Create README.md

README.md

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+---
+  widget:
+  - text: "They're able to charge women more for the same exact procedure a man gets."
+    example_title: "Example: Yes"
+  - text: "There's no way they would give it up."
+    example_title: "Example: No"
+---
+
+# ba-claim/bert
+## Model Details
+Fine-tuned BERT Model for Claim Relevance Identification
+
+### Model Description
+This Hugging Face model is a fine-tuned BERT model specifically developed for identifying relevant claims in the context of combating fake news.
+The model was trained as part of a bachelor thesis project aimed at automating the fact-checking process by automatically identifying claims of interest.
+
+The project participated in the CheckThat!2023 competition, focusing on task 1B, organized by the Conference and Labs of the Evaluation Forum (CLEF).
+The CheckThat! lab provided relevant training data for predicting the checkworthiness of claims.
+The data was analyzed, and various transformer models, including DistilBERT and ELECTRA, were experimented with to identify the most effective architecture.
+
+Overall, this fine-tuned BERT model serves as a valuable tool in automating the identification of relevant claims, reducing the need for manual fact-checking, and contributing to efforts to combat the challenges posed by the widespread dissemination of fake news.
+
+
+#### Examples
+
+37440	There's no way they would give it up.	No
+
+37463	They're able to charge women more for the same exact procedure a man gets.	Yes
+
+
+## Training Details
+
+|Hyperparameters||
+|----|----|
+| Learning Rate|9.459e-05|
+| Weight Decay|2.737e-04| 
+| Batch Size|64| 
+| Number of Epochs|4| 
+
+
+