cwinkler
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distilbert-base-uncased-finetuned-greenpatent

Text Classification

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cwinkler commited on Jan 6, 2023

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@@ -53,7 +53,7 @@ Examples were inspired by https://www.epo.org/news-events/in-focus/classificatio
 # distilbert-base-uncased-finetuned-greenpatent
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [green patent dataset](https://huggingface.co/datasets/cwinkler/green_patents). The green patent dataset was split into 70 % training data and 30 % test data (using ".train_test_split(test_size=0.3)").
-It achieves the following results on the evaluation set:
 - Loss: 0.3148
 - Accuracy: 0.8776
 - F1: 0.8770

 # distilbert-base-uncased-finetuned-greenpatent
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [green patent dataset](https://huggingface.co/datasets/cwinkler/green_patents). The green patent dataset was split into 70 % training data and 30 % test data (using ".train_test_split(test_size=0.3)").
+The model achieves the following results on the evaluation set:
 - Loss: 0.3148
 - Accuracy: 0.8776
 - F1: 0.8770