Chronos Bolt Small Fine-Tuned v3
| Property | Value |
|---|---|
| Author | nieche (Fevzi KILAS) |
| Base Architecture | amazon/chronos-bolt-small |
| Model URL | HuggingFace |
| Performance Metric | WQL = 0.5908 |
What is chronos-bolt-small-fine-tuned-v3?
Chronos Bolt Small Fine-Tuned v3 is a specialized time-series forecasting model designed specifically for intermittent demand prediction. Built upon Amazon's chronos-bolt-small architecture, this model has been fine-tuned on a massive proprietary dataset containing 25 million rows of multi-dimensional time-series data, enhanced with five additional exogenous variables including two different types of volume measurements.
Implementation Details
The model implements a sequence-to-sequence architecture optimized for multi-horizon forecasting scenarios. It leverages the pre-trained capabilities of the base Chronos Bolt Small model while incorporating additional training on complex temporal patterns and dependencies.
- Fine-tuned on 25 million rows of time-series data
- Incorporates 5 additional exogenous variables
- Specialized for intermittent demand patterns
- Built on proven amazon/chronos-bolt-small architecture
Core Capabilities
- Multi-dimensional time-series forecasting
- Handling of intermittent demand patterns
- Integration of exogenous variables
- Multi-horizon prediction capabilities
- Complex pattern recognition in temporal data
Frequently Asked Questions
Q: What makes this model unique?
This model's uniqueness lies in its specialized fine-tuning on a massive proprietary dataset focused on intermittent demand patterns, combined with its ability to incorporate multiple exogenous variables for improved prediction accuracy.
Q: What are the recommended use cases?
The model is particularly well-suited for scenarios involving intermittent demand forecasting, such as spare parts inventory management, retail demand prediction for slow-moving items, and other applications where demand patterns are non-continuous or irregular.
