---
library_name: transformers
base_model:
- amazon/chronos-bolt-small
pipeline_tag: time-series-forecasting
---
# Model Card for Chronos Bolt Small Fine-Tuned Model


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## Summary

This model is fine-tuned for time-series forecasting tasks and serves as a tool for both practical predictions and research into time-series demand forecasting. It is based on the `amazon/chronos-bolt-small` model and has been adapted using a dataset with 25 million rows of proprietary time-series data. Due to confidentiality restrictions, dataset details cannot be shared.

## Fine-Tuning Dataset

The model was fine-tuned on a proprietary dataset containing 25 million rows of time-series data. While details about the dataset are confidential, the following general characteristics are provided:
- The dataset consists of multi-dimensional time-series data.  
 

This large-scale dataset ensures the model captures complex patterns and temporal dependencies necessary for accurate forecasting.


#### Summary

The fine-tuned model performs well on intermitent demand forecasting.

## Technical Specifications

### Model Architecture and Objective

The model is based on the `amazon/chronos-bolt-small` architecture, fine-tuned specifically for time-series forecasting tasks. It leverages pre-trained capabilities for sequence-to-sequence modeling, adapted to handle multi-horizon forecasting scenarios.

## Contact:

[NIEXCHE (Fevzi KILAS)](https://niexche.github.io/) 

![header](https://capsule-render.vercel.app/api?type=venom&height=150&text=👋%20NIEXCHE&textBg=false&fontColor=f3c1c0&fontAlign=46&animation=blink&stroke=800000&strokeWidth=45section=header)