608_175250/zeroshot
SFT outputs: /mnt/share01/sqk/ChatTime/rats40k_adapter/outputs/pipeline_20260608_175250/sft

Useful smoke-test knobs:

MAX_TRAIN_SAMPLES=128 MAX_EVAL_SAMPLES=64 bash rats40k_adapter/run_zeroshot_then_sft_4gpu.sh
MAX_TRAIN_SAMPLES=128 MAX_EVAL_SAMPLES=64 bash rats40k_adapter/run_sft_4gpu.sh
MAX_EVAL_SAMPLES=64 bash rats40k_adapter/run_zeroshot_4gpu.sh