Update README.md

README.md

@@ -174,7 +174,7 @@ fewshot_output = finetune_forecast_trainer.evaluate(dset_test)
 
 ## Training Data
 
-The TTM models were trained on a collection of datasets from the Monash Time Series Forecasting repository. The datasets used include:
+The original r1 TTM models were trained on a collection of datasets from the Monash Time Series Forecasting repository. The datasets used include:
  - Australian Electricity Demand: https://zenodo.org/records/4659727 
  - Australian Weather: https://zenodo.org/records/4654822 
  - Bitcoin dataset: https://zenodo.org/records/5122101 
@@ -187,10 +187,12 @@ The TTM models were trained on a collection of datasets from the Monash Time Ser
  - US Births: https://zenodo.org/records/4656049 
  - Wind Farms Production data: https://zenodo.org/records/4654858 
  - Wind Power: https://zenodo.org/records/4656032
- - [to be updated]
+In addition to the above datasets, the updated TTM model (512-96-r2) was trained on the following:
+ - PEMSD3, PEMSD4, PEMSD7, PEMSD8, PEMS_BAY: https://drive.google.com/drive/folders/1g5v2Gq1tkOq8XO0HDCZ9nOTtRpB6-gPe
+ - LOS_LOOP: https://drive.google.com/drive/folders/1g5v2Gq1tkOq8XO0HDCZ9nOTtRpB6-gPe
 
 
-## Citation [optional]
+## Citation
 Kindly cite the following paper, if you intend to use our model or its associated architectures/approaches in your 
 work