Download examples/sin_regression.json from oldman-dev/stanno: direct link, hf CLI and curl.
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https://huggingface.co/oldman-dev/stanno/resolve/main/examples/sin_regression.json
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hf download hf://oldman-dev/stanno/examples/sin_regression.json
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curl -L -o sin_regression.json https://huggingface.co/oldman-dev/stanno/resolve/main/examples/sin_regression.json
955 Bytes
| { | |
| "_comment": "Sin regression example. STANNO approximates sin(2πx) on x∈[0,1]. FixedTrainerNet is equivalent to vanilla SGD — lr=0.05 converges to MAE~0.15. For MAE<0.01, use Adam (not available in FixedTrainer) or LocalRuleTrainerNet after meta-training.", | |
| "stanno": { | |
| "layers": [1, 32, 1], | |
| "trainer_type": "fixed", | |
| "learning_rate": 0.05, | |
| "feedback_projection": "repeat" | |
| }, | |
| "data": { | |
| "format": "builtin:sin", | |
| "n_samples": 512, | |
| "split_ratio": 0.8, | |
| "normalize": false | |
| }, | |
| "fit": { | |
| "epochs": 300, | |
| "batch_size": 64, | |
| "log_every": 30, | |
| "patience": 20 | |
| }, | |
| "save_path": "examples/sin_regression.stanno.pkl", | |
| "dream": [ | |
| { | |
| "num_steps": 32, | |
| "noise_sigma": 0.0, | |
| "blind_inputs": false | |
| }, | |
| { | |
| "num_steps": 32, | |
| "noise_sigma": 0.1, | |
| "blind_inputs": false | |
| }, | |
| { | |
| "num_steps": 32, | |
| "noise_sigma": 0.3, | |
| "blind_inputs": true | |
| } | |
| ] | |
| } | |