Arithmetic SoRL Models

Model checkpoints for the SoRL Arithmetic Interpretability Study.

Small Qwen3 transformers (3L/4H/512d, ~168M params) trained from scratch on integer

addition and subtraction, with and without SoRL abstraction tokens.

Goal

Show that SoRL externalizes arithmetic reasoning mechanisms (carry, borrow circuits)

as explicit abstraction tokens — observable and intervenable without activation-level tooling.

Architecture

Tiny Qwen3 from random init via SorlModelWrapper.from_scratch:

hidden_size=512, num_hidden_layers=3, num_attention_heads=4
intermediate_size=2048, vocab_size=151936

Experiment subfolders

Each subfolder contains a trained model + train_config.json + metrics.json.

| Subfolder | Task | Mode | Abstract Vocab |

|---|---|---|---|

| add_baseline | addition | SFT baseline | 0 |

| add_sorl_abs4 | addition | SoRL v6 | 4 |

| add_sorl_abs8 | addition | SoRL v6 | 8 |

| ... | | | |

Related

• Training data: thoughtworks/arithmetic-sorl-data
• Code: mod_gpt/arithmetic/
• SoRL paper: Yu & Abdullah, "Intention-Level Alignment with Weak Supervision" (2025)