--- 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).