Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Shivasharanappa/Shiva-project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shivasharanappa/Shiva-project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shivasharanappa/Shiva-project")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shivasharanappa/Shiva-project") model = AutoModelForSequenceClassification.from_pretrained("Shivasharanappa/Shiva-project", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.651250422000885
f1_macro: 0.7322222222222221
f1_micro: 0.7333333333333333
f1_weighted: 0.7322222222222222
precision_macro: 0.7326247987117552
precision_micro: 0.7333333333333333
precision_weighted: 0.7326247987117551
recall_macro: 0.7333333333333334
recall_micro: 0.7333333333333333
recall_weighted: 0.7333333333333333
accuracy: 0.7333333333333333
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