I trained a sprite model with agents. The data was the bottleneck.

1. 1Build a sprite-art transformer model using agents
2. 2Train the model on a dataset and evaluate its performance
3. 3Identify the bottleneck in the model's performance, such as data quality or quantity
4. 4Apply data augmentation techniques to improve the model's performance
5. 5Compare the results of the model with and without data augmentation

ML engineers and researchers working with agentic ML loops can benefit from understanding the limitations of their models and the importance of high-quality data

💡 Data quality is a crucial factor in the performance of agentic ML loops

🤖 Trained a 2.9M-parameter sprite-art transformer with agents and found data to be the bottleneck! 📊