File size: 1,194 Bytes
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Project structure
=================
train.py
test.py
requirements.txt
run_all.sh
run_all.bat
README.txt
sample/
data/
train_four_output.jsonl
validation_four_output.jsonl
test_four_output.jsonl
.cache/
huggingface/
models/
(training output will be written here)
Training
========
1. Install dependencies:
pip install -r requirements.txt
2. Make sure CUDA + a compatible NVIDIA GPU/bitsandbytes setup is available.
3. Train:
python train.py
4. Evaluate:
python test.py --adapter "models/telecom-qwen-four-output" --test "sample/data/test_four_output.jsonl" --samples 0
Debug:
======
python test.py --adapter "models/telecom-qwen-four-output" --test "sample/data/test_four_output.jsonl" --samples 10 --debug
Expected response sections
===========================
Probable Root Cause:
Explanation:
Recommendation:
Fault Severity:
fault_severity=0|1|2
Important
=========
Root Cause, Explanation, and Recommendation targets are structured,
data-constrained synthetic targets because the source dataset contains
fault_severity labels but not engineer-validated root-cause/remediation
annotations. See README.txt.
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