
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 61622134846
- CO2 Emissions (in grams): 1.2832

## Validation Metrics

- Loss: 0.883
- Accuracy: 0.583
- Macro F1: 0.184
- Micro F1: 0.583
- Weighted F1: 0.429
- Macro Precision: 0.146
- Micro Precision: 0.583
- Weighted Precision: 0.340
- Macro Recall: 0.250
- Micro Recall: 0.583
- Weighted Recall: 0.583

## 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]
data.columns = ["feat_" + str(col) for col in data.columns]

predictions = model.predict(data)  # or model.predict_proba(data)

```
{"tags": ["tabular", "classification", "tabular-classification", "google-ads"], "datasets": ["adgrowr/autotrain-data-negative-keywords-classifier"], "widget": {"structuredData": {"keyword": ["garner", "chevy", "location"], "class": ["brand", "brand", "geo"]}}, "co2_eq_emissions": {"emissions": 1.2831572182351383}}
transformers joblib xgboost tabular classification tabular-classification google-ads dataset:adgrowr/autotrain-data-negative-keywords-classifier co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #joblib #xgboost #tabular #classification #tabular-classification #google-ads #dataset-adgrowr/autotrain-data-negative-keywords-classifier #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 61622134846
- CO2 Emissions (in grams): 1.2832

## Validation Metrics

- Loss: 0.883
- Accuracy: 0.583
- Macro F1: 0.184
- Micro F1: 0.583
- Weighted F1: 0.429
- Macro Precision: 0.146
- Micro Precision: 0.583
- Weighted Precision: 0.340
- Macro Recall: 0.250
- Micro Recall: 0.583
- Weighted Recall: 0.583

## Usage


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 61622134846
- CO2 Emissions (in grams): 1.2832 ## Validation Metrics

- Loss: 0.883
- Accuracy: 0.583
- Macro F1: 0.184
- Micro F1: 0.583
- Weighted F1: 0.429
- Macro Precision: 0.146
- Micro Precision: 0.583
- Weighted Precision: 0.340
- Macro Recall: 0.250
- Micro Recall: 0.583
- Weighted Recall: 0.583 ## Usage
TAGS
#transformers #joblib #xgboost #tabular #classification #tabular-classification #google-ads #dataset-adgrowr/autotrain-data-negative-keywords-classifier #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 61622134846
- CO2 Emissions (in grams): 1.2832 ## Validation Metrics

- Loss: 0.883
- Accuracy: 0.583
- Macro F1: 0.184
- Micro F1: 0.583
- Weighted F1: 0.429
- Macro Precision: 0.146
- Micro Precision: 0.583
- Weighted Precision: 0.340
- Macro Recall: 0.250
- Micro Recall: 0.583
- Weighted Recall: 0.583 ## Usage