Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use autoevaluate/binary-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/binary-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/binary-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/binary-classification") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/binary-classification") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on glue
#28
by lewtun HF Staff - opened
README.md
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verified: true
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value: 0.9672423591816116
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verified: true
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- name: F1
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type: f1
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verified: true
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value: 0.30093517899513245
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verified: true
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- name: matthews_correlation
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type: matthews_correlation
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