Downloads · 30 days
8
9% of all-time downloads
OldEngine/qwen3-0.6b-bitext-ticket-router-sft
qwen3-0.6b-bitext-ticket-router-sft is a machine learning model from OldEngine. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
LoRA SFT adapter for routing customer-support tickets to the top 12 intents by frequency from the first 50000 rows of bitext/Bitext-customer-support-llm-chatbot-training-dataset.
Downloads · 30 days
8
9% of all-time downloads
All-time downloads
90
Public
Repo size
51.9 MB
Likes
0
Public
Click a slice to open those files.
.safetensors40.4 MB · 76%
From the Hugging Face model README
LoRA SFT adapter for routing customer-support tickets to the top 12 intents
by frequency from the first 50000 rows of bitext/Bitext-customer-support-llm-chatbot-training-dataset.
The training prompt enforces strict JSON-only output:
system: You are a customer-support ticket router. Return only one strict JSON object...
user: <ticket text>
assistant: {"intent":"<label>","confidence":0.99,"reason":"<short reason>"}
Held-out eval examples: 1000
{
"accuracy": 0.999,
"valid_json_rate": 1.0,
"schema_pass_rate": 1.0,
"accuracy_on_schema": 0.999,
"num_eval_examples": 1000,
"num_train_examples": 10793,
"top_intents": [
"check_invoice",
"complaint",
"contact_customer_service",
"edit_account",
"switch_account",
"check_payment_methods",
"contact_human_agent",
"delivery_period",
"get_invoice",
"newsletter_subscription",
"payment_issue",
"registration_problems"
],
"base_model": "Qwen/Qwen3-0.6B",
"dataset": "bitext/Bitext-customer-support-llm-chatbot-training-dataset",
"max_steps": 800,
"learning_rate": 0.0002,
"warmup_ratio": 0.03,
"max_length": 512
}