Upload folder using huggingface_hub

README.md

@@ -0,0 +1,56 @@
+
+---
+tags:
+- autotrain
+- tabular
+- regression
+- tabular-regression
+datasets:
+- nicoler229/autotrain-data-renp-vcyx-5hff
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Tabular regression
+
+## Validation Metrics
+
+- r2: 0.8987710422047952
+- mse: 15.386801584871137
+- mae: 3.1008129119873047
+- rmse: 3.9226013798079378
+- rmsle: 0.049014949862444
+- loss: 3.9226013798079378
+
+## Best Params
+
+- learning_rate: 0.09858308825036341
+- reg_lambda: 1.7244892825164977e-06
+- reg_alpha: 0.004880162297132929
+- subsample: 0.5918267532876357
+- colsample_bytree: 0.6228647593929555
+- max_depth: 8
+- early_stopping_rounds: 440
+- n_estimators: 7000
+- eval_metric: rmse
+
+## Usage
+
+```python
+import json
+import joblib
+import pandas as pd
+
+model = joblib.load('model.joblib')
+config = json.load(open('config.json'))
+
+features = config['features']
+
+# data = pd.read_csv("data.csv")
+data = data[features]
+
+predictions = model.predict(data)  # or model.predict_proba(data)
+
+# predictions can be converted to original labels using label_encoders.pkl
+
+```

model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:055eb9e7b8fe9ff6644fb20e22f9b903f6309dc487637aa8ff21f612582871b7
+size 512099

target_encoders.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:926248e52d1fa532c317e37da24ed652ae64110f8219cb5e061668bd3091f048
+size 5

training_params.json

@@ -0,0 +1 @@
+{"data_path": "nicoler229/autotrain-data-renp-vcyx-5hff", "model": "xgboost", "username": "nicoler229", "seed": 42, "train_split": "train", "valid_split": "validation", "project_name": "/tmp/model", "push_to_hub": true, "id_column": "autotrain_id", "target_columns": ["autotrain_label"], "repo_id": "nicoler229/renp-vcyx-5hff-0", "categorical_columns": null, "numerical_columns": null, "task": "regression", "num_trials": 100, "time_limit": 3600, "categorical_imputer": null, "numerical_imputer": "mean", "numeric_scaler": "standard"}