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crcb
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emo_go_new

Text Classification
Transformers
PyTorch
Enawené-Nawé
roberta
Trained with AutoTrain
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emo_go_new / README.md
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metadata
tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - crcb/autotrain-data-go_emo_new
co2_eq_emissions: 20.58663910106142

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 813325491
  • CO2 Emissions (in grams): 20.58663910106142

Validation Metrics

  • Loss: 1.3628994226455688
  • Accuracy: 0.5920355494787216
  • Macro F1: 0.4844439507523978
  • Micro F1: 0.5920355494787216
  • Weighted F1: 0.5873137663478112
  • Macro Precision: 0.5458988948121151
  • Micro Precision: 0.5920355494787216
  • Weighted Precision: 0.591386299522425
  • Macro Recall: 0.4753100798358001
  • Micro Recall: 0.5920355494787216
  • Weighted Recall: 0.5920355494787216

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/crcb/autotrain-go_emo_new-813325491

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-go_emo_new-813325491", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-go_emo_new-813325491", use_auth_token=True)

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

outputs = model(**inputs)