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README.md

@@ -28,7 +28,7 @@ This model class uses satellite data, numericl weather predictions, and recent G
 
 <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
-The model is trained on data from 2017-2020 and validated on data from 2021. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) for more details.
+The model is trained on data from 2019-2022 and validated on data from 2022-2023. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) for more details.
 
 
 ### Preprocessing
@@ -38,7 +38,9 @@ Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [2].
 
 ## Results
 
-The training logs for the current model can be found [here on wandb](https://wandb.ai/openclimatefix/pvnet2.1/runs/None).
+The training logs for the current model can be found here:
+ - [https://wandb.ai/openclimatefix/pvnet2.1/runs/rvlntlb4](https://wandb.ai/openclimatefix/pvnet2.1/runs/rvlntlb4)
+
 
 The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
 

config.json

@@ -40,7 +40,7 @@
         "dropout_frac": 0.0
     },
     "embedding_dim": 16,
-    "include_sun": false,
+    "include_sun": true,
     "include_gsp_yield_history": false,
     "forecast_minutes": 2880,
     "history_minutes": 60,

data_config.yaml

@@ -7,6 +7,9 @@ input_data:
   default_history_minutes: 60
   nwp:
     ecmwf:
+      dropout_fraction: 1.0
+      dropout_timedeltas_minutes:
+      - -420
       forecast_minutes: 2880
       history_minutes: 60
       nwp_channels:

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 330260298
+oid sha256:84d1d5ec959b1eb657d94c590fb4af84df15a55d9deb1bd02cdc13ae58c8695f
+size 330294354