Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 754123133
CO2 Emissions (in grams): 0.005300030853867218

Validation Metrics

Loss: 0.387116938829422
Accuracy: 0.8658536585365854
Macro F1: 0.7724053724053724
Micro F1: 0.8658536585365854
Weighted F1: 0.8467166979362101
Macro Precision: 0.8232219717155155
Micro Precision: 0.8658536585365854
Weighted Precision: 0.8516026874759421
Macro Recall: 0.7642089093701996
Micro Recall: 0.8658536585365854
Weighted Recall: 0.8658536585365854

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/zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133", use_auth_token=True)

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

outputs = model(**inputs)