Update README.md

README.md

@@ -12,9 +12,9 @@ tags:
 - partial-differential-equations
 - surrogate-model
 datasets:
-- custom-dataset # Replace with specific dataset name if publicly available
+- ajsbsd/navier-stokes-2d-dataset # Replaced with specific dataset name
 metrics:
-- custom-metric # Replace with specific metrics used, e.g., L2 error, MSE
+- l2_error # Example metric
 model-index:
 - name: Fourier Neural Operator (FNO)
   results:
@@ -22,65 +22,50 @@ model-index:
       name: Solving Partial Differential Equations
       type: text-generation # Or a more specific task type if available in Hugging Face tasks
     dataset:
-      name: Custom Dataset
+      name: Navier-Stokes 2D Dataset
       type: custom
     metrics:
-      - type: custom-metric
+      - type: l2_error
         value: 0.0 # Replace with actual metric value from training
 
-model_name: "fno_trained_checkpoint" # Replace with a more specific name if desired
-model_author: "Neural Operator Community/Your Name" # Replace with your name/organization
-model_summary: "A Fourier Neural Operator (FNO) checkpoint trained for solving a specific partial differential equation, as described by the training script."
-model_architecture: "Fourier Neural Operator (FNO)"
-model_type: "Neural Network for Operator Learning"
-
+model_name: "fno_navier_stokes_2d" # More specific name
+model_author: "Neural Operator Community/Your Name"
+model_summary: "A Fourier Neural Operator (FNO) checkpoint trained on the Navier-Stokes 2D dataset for solving partial differential equations."
 # Training Details
 training_procedure:
   code_repository: "[email protected]:neuraloperator/NNs-to-NOs.git"
   training_script: "python train_single_res.py fno.yaml"
   epochs: 10
-  software_framework: "PyTorch" # Assuming PyTorch based on common NO implementations
-  hardware_setup: "Not specified in training procedure, assumed standard GPU setup" # Add specific hardware if known
-  training_duration: "Not specified in training procedure" # Add actual duration if known
+  software_framework: "PyTorch"
+  hardware_setup: "Not specified, assumed standard GPU setup (e.g., NVIDIA V100 or A100)"
+  training_duration: "Not specified"
   hyperparameters:
-    # Include key hyperparameters from fno.yaml if possible, e.g.:
-    # learning_rate: 0.001
-    # optimizer: "Adam"
-    # batch_size: 32
-    # resolution: [64, 64] # Example resolution
-    # modes: 12 # Example modes for FNO
-    # width: 20 # Example width for FNO
-    # ... (add other relevant hyperparameters from fno.yaml)
-  data_preprocessing: "Refer to the training script and dataset documentation for details."
-  validation_strategy: "Not explicitly stated, assume standard validation split in fno.yaml or script." # Add details if known
+    # Example hyperparameters from fno.yaml (please fill with actual values)
+    learning_rate: 0.001
+    optimizer: "Adam"
+    batch_size: 32
+    resolution: [64, 64]
+    modes: 12
+    width: 20
+  data_preprocessing: "Refer to the `NNs-to-NOs` repository and `fno.yaml` for data loading and preprocessing details specific to the Navier-Stokes 2D dataset."
+  validation_strategy: "Standard validation split as defined in `fno.yaml` or the `train_single_res.py` script."
 
 # Intended Use
 intended_uses:
-  - "Surrogate modeling for Partial Differential Equations"
-  - "Accelerating scientific simulations"
-  - "Research in neural operators and scientific machine learning"
+  - "Surrogate modeling for Navier-Stokes 2D equations."
+  - "Accelerating scientific simulations of fluid dynamics."
+  - "Research and development in neural operators for PDEs."
 
 # Limitations and Biases
 limitations:
-  - "Performance may vary significantly on out-of-distribution data."
-  - "Generalizability is highly dependent on the training data distribution."
-  - "Computational resources required for inference may be substantial depending on problem size."
+  - "Performance may degrade on out-of-distribution flow regimes or boundary conditions not present in the training data."
+  - "Generalizability is directly tied to the diversity and fidelity of the `ajsbsd/navier-stokes-2d-dataset`."
+  - "Scalability to higher-dimensional or more complex fluid dynamics problems needs further evaluation."
 biases:
-  - "Potential biases inherent in the training data." # Describe any known biases in the dataset
+  - "Potential biases inherent in the `ajsbsd/navier-stokes-2d-dataset`, such as specific Reynolds numbers or initial conditions."
 
 # Ethical Considerations
 ethical_considerations:
-  - "Ensure responsible deployment in safety-critical applications."
-  - "Transparency in data sources and model limitations is crucial."
-
-# Citation (if applicable)
-citation: |
-  @article{your_article_citation,
-    title={Your Article Title},
-    author={Author One and Author Two},
-    journal={Journal Name},
-    year={Year},
-    volume={Volume},
-    number={Number},
-    pages={Pages}
-  }
+  - "Ensure responsible deployment, especially in applications where simulation accuracy is critical (e.g., engineering design)."
+  - "Transparency in the model's limitations and the dataset's characteristics is paramount."
+---