readme: ---
  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)
  ```