fix: notebooks

2025-10-05 23:23:58 +02:00
parent 137dea7fe5
commit 8f90fdd625
16 changed files with 5006 additions and 6362 deletions
@@ -10,12 +10,14 @@ million names from the Democratic Republic of Congo (DRC) annotated with gender

 ### Installation & Setup

-**Unix based**
 ```bash
-curl -LsSf https://astral.sh/uv/install.sh | sh
-
 git clone https://github.com/bernard-ng/drc-ners-nlp.git
 cd drc-ners-nlp
+```
+
+**Linux**
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh

 uv sync
 ```
@@ -23,12 +25,9 @@ uv sync
 **Macos & windows**
 ```bash
 docker compose build
-docker compose run --rm app
-docker compose run --rm app ners pipeline run --env=production
-docker compose run --rm app ners research train --name=lightgbm --type=baseline --env=production
-docker compose run --rm --service-ports app ners web run --env=production
+docker compose exec app bash
 ```
-
+s
 ## Data Processing

 This project includes a robust data processing pipeline designed to handle large datasets efficiently with batching,
@@ -118,6 +117,10 @@ experiments and make predictions without needing to understand the underlying co
 uv run ners web run --env="production"
 ```

+```bash
+docker compose run --rm --service-ports app ners web run --env=production
+```
+
 ## Contributors

 <a href="https://github.com/bernard-ng/drc-ners-nlp/graphs/contributors" title="show all contributors">
@@ -1,412 +0,0 @@
-baseline_experiments:
-  # BiGRU Models (GPU-enabled)
-  - name: "bigru"
-    description: "Baseline BiGRU with full name features (GPU)"
-    model_type: "bigru"
-    features: [ "full_name" ]
-    model_params:
-      embedding_dim: 64
-      gru_units: 32
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "bigru", "gpu" ]
-
-  - name: "bigru_native"
-    description: "Baseline BiGRU with native name features (GPU)"
-    model_type: "bigru"
-    features: [ "native_name" ]
-    model_params:
-      embedding_dim: 64
-      gru_units: 32
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "bigru", "native", "gpu" ]
-
-  - name: "bigru_surname"
-    description: "Baseline BiGRU with surname features (GPU)"
-    model_type: "bigru"
-    features: [ "surname" ]
-    model_params:
-      embedding_dim: 64
-      gru_units: 32
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "bigru", "surname", "gpu" ]
-
-  ## CNN Models (GPU-enabled)
-  - name: "cnn"
-    description: "Baseline CNN with character patterns (GPU)"
-    model_type: "cnn"
-    features: [ "full_name" ]
-    model_params:
-      embedding_dim: 64
-      filters: 64
-      kernel_size: 3
-      dropout: 0.5
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "cnn", "gpu" ]
-
-  - name: "cnn_native"
-    description: "Baseline CNN with native name character patterns (GPU)"
-    model_type: "cnn"
-    features: [ "native_name" ]
-    model_params:
-      embedding_dim: 64
-      filters: 64
-      kernel_size: 3
-      dropout: 0.5
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "cnn", "native", "gpu" ]
-
-  - name: "cnn_surname"
-    description: "Baseline CNN with surname character patterns (GPU)"
-    model_type: "cnn"
-    features: [ "surname" ]
-    model_params:
-      embedding_dim: 64
-      filters: 64
-      kernel_size: 3
-      dropout: 0.5
-      epochs: 2
-      batch_size: 32
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "cnn", "surname", "gpu" ]
-
-  ## Ensemble Models (CPU)
-  - name: "ensemble"
-    description: "Baseline Ensemble with multiple models"
-    model_type: "ensemble"
-    features: [ "full_name" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble" ]
-
-  - name: "ensemble_native"
-    description: "Baseline Ensemble with native name"
-    model_type: "ensemble"
-    features: [ "native_name" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble", "native" ]
-
-  - name: "ensemble_surname"
-    description: "Baseline Ensemble with surname"
-    model_type: "ensemble"
-    features: [ "surname" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble", "surname" ]
-
-  # LightGBM Models (GPU-enabled)
-  - name: "lightgbm"
-    description: "Baseline LightGBM with engineered features (GPU)"
-    model_type: "lightgbm"
-    features: [ "full_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: -1
-      learning_rate: 0.1
-      num_leaves: 31
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "lightgbm", "gpu" ]
-
-  - name: "lightgbm_native"
-    description: "Baseline LightGBM with native name features (GPU)"
-    model_type: "lightgbm"
-    features: [ "native_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: -1
-      learning_rate: 0.1
-      num_leaves: 31
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "lightgbm", "native", "gpu" ]
-
-  - name: "lightgbm_surname"
-    description: "Baseline LightGBM with surname features (GPU)"
-    model_type: "lightgbm"
-    features: [ "surname" ]
-    model_params:
-      n_estimators: 100
-      max_depth: -1
-      learning_rate: 0.1
-      num_leaves: 31
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "lightgbm", "surname", "gpu" ]
-
-  # Logistic Regression Models (CPU)
-  - name: "logistic_regression"
-    description: "Baseline logistic regression with full name"
-    model_type: "logistic_regression"
-    features: [ "full_name" ]
-    model_params:
-      max_features: 10000
-    tags: [ "baseline", "logistic_regression", "fullname" ]
-
-  - name: "logistic_regression_native"
-    description: "Logistic regression with native name only"
-    model_type: "logistic_regression"
-    features: [ "native_name" ]
-    model_params:
-      max_features: 5000
-    tags: [ "baseline", "logistic_regression", "native" ]
-
-  - name: "logistic_regression_surname"
-    description: "Logistic regression with surname name only"
-    model_type: "logistic_regression"
-    features: [ "surname" ]
-    model_params:
-      max_features: 5000
-    tags: [ "baseline", "logistic_regression", "surname" ]
-
-  # LSTM Models (GPU-enabled)
-  - name: "lstm"
-    description: "Baseline LSTM with full name features (GPU)"
-    model_type: "lstm"
-    features: [ "full_name" ]
-    model_params:
-      embedding_dim: 128
-      lstm_units: 64
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "lstm", "gpu" ]
-
-  - name: "lstm_native"
-    description: "Baseline LSTM with native name features (GPU)"
-    model_type: "lstm"
-    features: [ "native_name" ]
-    model_params:
-      embedding_dim: 128
-      lstm_units: 64
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "lstm", "native", "gpu" ]
-
-  - name: "lstm_surname"
-    description: "Baseline LSTM with surname features (GPU)"
-    model_type: "lstm"
-    features: [ "surname" ]
-    model_params:
-      embedding_dim: 128
-      lstm_units: 64
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "lstm", "surname", "gpu" ]
-
-  # Naive Bayes Models (CPU)
-  - name: "naive_bayes"
-    description: "Baseline Naive Bayes with full name features"
-    model_type: "naive_bayes"
-    features: [ "full_name" ]
-    model_params:
-      max_features: 5000
-    tags: [ "baseline", "naive_bayes" ]
-
-  - name: "naive_bayes_native"
-    description: "Baseline Naive Bayes with native name features"
-    model_type: "naive_bayes"
-    features: [ "native_name" ]
-    model_params:
-      max_features: 5000
-    tags: [ "baseline", "naive_bayes", "native" ]
-
-  - name: "naive_bayes_surname"
-    description: "Baseline Naive Bayes with surname features"
-    model_type: "naive_bayes"
-    features: [ "surname" ]
-    model_params:
-      max_features: 5000
-    tags: [ "baseline", "naive_bayes", "surname" ]
-
-  # Random Forest Models (CPU)
-  - name: "random_forest"
-    description: "Baseline Random Forest with engineered features"
-    model_type: "random_forest"
-    features: [ "full_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 10
-      min_samples_split: 2
-      min_samples_leaf: 1
-    tags: [ "baseline", "random_forest", "engineered" ]
-
-  - name: "random_forest_native"
-    description: "Baseline Random Forest with native name engineered features"
-    model_type: "random_forest"
-    features: [ "native_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 10
-      min_samples_split: 2
-      min_samples_leaf: 1
-    tags: [ "baseline", "random_forest", "engineered", "native" ]
-
-  - name: "random_forest_surname"
-    description: "Baseline Random Forest with surname engineered features"
-    model_type: "random_forest"
-    features: [ "surname" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 10
-      min_samples_split: 2
-      min_samples_leaf: 1
-    tags: [ "baseline", "random_forest", "engineered", "surname" ]
-
-  # SVM Models (CPU)
-  - name: "svm"
-    description: "Baseline SVM with full name features"
-    model_type: "svm"
-    features: [ "full_name" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm" ]
-
-  - name: "svm_native"
-    description: "Baseline SVM with native name features"
-    model_type: "svm"
-    features: [ "native_name" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm", "native" ]
-
-  - name: "svm_surname"
-    description: "Baseline SVM with surname features"
-    model_type: "svm"
-    features: [ "surname" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm", "surname" ]
-
-  # Transformer Models (GPU-enabled)
-  - name: "transformer"
-    description: "Baseline Transformer with attention mechanism (GPU)"
-    model_type: "transformer"
-    features: [ "full_name" ]
-    model_params:
-      embedding_dim: 128
-      num_heads: 4
-      num_layers: 2
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "transformer", "gpu" ]
-
-  - name: "transformer_native"
-    description: "Baseline Transformer with native name attention mechanism (GPU)"
-    model_type: "transformer"
-    features: [ "native_name" ]
-    model_params:
-      embedding_dim: 128
-      num_heads: 4
-      num_layers: 2
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "transformer", "native", "gpu" ]
-
-  - name: "transformer_surname"
-    description: "Baseline Transformer with surname attention mechanism (GPU)"
-    model_type: "transformer"
-    features: [ "surname" ]
-    model_params:
-      embedding_dim: 128
-      num_heads: 4
-      num_layers: 2
-      epochs: 2
-      batch_size: 64
-      use_gpu: true
-      mixed_precision: true
-    tags: [ "baseline", "neural", "transformer", "surname", "gpu" ]
-
-  # XGBoost Models (GPU-enabled)
-  - name: "xgboost"
-    description: "Baseline XGBoost with engineered features (GPU)"
-    model_type: "xgboost"
-    features: [ "full_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 6
-      learning_rate: 0.1
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "xgboost", "gpu" ]
-
-  - name: "xgboost_native"
-    description: "Baseline XGBoost with native name engineered features (GPU)"
-    model_type: "xgboost"
-    features: [ "native_name" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 6
-      learning_rate: 0.1
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "xgboost", "native", "gpu" ]
-
-  - name: "xgboost_surname"
-    description: "Baseline XGBoost with surname engineered features (GPU)"
-    model_type: "xgboost"
-    features: [ "surname" ]
-    model_params:
-      n_estimators: 100
-      max_depth: 6
-      learning_rate: 0.1
-      subsample: 0.8
-      colsample_bytree: 0.8
-      use_gpu: true
-    tags: [ "baseline", "xgboost", "surname", "gpu" ]
-
-
-# Advanced Experiments Configuration
-advanced_experiments:
-
-# Feature Study Configurations
-feature_studies:
-
-# Hyperparameter Tuning Configurations
-hyperparameter_tuning:
-
@@ -73,37 +73,6 @@ baseline_experiments:
      batch_size: 32
    tags: [ "baseline", "neural", "cnn", "surname" ]

-  ## Ensemble Models
-  - name: "ensemble"
-    description: "Baseline Ensemble with multiple models"
-    model_type: "ensemble"
-    features: [ "full_name" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble" ]
-
-  - name: "ensemble_native"
-    description: "Baseline Ensemble with native name"
-    model_type: "ensemble"
-    features: [ "native_name" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble", "native" ]
-
-  - name: "ensemble_surname"
-    description: "Baseline Ensemble with surname"
-    model_type: "ensemble"
-    features: [ "surname" ]
-    model_params:
-      base_models: [ "logistic_regression", "random_forest", "xgboost" ]
-      voting: "soft"
-      cv_folds: 5
-    tags: [ "baseline", "ensemble", "surname" ]
-
  # LightGBM Models
  - name: "lightgbm"
    description: "Baseline LightGBM with engineered features"
@@ -262,40 +231,6 @@ baseline_experiments:
      min_samples_leaf: 1
    tags: [ "baseline", "random_forest", "engineered", "surname" ]

-  # SVM Models
-  - name: "svm"
-    description: "Baseline SVM with full name features"
-    model_type: "svm"
-    features: [ "full_name" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm" ]
-
-  - name: "svm_native"
-    description: "Baseline SVM with native name features"
-    model_type: "svm"
-    features: [ "native_name" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm", "native" ]
-
-  - name: "svm_surname"
-    description: "Baseline SVM with surname features"
-    model_type: "svm"
-    features: [ "surname" ]
-    model_params:
-      C: 1.0
-      kernel: "rbf"
-      ngram_range: [ 2, 4 ]
-      max_features: 5000
-    tags: [ "baseline", "svm", "surname" ]
-
  # Transformer Models
  - name: "transformer"
    description: "Baseline Transformer with attention mechanism"
@@ -24,6 +24,7 @@ dependencies = [
    "typer>=0.19.2",
    "tensorflow==2.20.0; sys_platform == 'linux' and platform_machine == 'x86_64'",
    "xgboost>=3.0.5",
+    "networkx>=3.5",
 ]

 [project.scripts]
@@ -35,5 +36,6 @@ build-backend = "uv_build"

 [dependency-groups]
 dev = [
+    "ipykernel>=6.30.1",
    "ruff>=0.13.3",
 ]
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 ]

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+version = "0.1.4"
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+[[package]]
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+version = "3.0.0"
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 [[package]]
 name = "astunparse"
 version = "1.6.3"
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 ]

+[[package]]
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