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Epironica
yigitkucuk/Epironica
Epironica is a text classification model from yigitkucuk. Use it when you need a label for a piece of text. It is set up for transformers.
- Loss: 0.537 - Accuracy: 0.721 - Macro F1: 0.720 - Micro F1: 0.721 - Weighted F1: 0.720 - Macro Precision: 0.723 - Micro Precision: 0.721 - Weighted Precision: 0.723 - Macro Recall: 0.721 - Micro Recall: 0.721 - Weig…
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- deberta-v2
- Access
- Public
- Created
- Jan 21, 2023
- Updated
- Oct 3, 2023
- SHA
- a87d4fa0
Try a prompt
Datasets
Model card
From the Hugging Face model README
Validation Metrics
- Loss: 0.537
- Accuracy: 0.721
- Macro F1: 0.720
- Micro F1: 0.721
- Weighted F1: 0.720
- Macro Precision: 0.723
- Micro Precision: 0.721
- Weighted Precision: 0.723
- Macro Recall: 0.721
- Micro Recall: 0.721
- Weighted Recall: 0.721
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 3.2437
- Model ID: 2994886333
Use with Python API
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Epironica", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Epironica", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- Languages
- en
- Created
- Jan 21, 2023
- Updated
- Oct 3, 2023