Job Tag Embedding Model (Dev)
Fine-tuned embedding model for job category recommendation based on BAAI/bge-large-zh-v1.5.
Model Details
- Base Model: 1111DataScience/job_tag_embedding
- Training Data: Job titles and category pairs
- Training Steps: 1,920 (3 epochs)
- Final Loss: 2.126
Usage
from FlagEmbedding import FlagModel
# Load model
model = FlagModel('1111DataScience/job_tag_embedding_dev', use_fp16=True)
# Encode query (job title)
query_embedding = model.encode_queries(["內外場儲備幹部"])
# Encode candidates (job categories)
candidate_embeddings = model.encode([
"儲備幹部",
"餐廚助手",
"餐飲服務人員"
])
# Calculate similarity
similarities = query_embedding @ candidate_embeddings.T
Training Command
torchrun --nproc_per_node 1 \
-m FlagEmbedding.finetune.embedder.encoder_only.base \
--model_name_or_path 1111DataScience/job_tag_embedding \
--cache_dir ./cache/model \
--train_data training_data.jsonl \
--output_dir ./output