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README.md

@@ -9,12 +9,12 @@ license: mit
 
 
 
-# PVNet2
+# PVNet_summation
 
 ## Model Description
 
 <!-- Provide a longer summary of what this model is/does. -->
-This model class uses satellite data, numerical weather predictions, and recent Grid Service Point( GSP) PV power output to forecast the near-term (~8 hours) PV power output at all GSPs. More information can be found in the model repo [1] and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
+This model class sums the output of the PVNet model's GSP level predictions to make a national forecast of UK PV output. More information can be found in the model repo [1], the PVNet model repo [2], and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
 
 - **Developed by:** openclimatefix
 - **Model type:** Fusion model
@@ -28,21 +28,21 @@ This model class uses satellite data, numerical weather predictions, and recent
 
 <!-- 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 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.
+The model is trained on the output predictions of our PVNet model which gives GSP (i.e. UK regional) level predictions
+of solar power across Great Britain. This model is trained to take those predictions and use them to estimate
+the national total with uncertainty estimates.
 
 
 ### Preprocessing
 
-Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Dataset [2].
+The input data is prepared with the `ocf_data_sampler` [3].
 
 
 ## Results
 
-The training logs for the current model can be found here:
- - [https://wandb.ai/None/runs/1w638yac](https://wandb.ai/None/runs/1w638yac)
+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 PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
+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)
 
@@ -53,5 +53,6 @@ Trained on a single NVIDIA Tesla T4
 
 ### Software
 
-- [1] https://github.com/openclimatefix/PVNet
-- [2] https://github.com/openclimatefix/ocf-data-sampler
+- [1] https://github.com/openclimatefix/PVNet_summation
+- [2] https://github.com/openclimatefix/PVNet
+- [3] https://github.com/openclimatefix/ocf-data-sampler

config.json

@@ -10,15 +10,16 @@
         0.98
     ],
     "model_name": "openclimatefix/pvnet_uk_region",
-    "model_version": "d81a9cf8adca49739ea6a3d031e36510f44744a1",
+    "model_version": "963d0cc47d6c9df9a08b9e05f8fd064a637346ba",
     "output_network": {
         "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
         "_partial_": true,
         "fc_hidden_features": 128,
         "n_res_blocks": 2,
         "res_block_layers": 2,
-        "dropout_frac": 0.0
+        "dropout_frac": 0.1
     },
+    "relative_scale_pvnet_outputs": false,
     "predict_difference_from_sum": true,
     "optimizer": {
         "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 95552878
+oid sha256:4c021dc0190e51f464d3bee3c880694fe0d7642bad03d1a82d35ab415327be0e
+size 100831838