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README.md

@@ -39,7 +39,7 @@ Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Da
 ## Results
 
 The training logs for the current model can be found here:
- - [https://wandb.ai/openclimatefix/pvnet2.1/runs/aswcdyxy](https://wandb.ai/openclimatefix/pvnet2.1/runs/aswcdyxy)
+ - [https://wandb.ai/openclimatefix/pvnet2.1/runs/rydw0jo0](https://wandb.ai/openclimatefix/pvnet2.1/runs/rydw0jo0)
 
 
 The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
@@ -53,5 +53,11 @@ Trained on a single NVIDIA Tesla T4
 
 ### Software
 
+This model was trained using the following Open Climate Fix packages:
+
 - [1] https://github.com/openclimatefix/PVNet
-- [2] https://github.com/openclimatefix/ocf-data-sampler
+- [2] https://github.com/openclimatefix/ocf-data-sampler
+
+The versions of these packages can be found below:
+ - pvnet==4.1.6
+ - ocf-data-sampler==0.2.17.post0+git.563e6370.dirty

data_config.yaml

@@ -3,6 +3,7 @@ general:
   name: PVNet current
 input_data:
   gsp:
+    boundaries_version: '20250109'
     dropout_fraction: 0
     dropout_timedeltas_minutes: []
     interval_end_minutes: 480
@@ -24,7 +25,7 @@ input_data:
       - mcc
       - lcc
       - tcc
-      - sde
+      - sd
       - sr
       - duvrs
       - u10
@@ -59,7 +60,7 @@ input_data:
         mcc:
           mean: 0.3288780450820923
           std: 0.38039860129356384
-        sde:
+        sd:
           mean: 8.107526082312688e-05
           std: 0.000913831521756947
         t2m:
@@ -191,6 +192,6 @@ input_data:
     time_resolution_minutes: 5
     zarr_path: PLACEHOLDER.zarr
   solar_position:
-    interval_end_minutes: 480
+    interval_end_minutes: 2160
     interval_start_minutes: -120
     time_resolution_minutes: 30

model_config.yaml

@@ -0,0 +1,401 @@
+_target_: pvnet.models.multimodal.multimodal.Model
+output_quantiles:
+- 0.02
+- 0.1
+- 0.25
+- 0.5
+- 0.75
+- 0.9
+- 0.98
+nwp_encoders_dict:
+  ukv:
+    _target_: pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet
+    _partial_: true
+    in_channels: 11
+    out_features: 256
+    number_of_conv3d_layers: 6
+    conv3d_channels: 32
+    image_size_pixels: 24
+  ecmwf:
+    _target_: pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet
+    _partial_: true
+    in_channels: 12
+    out_features: 256
+    number_of_conv3d_layers: 4
+    conv3d_channels: 32
+    image_size_pixels: 12
+sat_encoder:
+  _target_: pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2
+  _partial_: true
+  in_channels: 11
+  out_features: 256
+  image_size_pixels: 24
+  hidden_channels: 32
+  n_res_blocks: 3
+  res_block_layers: 3
+  batch_norm: true
+  dropout_frac: 0.0
+add_image_embedding_channel: false
+pv_encoder: null
+output_network:
+  _target_: pvnet.models.multimodal.linear_networks.networks.ResFCNet2
+  _partial_: true
+  fc_hidden_features: 128
+  n_res_blocks: 6
+  res_block_layers: 2
+  dropout_frac: 0.0
+embedding_dim: 16
+include_sun: true
+include_gsp_yield_history: false
+forecast_minutes: 480
+history_minutes: 120
+min_sat_delay_minutes: 30
+sat_history_minutes: 60
+pv_history_minutes: 180
+nwp_history_minutes:
+  ukv: 120
+  ecmwf: 120
+nwp_forecast_minutes:
+  ukv: 480
+  ecmwf: 480
+optimizer:
+  _target_: pvnet.optimizers.EmbAdamWReduceLROnPlateau
+  lr: 0.0001
+  weight_decay: 0.25
+  amsgrad: true
+  patience: 10
+  factor: 0.1
+  threshold: 0.002
+location_id_mapping:
+  1: 1
+  2: 2
+  3: 3
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+adapt_batches: true

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 34546610
+oid sha256:b167289e37df64574c50d76fe466c8d6423ac9f105250229a5c85d152a6ae6fe
+size 34547915