Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use PracticalWork/distilbert-base-uncased-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PracticalWork/distilbert-base-uncased-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PracticalWork/distilbert-base-uncased-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") model = AutoModelForSequenceClassification.from_pretrained("PracticalWork/distilbert-base-uncased-classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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- Accuracy: 0.8809
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- F1: 0.7916
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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- Accuracy: 0.8809
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- F1: 0.7916
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## Training procedure
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### Training hyperparameters
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