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config.json

@@ -4,6 +4,6 @@
     "AutoConfig": "configuration_sm_subgroup_classifier.SmSubgroupClassifierConfig",
     "AutoModel": "modeling_sm_subgroup_classifier.SmSubgroupClassifier"
   },
-  "available_models": ["fi_na-nb"],
+  "available_models": ["fi_NA-nb"],
   "model_type": "sm_subgroup_classifier"
 }

example.py

@@ -10,6 +10,6 @@ sm_classifier = AutoModel.from_pretrained(
 embedding = np.random.rand(1024).astype(np.float32)
 
 # Use - model automatically discovers what's available
-result = sm_classifier("fi", "na-nb", embedding)
+result = sm_classifier("fi", "NA-nb", embedding)
 
 print(result)

fi_NA-nb/metadata.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dcebec77f65e7a4edab907a0680e37b2ee48f4c384a7ff2dee7d00dc88f60749
+size 76

fi_NA-nb/model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:da0a8b8d946ea6c2bb415f6f36b9cd5b08c5fda7c1faa67c44d093d2fdcb46e4
+size 9055

fi_NA-nb/scaler.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4193fa89889dce247553136aab6945fbbc389254eb8c9d203588a7fb04cdd7a1
+size 25191

fi_NA-nb/training_details.txt

@@ -0,0 +1,39 @@
+Training Details for fi_NA-nb
+========================================
+
+Language: fi
+Model Name: NA-nb
+Training Date: 2025-09-18 16:12:26
+
+Data Summary:
+- Total samples: 218088
+- Training samples: 174470
+- Test samples: 43618
+- Embedding dimension: 1024
+
+Classes:
+- Number of classes: 2
+- Class names: with_comments, general
+- Class distribution: {'with_comments': 24862, 'general': 193226}
+
+Cross-Validation Results:
+- CV folds: 5
+- CV scores: [0.9941823809250874, 0.9942396973691752, 0.9939817733707801, 0.9939817733707801, 0.9939817733707801]
+- CV mean: 0.9941
+- CV std: 0.0001
+- CV confidence interval: 0.9941 ± 0.0002
+
+Final Performance:
+- Test accuracy: 0.9945
+
+Model Configuration:
+- Algorithm: Logistic Regression
+- Regularization (C): 1.0
+- Feature scaling: StandardScaler
+- Random state: 42
+
+Files:
+- Classifier: model.pkl
+- Scaler: scaler.pkl
+- Metadata: metadata.pkl
+- This file: training_details.txt