Hugging Face's logo

ikram54
/
autotrain-harassement-675420038

Text Classification
Transformers
PyTorch
Enawené-Nawé
bert
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
Model card Files Community
1
autotrain-harassement-675420038 / README.md
abhishek's picture
abhishek HF staff
Commit From AutoTrain
fa34bc1
preview code
|
raw history blame
No virus
1.4 kB
metadata
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)