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  1. README.md +6 -4
  2. config.json +5 -14
  3. pytorch_model.bin +2 -2
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  language: en
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- license: mit
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  library_name: pytorch
 
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  ---
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@@ -28,12 +28,14 @@ This model class sums the output of the PVNet model's GSP level predictions to m
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  <!-- 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. -->
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- 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.
 
 
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  ### Preprocessing
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- Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [3].
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  ## Results
@@ -53,4 +55,4 @@ Trained on a single NVIDIA Tesla T4
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  - [1] https://github.com/openclimatefix/PVNet_summation
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  - [2] https://github.com/openclimatefix/PVNet
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- - [3] https://github.com/openclimatefix/ocf_datapipes
 
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  ---
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  language: en
 
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  library_name: pytorch
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+ license: mit
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  ---
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  <!-- 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. -->
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+ The model is trained on the output predictions of our PVNet model which gives GSP (i.e. UK regional) level predictions
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+ of solar power across Great Britain. This model is trained to take those predictions and use them to estimate
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+ the national total with uncertainty estimates.
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  ### Preprocessing
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+ The input data is prepared with the `ocf_data_sampler` [3].
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  ## Results
 
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  - [1] https://github.com/openclimatefix/PVNet_summation
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  - [2] https://github.com/openclimatefix/PVNet
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+ - [3] https://github.com/openclimatefix/ocf-data-sampler
config.json CHANGED
@@ -1,32 +1,23 @@
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  {
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  "_target_": "pvnet_summation.models.flat_model.FlatModel",
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- "output_quantiles": [
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- 0.02,
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- 0.1,
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- 0.25,
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- 0.5,
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- 0.75,
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- 0.9,
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- 0.98
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- ],
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  "model_name": "openclimatefix/pvnet_uk_region",
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- "model_version": "35d55181a82440bdd087f380d650bfd0b64bd322",
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  "output_network": {
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  "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
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  "_partial_": true,
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  "fc_hidden_features": 128,
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  "n_res_blocks": 2,
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  "res_block_layers": 2,
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- "dropout_frac": 0.1
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  },
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- "relative_scale_pvnet_outputs": true,
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- "predict_difference_from_sum": true,
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  "optimizer": {
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  "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",
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  "lr": 0.0001,
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  "weight_decay": 0.25,
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  "amsgrad": true,
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- "patience": 10,
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  "factor": 0.1,
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  "threshold": 0.0
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  }
 
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  {
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  "_target_": "pvnet_summation.models.flat_model.FlatModel",
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+ "output_quantiles": null,
 
 
 
 
 
 
 
 
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  "model_name": "openclimatefix/pvnet_uk_region",
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+ "model_version": "20b882bd4ceaee190a1c994d861f8e5d553ea843",
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  "output_network": {
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  "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
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  "_partial_": true,
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  "fc_hidden_features": 128,
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  "n_res_blocks": 2,
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  "res_block_layers": 2,
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+ "dropout_frac": 0.0
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  },
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+ "predict_difference_from_sum": false,
 
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  "optimizer": {
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  "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",
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  "lr": 0.0001,
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  "weight_decay": 0.25,
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  "amsgrad": true,
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+ "patience": 20,
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  "factor": 0.1,
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  "threshold": 0.0
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  }
pytorch_model.bin CHANGED
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