metadata

tags:
  - autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - juliensimon/autonlp-data-song-lyrics
co2_eq_emissions: 112.75546781635975

Model Trained Using AutoNLP

Problem type: Multi-class Classification
Model ID: 18753417
CO2 Emissions (in grams): 112.75546781635975

Validation Metrics

Loss: 0.9065971970558167
Accuracy: 0.6680274633512711
Macro F1: 0.5384854358272774
Micro F1: 0.6680274633512711
Weighted F1: 0.6414749238882866
Macro Precision: 0.6744495173269196
Micro Precision: 0.6680274633512711
Weighted Precision: 0.6634090047492259
Macro Recall: 0.5078466493896978
Micro Recall: 0.6680274633512711
Weighted Recall: 0.6680274633512711

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/juliensimon/autonlp-song-lyrics-18753417

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("juliensimon/autonlp-song-lyrics-18753417", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("juliensimon/autonlp-song-lyrics-18753417", use_auth_token=True)

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

outputs = model(**inputs)