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README.md

@@ -28,7 +28,7 @@ This model class sums the output of the PVNet model's GSP level predictions to m
 
 <!-- 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 Jan 2019- May 2022 and validated on data from May 2022 - May 2023.
+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.
 
 
 ### Preprocessing
@@ -38,7 +38,9 @@ Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [3].
 
 ## Results
 
-The training logs for the current model can be found [here on wandb](https://wandb.ai/openclimatefix/pvnet_day_ahead_summation).
+The training logs for the current model can be found [here on wandb](https://wandb.ai/openclimatefix/pvnet_summation/runs/).
+
+The training logs for all model runs of PVNet_summation can be found [here](https://wandb.ai/openclimatefix/pvnet_summation).
 
 Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
 

config.json

@@ -1,13 +1,9 @@
 {
     "_target_": "pvnet_summation.models.flat_model.FlatModel",
     "output_quantiles": [
-        0.02,
         0.1,
-        0.25,
         0.5,
-        0.75,
-        0.9,
-        0.98
+        0.9
     ],
     "model_name": "openclimatefix/pvnet_uk_region_day_ahead",
     "model_version": "d87565731692a6003e43caac4feaed0f69e79272",
@@ -17,13 +13,13 @@
         "fc_hidden_features": 128,
         "n_res_blocks": 2,
         "res_block_layers": 2,
-        "dropout_frac": 0.1
+        "dropout_frac": 0.0
     },
-    "predict_difference_from_sum": false,
+    "predict_difference_from_sum": true,
     "optimizer": {
         "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",
         "lr": 0.0001,
-        "weight_decay": 0.25,
+        "weight_decay": 0.1,
         "amsgrad": true,
         "patience": 10,
         "factor": 0.1,

pytorch_model.bin

@@ -1,3 +1,3 @@
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-oid sha256:17561f716f5e460abb12078493c58db16abf1297a353d236ceaf5450565b8312
-size 176615346
+oid sha256:8267af3ce3eaa0b347714d9bcfff6dbd8f9287f1300b9217d632ae0f2cc2f2bc
+size 176654970