readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - ikram54/autotrain-data-harassement
  co2_eq_emissions: 2.6332836871905054
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 675420038
  - CO2 Emissions (in grams): 2.6332836871905054
  
  ## Validation Metrics
  
  - Loss: 0.8747465014457703
  - Accuracy: 0.7085201793721974
  - Macro F1: 0.579743989078862
  - Micro F1: 0.7085201793721974
  - Weighted F1: 0.6913786522271296
  - Macro Precision: 0.5669375905888698
  - Micro Precision: 0.7085201793721974
  - Weighted Precision: 0.6760144007300164
  - Macro Recall: 0.5940655209452201
  - Micro Recall: 0.7085201793721974
  - Weighted Recall: 0.7085201793721974
  
  
  ## Usage
  
  You can use cURL to access this model:
  
  ```
  $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/ikram54/autotrain-harassement-675420038
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("ikram54/autotrain-harassement-675420038", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("ikram54/autotrain-harassement-675420038", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```