Downloads · 30 days
0
autotrain-uzdtm-nwkp2
diffuser34/autotrain-uzdtm-nwkp2
autotrain-uzdtm-nwkp2 is a tabular regression model from diffuser34. Use it for the tabular regression task on the model card, and read the license before you ship it in a product. It is set up for transformers.
Access
Public
Updated Feb 13, 2024
Repo size
508 KB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.joblib508 KB · 99%
At a glance
- Task
- Tabular Regression
- Library
- transformers
- Access
- Public
- Created
- Feb 13, 2024
- Updated
- Feb 13, 2024
- SHA
- 12538c3f
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Tabular regression
Validation Metrics
- r2: 0.5287307064016351
- mse: 3.103168000915719e+19
- mae: 2243863540.8
- rmse: 5570608585.168877
- rmsle: 8.027979609819264
- loss: 5570608585.168877
Best Params
- learning_rate: 0.11299209471906922
- reg_lambda: 1.95078305416454e-06
- reg_alpha: 0.03568550183373181
- subsample: 0.6486218191662874
- colsample_bytree: 0.22654368454464396
- max_depth: 1
- early_stopping_rounds: 481
- n_estimators: 20000
- eval_metric: rmse
Usage
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
- Task
- Tabular Regression
- Library
- transformers
- Created
- Feb 13, 2024
- Updated
- Feb 13, 2024