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ssclass_best
asaderu-ai/ssclass_best
ssclass_best is a text classification model from asaderu-ai. Use it when you need a label for a piece of text. It is set up for transformers.
- Loss: 0.073 - Accuracy: 0.980 - Macro F1: 0.981 - Micro F1: 0.980 - Weighted F1: 0.980 - Macro Precision: 0.981 - Micro Precision: 0.980 - Weighted Precision: 0.980 - Macro Recall: 0.982 - Micro Recall: 0.980 - Weig…
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jan 27, 2023
- Updated
- Apr 11, 2023
- SHA
- ead04320
Model card
From the Hugging Face model README
Validation Metrics
- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980
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/asaderu/autotrain-sunnishia_2-3090387920
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("asaderu/autotrain-sunnishia_2-3090387920", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("asaderu/autotrain-sunnishia_2-3090387920", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- unk
- Created
- Jan 27, 2023
- Updated
- Apr 11, 2023