Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 1055036381
CO2 Emissions (in grams): 17.43982800509071

Validation Metrics

Loss: 0.6177256107330322
Accuracy: 0.7306006137658921
Macro F1: 0.719534854339415
Micro F1: 0.730600613765892
Weighted F1: 0.7302204676842725
Macro Precision: 0.714938066281146
Micro Precision: 0.7306006137658921
Weighted Precision: 0.7316651970219867
Macro Recall: 0.7258484087500343
Micro Recall: 0.7306006137658921
Weighted Recall: 0.7306006137658921

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/kakashi210/autotrain-tweet-sentiment-classifier-1055036381

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("kakashi210/autotrain-tweet-sentiment-classifier-1055036381", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("kakashi210/autotrain-tweet-sentiment-classifier-1055036381", use_auth_token=True)

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

outputs = model(**inputs)