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@@ -21,6 +21,8 @@ Detailed Python notebooks documenting the research and methodology are available
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  - **Training Environment**: Google Colab, utilizing an A100 GPU, with a training time of approximately 1.5 hours.
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  ### Model Performance
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- The model's effectiveness in anomaly detection is evidenced by its performance on test data. For visual representation of the model's capability to segregate normal vs. anomalous execution traces, see the results [here](https://cdn-uploads.huggingface.co/production/uploads/661915f3fdcb7df8a6e2fdaa/bsZ8dXWN6IoAH4zXfwzi2.png).
 
 
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  This detailed configuration and performance data is provided to facilitate replication and further experimentation by the community. The use of the Apache-2.0 license allows for both academic and commercial use, promoting wider adoption and potential contributions to the model's development.
 
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  - **Training Environment**: Google Colab, utilizing an A100 GPU, with a training time of approximately 1.5 hours.
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  ### Model Performance
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+ The model's effectiveness in anomaly detection is evidenced by its performance on test data. For visual representation of the model's capability to segregate normal vs. anomalous execution traces.
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/661915f3fdcb7df8a6e2fdaa/bsZ8dXWN6IoAH4zXfwzi2.png)
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  This detailed configuration and performance data is provided to facilitate replication and further experimentation by the community. The use of the Apache-2.0 license allows for both academic and commercial use, promoting wider adoption and potential contributions to the model's development.