README.md

metadata

license: apache-2.0
datasets:
  - ustc-zyt/time-r1-data
language:
  - en
metrics:
  - mse
  - mae
base_model:
  - Qwen/Qwen2.5-7B

🧠 Time-R1 Reinforced Model Weights

These are the official reinforcement learning (RL) fine-tuned model checkpoints for the paper: "Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs".

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📦 Model Details

• Base Model: Qwen2.5-7B
• Tuning Framework: Verl + LLaMA Factory
• Final Stage: Trained using GRIP (Group-based Relative Importance Policy optimization)
• Objective: Multi-horizon time series forecasting with structured reasoning

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📦 Files Included

This model follows the standard Hugging Face transformers format and uses the efficient safetensors backend.

Time-R1/
├── config.json
├── generation_config.json
├── model.safetensors.index.json
├── model-00001-of-00004.safetensors
├── model-00002-of-00004.safetensors
├── model-00003-of-00004.safetensors
├── model-00004-of-00004.safetensors
├── tokenizer_config.json
├── tokenizer.json
└── vocab.json

✅ Fully compatible with Hugging Face transformers and AutoModelForCausalLM.