--- tags: autonlp language: en widget: - text: "I love AutoNLP 🤗" datasets: - bgoel4132/autonlp-data-tweet-disaster-classifier co2_eq_emissions: 27.22397099134103 --- # Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 28716412 - CO2 Emissions (in grams): 27.22397099134103 ## Validation Metrics - Loss: 0.4146720767021179 - Accuracy: 0.8066924731182795 - Macro F1: 0.7835463282531184 - Micro F1: 0.8066924731182795 - Weighted F1: 0.7974252447208724 - Macro Precision: 0.8183917344767431 - Micro Precision: 0.8066924731182795 - Weighted Precision: 0.8005510296861892 - Macro Recall: 0.7679676081852519 - Micro Recall: 0.8066924731182795 - Weighted Recall: 0.8066924731182795 ## 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 AutoNLP"}' https://api-inference.huggingface.co/models/bgoel4132/autonlp-tweet-disaster-classifier-28716412 ``` Or Python API: ``` from transformers import AutoModelForSequenceClassification, AutoTokenizer model = AutoModelForSequenceClassification.from_pretrained("bgoel4132/autonlp-tweet-disaster-classifier-28716412", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("bgoel4132/autonlp-tweet-disaster-classifier-28716412", use_auth_token=True) inputs = tokenizer("I love AutoNLP", return_tensors="pt") outputs = model(**inputs) ```