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fitness_message_classification
lucieackley/fitness_message_classification
fitness_message_classification is a text classification model from lucieackley. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 40235104670 - CO2 Emissions (in grams): 0.0028
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- deberta
- Access
- Public
- Created
- Mar 10, 2023
- Updated
- Mar 10, 2023
- SHA
- 2ff681e0
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Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 40235104670
- CO2 Emissions (in grams): 0.0028
Validation Metrics
- Loss: 1.121
- Accuracy: 0.589
- Macro F1: 0.403
- Micro F1: 0.589
- Weighted F1: 0.541
- Macro Precision: 0.433
- Micro Precision: 0.589
- Weighted Precision: 0.536
- Macro Recall: 0.415
- Micro Recall: 0.589
- Weighted Recall: 0.589
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/lucieackley/autotrain-fitness_message_classification-40235104670
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("lucieackley/autotrain-fitness_message_classification-40235104670", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("lucieackley/autotrain-fitness_message_classification-40235104670", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- deberta
- Languages
- en
- Created
- Mar 10, 2023
- Updated
- Mar 10, 2023