metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Souvikcmsa/autotrain-data-sentiment_analysis
co2_eq_emissions: 0.015536746909294205

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 762923432
CO2 Emissions (in grams): 0.015536746909294205

Validation Metrics

Loss: 0.49825894832611084
Accuracy: 0.7962895598399418
Macro F1: 0.7997458031044901
Micro F1: 0.7962895598399418
Weighted F1: 0.796365325858282
Macro Precision: 0.7995724418486833
Micro Precision: 0.7962895598399418
Weighted Precision: 0.7965384250324863
Macro Recall: 0.8000290112564951
Micro Recall: 0.7962895598399418
Weighted Recall: 0.7962895598399418

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/Souvikcmsa/autotrain-sentiment_analysis-762923432

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Souvikcmsa/autotrain-sentiment_analysis-762923432", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Souvikcmsa/autotrain-sentiment_analysis-762923432", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)