config.json

{
  "model_name": "liquidnet-har-classifier",
  "description": "\n    LiquidNet\u6a21\u578b\u7528\u65bcUCI HAR\u6578\u64da\u96c6\u7684\u4eba\u9ad4\u6d3b\u52d5\u8b58\u5225\u3002\n    \u8a72\u6a21\u578b\u4f7f\u75289\u500b\u539f\u59cb\u611f\u6e2c\u5668\u4fe1\u865f\uff083\u8ef8\u52a0\u901f\u5ea6\u8a08\u548c3\u8ef8\u9640\u87ba\u5100\uff09\u9032\u884c\u8a13\u7df4\uff0c\n    \u53ef\u4ee5\u8b58\u52256\u7a2e\u4e0d\u540c\u7684\u4eba\u9ad4\u6d3b\u52d5\u3002\n    \n    \u7279\u9ede\uff1a\n    - \u4f7f\u7528LiquidNet\u67b6\u69cb\u8655\u7406\u6642\u9593\u5e8f\u5217\u6578\u64da\n    - \u8f38\u5165\uff1a9\u500b\u7279\u5fb5\uff083\u8ef8\u52a0\u901f\u5ea6\u8a08\u548c3\u8ef8\u9640\u87ba\u5100\uff09\n    - \u8f38\u51fa\uff1a6\u7a2e\u6d3b\u52d5\u985e\u5225\n    - \u6642\u9593\u6b65\u9577\uff1a128\n    ",
  "architecture": "LiquidNet",
  "input_size": 9,
  "hidden_size": 128,
  "output_size": 6,
  "steps": 128,
  "training_metrics": {
    "best_val_acc": 56.09093993892094,
    "epoch": 44
  }
}