Instructions to use caush/Clickbait4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait4") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait4") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: Clickbait1
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results: []
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---
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This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the Webis-Clickbait-17 dataset. It achieves the following results on the evaluation set:
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Loss: 0.0261
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The following list presents the current performances achieved by the participants. As primary evaluation measure, Mean Squared Error (MSE) with respect to the mean judgments of the annotators is used. Our result is 0,0261 for the MSE metric. We do not compute the other metrics. We try not to cheat using unknown data at the time of the challenge. We do not use k-fold cross validation techniques.
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| team | MSE | F1 | Precision | Recall| Accuracy| Runtime |
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|----- |----- |--- |-----------|-------|---------|-------- |
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|goldfish | 0.024 | 0.741 | 0.739 | 0.742 | 0.876 | 16:20:21|
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|caush | 0.026 | | | | | 00:11:00|
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|monkfish | 0.026 | 0.694 | 0.785 | 0.622 | 0.870 | 03:41:35|
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|dartfish | 0.027 | 0.706 | 0.733 | 0.681 | 0.865 | 00:47:07|
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|torpedo19 | 0.03 | 0.677 | 0.755 | 0.614 | 0.861 | 00:52:44|
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|albacore | 0.031 | 0.67 | 0.731 | 0.62 | 0.855 | 00:01:10|
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|blobfish | 0.032 | 0.646 | 0.738 | 0.574 | 0.85 | 00:03:22|
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|zingel | 0.033 | 0.683 | 0.719 | 0.65 | 0.856 | 00:03:27|
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|anchovy | 0.034 | 0.68 | 0.717 | 0.645 | 0.855 | 00:07:20|
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|ray | 0.034 | 0.684 | 0.691 | 0.677 | 0.851 | 00:29:28|
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|icarfish | 0.035 | 0.621 | 0.768 | 0.522 | 0.849 | 01:02:57|
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|emperor | 0.036 | 0.641 | 0.714 | 0.581 | 0.845 | 00:04:03|
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|carpetshark | 0.036 | 0.638 | 0.728 | 0.568 | 0.847 | 00:08:05|
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|electriceel | 0.038 | 0.588 | 0.727 | 0.493 | 0.835 | 01:04:54|
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|arowana | 0.039 | 0.656 | 0.659 | 0.654 | 0.837 | 00:35:24|
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|pineapplefish | 0.041 | 0.631 | 0.642 | 0.621 | 0.827 | 00:54:28|
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|whitebait | 0.043 | 0.565 | 0.7 | 0.474 | 0.826 | 00:04:31|
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