Model: rommeltest/onereason_full_wuliao Source: Original Platform
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onereason_full_wuliao
This model is a full-parameter fine-tuned OneReason-0.8B checkpoint trained on the full_add_wuliao dataset. This repository publishes checkpoint 600.
Model description
The model is based on the Qwen3 causal language model architecture and is trained for OneReason multi-domain recommendation and text-to-SID tasks.
Intended uses & limitations
This checkpoint is intended for research and evaluation on OneReason-format recommendation and SID generation tasks.
Training data
The training dataset combines multi-domain user-history recommendation examples with material text-to-SID examples for product, live, advertisement, and video domains.
Training procedure
Key training hyperparameters:
- learning rate: 1e-5
- train batch size per device: 1
- eval batch size per device: 1
- gradient accumulation steps: 8
- number of devices: 4
- total train batch size: 32
- seed: 42
- scheduler: linear
- warmup ratio: 0.05
- configured epochs: 3
Framework versions
- Transformers 5.3.0
- PyTorch 2.4.1
- Tokenizers 0.22.2
Description
Languages
Jinja
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