Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use wisejiyoon/bert-base-finetuned-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wisejiyoon/bert-base-finetuned-sts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wisejiyoon/bert-base-finetuned-sts")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wisejiyoon/bert-base-finetuned-sts") model = AutoModelForSequenceClassification.from_pretrained("wisejiyoon/bert-base-finetuned-sts") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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@@ -5,20 +5,21 @@ datasets:
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- klue
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metrics:
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- pearsonr
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model-index:
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- name: bert-base-finetuned-sts
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: klue
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type: klue
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args: sts
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metrics:
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type: pearsonr
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value: 0.9000373376026184
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- klue
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metrics:
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- pearsonr
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base_model: klue/bert-base
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model-index:
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- name: bert-base-finetuned-sts
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: klue
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type: klue
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args: sts
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metrics:
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- type: pearsonr
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value: 0.9000373376026184
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name: Pearsonr
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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