File size: 1,867 Bytes
5304ba1 1f9c189 5304ba1 1fada96 5304ba1 1fada96 5304ba1 1fada96 5304ba1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
---
library_name: transformers
base_model:
- amazon/chronos-bolt-small
pipeline_tag: time-series-forecasting
---
# Model Card for Chronos Bolt Small Fine-Tuned Model
<img align="center" height="350" src="https://media3.giphy.com/media/v1.Y2lkPTc5MGI3NjExYjRmcWUwaGFkbW1lczJoYzBjbHBxZjMyeDdhdDQycGdzamwyOGhiZyZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/ZtB2l3jHiJsFa/giphy.gif"/> </p>
## 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/)
|