README.md

---
license: cc-by-nc-nd-4.0
base_model:
- Salesforce/moirai-1.0-R-small
- Salesforce/moirai-1.0-R-base
- Salesforce/moirai-1.0-R-large
pipeline_tag: time-series-forecasting
---

---
license: cc-by-nc-nd-4.0
base_model:
- Salesforce/moirai-1.0-R-small
- Salesforce/moirai-1.0-R-base
- Salesforce/moirai-1.0-R-large
pipeline_tag: time-series-forecasting
---


# Time Series Forecasting Model

This model is built on top of the Salesforce Moirai architecture, specifically fine-tuned and trained from scratch for time series forecasting tasks.

## Model Details

### Model Description

This model leverages the Moirai architecture from Salesforce, which is designed specifically for time series forecasting. The model is available in multiple versions:

- Fine-tuned variants (located in `./finetune` directory)
- Trained from scratch variants (located in `./train_from_scratch` directory)

All checkpoint files (.ckpt) include self-explanatory naming conventions that indicate their configuration and training approach.

### Model Type

Time Series Forecasting

### Version

1.0


## Training Procedure

### Training Methodology

Two distinct training approaches were utilized:
1. **Fine-tuning approach**: Starting with the pre-trained Moirai models (small, base) and fine-tuning on domain-specific data
2. **Training from scratch**: Building models with the Moirai architecture but training entirely on specific datasets


## Limitations and Biases

- The model inherits any limitations present in the base Moirai architecture
- Performance may degrade for extremely long-range forecasts
- The model may not perform optimally on domains significantly different from its training data

## Additional Information

### Checkpoints

The model checkpoints are organized as follows:
- Fine-tuned models: `./finetune/*.ckpt`
- Models trained from scratch: `./train_from_scratch/*.ckpt`


### Citation

If you use this model in your research, please cite: TBA

### License

This model is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).