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muat-fourier-3-classifier
maximuspowers/muat-fourier-3-classifier
muat-fourier-3-classifier is a machine learning model from maximuspowers. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model was trained to classify which patterns a subject model was trained on, based on neuron activation signatures.
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.pt5.1 MB · 66%
At a glance
- Access
- Public
- Created
- Dec 2, 2025
- Updated
- Dec 2, 2025
- SHA
- 94c25355
Datasets
Model card
From the Hugging Face model README
Pattern Classifier
This model was trained to classify which patterns a subject model was trained on, based on neuron activation signatures.
Dataset
- Training Dataset: maximuspowers/muat-fourier-3
- Input Mode: signature
- Number of Patterns: 14
Patterns
The model predicts which of the following 14 patterns the subject model was trained on:
palindromesorted_ascendingsorted_descendingalternatingcontains_abcstarts_withends_withno_repeatshas_majorityincreasing_pairsdecreasing_pairsvowel_consonantfirst_last_matchmountain_pattern
Model Architecture
- Signature Encoder: [512, 256, 256, 128]
- Activation: relu
- Dropout: 0.2
- Batch Normalization: True
Training Configuration
- Optimizer: adam
- Learning Rate: 0.001
- Batch Size: 16
- Loss Function: BCE with Logits (with pos_weight for training, unweighted for validation)
Test Set Performance
- F1 Macro: 0.2985
- F1 Micro: 0.2756
- Hamming Accuracy: 0.7292
- Exact Match Accuracy: 0.0250
- BCE Loss: 0.4709
Per-Pattern Performance (Test Set)
| Pattern | Precision | Recall | F1 Score |
|---|---|---|---|
| palindrome | 14.1% | 90.0% | 24.4% |
| sorted_ascending | 49.1% | 62.1% | 54.8% |
| sorted_descending | 12.9% | 89.7% | 22.5% |
| alternating | 18.6% | 69.9% | 29.4% |
| contains_abc | 26.4% | 73.7% | 38.8% |
| starts_with | 9.6% | 84.7% | 17.3% |
| ends_with | 15.1% | 82.2% | 25.5% |
| no_repeats | 12.7% | 59.3% | 21.0% |
| has_majority | 56.2% | 34.6% | 42.9% |
| increasing_pairs | 27.6% | 66.7% | 39.0% |
| decreasing_pairs | 16.5% | 80.8% | 27.4% |
| vowel_consonant | 12.1% | 50.0% | 19.5% |
| first_last_match | 21.1% | 78.1% | 33.2% |
| mountain_pattern | 13.8% | 54.3% | 22.0% |
Usage
import torch
from huggingface_hub import hf_hub_download
# Download the model
checkpoint_path = hf_hub_download(repo_id='maximuspowers/muat-fourier-3-classifier', filename='best_model.pt')
checkpoint = torch.load(checkpoint_path)
- Created
- Dec 2, 2025
- Updated
- Dec 2, 2025