classification_test.json

{                 
   "model_name": "MultiAttnHeadSimple",
   "model_type": "PyTorch",
   "model_params": {
     "number_time_series":2, 
     "seq_len":6, 
     "final_layer": "Softmax",
     "output_seq_len": 1,
     "output_dim": 9
    },
    "dataset_params":
    { "class": "GeneralClassificationLoader",
      "n_classes": 9,
       "training_path": "tests/test_data/keag_small.csv",
       "validation_path": "tests/test_data/keag_small.csv",
       "test_path": "tests/test_data/keag_small.csv",
       "sequence_length":6,
       "batch_size":20,
       "forecast_history":6,
       "train_end": 300,
       "valid_start":0,
       "valid_end": 300,
       "test_end": 303,
       "target_col": ["precip"],
       "relevant_cols": ["precip", "temp", "cfs"],
       "scaler": "StandardScaler", 
       "interpolate": false
    },

    "training_params":
    {
       "criterion":"FocalLoss",
       "optimizer": "Adam",
       "criterion_params":
            {"alpha": 0.5,
             "reduction": "sum"},
       "optim_params":
       {},
       "lr": 0.3,
       "epochs": 1,
       "batch_size":4
    },
    "GCS": false,
   
    "wandb": {
       "name": "flood_forecast_circleci",
       "tags": ["dummy_run", "circleci", "multi_head", "classification"],
       "project": "repo-flood_forecast"
    },
   "forward_params":{},
   "metrics":["CrossEntropyLoss"]
}