Create README.md

README.md

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+---
+language:
+- en
+---
+
+Source: CrisisMMD dataset (Alam et al., 2017)
+
+✅Original Labels (8 classes from annotations):
+
+Infrastructure and utility damage
+
+Vehicle damage
+
+Rescue, volunteering, or donation efforts
+
+Affected individuals
+
+Injured or dead people
+
+Missing or found people
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+Other relevant information
+
+Not humanitarian
+
+✅Label Preprocessing (Class Merging):
+
+Vehicle damage merged into Infrastructure and utility damage
+
+Missing or found people merged into Affected individuals
+
+Not humanitarian retained as a separate class
+
+Removed very low-frequency categories (e.g., "Missing or found people" as a separate class)
+
+✅Final Label Set (5 classes total):
+
+Infrastructure and utility damage
+
+Rescue, volunteering, or donation efforts
+
+Affected individuals
+
+Injured or dead people
+
+Not humanitarian
+
+✅Multimodal Consistency:
+
+Selected only those posts where text and image annotations matched
+
+Resulted in a total of 8,219 consistent samples:
+
+Train set: 6,574 posts
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+Test set: 1,644 posts
+
+✅ Preprocessing Done Text:
+
+Tokenized using BERT tokenizer (bert-base-uncased)
+
+Extracted input_ids and attention_mask
+
+Image:
+
+Processed using ResNet-50
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+Extracted 2048-dimensional image features
+
+The preprocessed data was saved in PyTorch .pt format:
+
+train_human.pt and test_human.pt
+
+Each contains: input_ids, attention_mask, image_vector, and label