Text Classification
Transformers
Safetensors
English
bert
proposal-analysis
business
binary-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use JonahDelman/ProposalClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonahDelman/ProposalClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JonahDelman/ProposalClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JonahDelman/ProposalClassifier") model = AutoModelForSequenceClassification.from_pretrained("JonahDelman/ProposalClassifier") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): adb6f09
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README.md
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library_name: transformers
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tags:
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- text-classification
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- distilbert
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- proposal-analysis
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- business
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- binary-classification
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metrics:
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- accuracy
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- f1
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value: 0.92
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- type: loss
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value: 0.32
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---
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library_name: transformers
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tags:
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- text-classification
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- proposal-analysis
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- business
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- binary-classification
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- bert
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metrics:
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- accuracy
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- f1
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value: 0.92
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- type: loss
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value: 0.32
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base_model:
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- google-bert/bert-base-uncased
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pipeline_tag: text-classification
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---
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