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  ---
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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```python
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  # Import necessary libraries
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  import torch
@@ -64,4 +91,4 @@ def infer(model, tokenizer, text):
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  # Example usage
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  text = "NASA announces new mission to study asteroids"
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  result = infer(model, tokenizer, text)
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- print(f"Predicted category: {result}")
 
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  ---
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  license: mit
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+ datasets:
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+ - fancyzhx/ag_news
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ base_model:
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+ - google-t5/t5-large
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+ pipeline_tag: text-classification
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+ tags:
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+ - ag
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+ - news
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+ - document
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+ - classification
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  ---
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+
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+ Epoch 1/2 - Training Loss: 0.2126
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+ Epoch 1/2 - Validation Loss: 0.1566
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+ Best model saved with validation loss: 0.1566
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+ Epoch 2/2 - Training Loss: 0.1205
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+ Epoch 2/2 - Validation Loss: 0.1590
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+ Test Loss: 0.1629
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+ Accuracy: 0.9521
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+ F1 Score: 0.9521
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+ Precision: 0.9522
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+ Recall: 0.952
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+
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+
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  ```python
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  # Import necessary libraries
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  import torch
 
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  # Example usage
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  text = "NASA announces new mission to study asteroids"
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  result = infer(model, tokenizer, text)
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+ print(f"Predicted category: {result}")