{
  "id": 586951,
  "title": "GRU/LSTM not work for me",
  "url": "/competitions/cmi-detect-behavior-with-sensor-data/discussion/586951",
  "author_name": "Ryenhails",
  "post_date": "2025-06-29T06:44:59.111000",
  "votes": 3,
  "comment_count": 18,
  "views": 0,
  "content": "<p>Hi everyone, I'm currently a bit stuck with architecture iteration and finding it difficult to effectively incorporate classic temporal models like GRU/LSTM. It seems that adding any additional module to my current 1D-CNN architecture actually reduces performance on both CV and LB. Has anyone else experienced similar results?</p>",
  "messages": [
    {
      "id": 3235922,
      "postDate": "2025-06-29T18:58:53.460Z",
      "content": "<p>Same here, whenever I add anything rnn or attention related to my cnn architecture, performance decreases. 🥸</p>",
      "rawMarkdown": "Same here, whenever I add anything rnn or attention related to my cnn architecture, performance decreases. 🥸",
      "votes": 3
    },
    {
      "id": 3235384,
      "postDate": "2025-06-29T06:44:59.113Z",
      "content": "<p>Hi everyone, I'm currently a bit stuck with architecture iteration and finding it difficult to effectively incorporate classic temporal models like GRU/LSTM. It seems that adding any additional module to my current 1D-CNN architecture actually reduces performance on both CV and LB. Has anyone else experienced similar results?</p>",
      "rawMarkdown": "Hi everyone, I'm currently a bit stuck with architecture iteration and finding it difficult to effectively incorporate classic temporal models like GRU/LSTM. It seems that adding any additional module to my current 1D-CNN architecture actually reduces performance on both CV and LB. Has anyone else experienced similar results?",
      "votes": 3
    },
    {
      "id": 3235495,
      "postDate": "2025-06-29T10:05:15.330Z",
      "content": "<p>I use LSTM-based models and will try to beat it with attention-based ones and 1D CNN.</p>",
      "rawMarkdown": "I use LSTM-based models and will try to beat it with attention-based ones and 1D CNN.",
      "votes": 4,
      "replies": [
        {
          "id": 3246430,
          "postDate": "2025-07-10T23:37:55.697Z",
          "content": "<p>Hey hey, any results to share from your attention and CNN experiments? </p>",
          "rawMarkdown": "Hey hey, any results to share from your attention and CNN experiments? ",
          "replies": [
            {
              "id": 3246531,
              "postDate": "2025-07-11T05:23:07.213Z",
              "content": "<p>Attention is on par with LSTM!</p>",
              "rawMarkdown": "Attention is on par with LSTM!",
              "votes": 1
            },
            {
              "id": 3246726,
              "postDate": "2025-07-11T12:06:08.883Z",
              "content": "<p>Thanks for the response. Are you using an implementation that's different from public notebooks? I'll revisit my testing with attention. </p>",
              "rawMarkdown": "Thanks for the response. Are you using an implementation that's different from public notebooks? I'll revisit my testing with attention. "
            },
            {
              "id": 3246743,
              "postDate": "2025-07-11T12:44:51.137Z",
              "content": "<p>I don't even remember any public notebook with pure attention-based architecture.</p>",
              "rawMarkdown": "I don't even remember any public notebook with pure attention-based architecture."
            },
            {
              "id": 3246792,
              "postDate": "2025-07-11T14:41:30.640Z",
              "content": "<p>Are you using attention pooling? I'm pretty sure the biggest improvements I can make to my models relate to pooling before class predictions. </p>",
              "rawMarkdown": "Are you using attention pooling? I'm pretty sure the biggest improvements I can make to my models relate to pooling before class predictions. "
            }
          ]
        }
      ]
    },
    {
      "id": 3236191,
      "postDate": "2025-06-30T04:03:32.913Z",
      "content": "<p>i tried using attention and my score dropped too!</p>",
      "rawMarkdown": "i tried using attention and my score dropped too!",
      "votes": 1
    },
    {
      "id": 3235459,
      "postDate": "2025-06-29T09:26:31.620Z",
      "content": "<p>Hello, I am in the process of doing some ablation tests to my current IMU only architecture over the next week, but I remember some random attempts of incorporating LSTM also not working. Same thing for any sort of attention usage, but I will revisit both.</p>",
      "rawMarkdown": "Hello, I am in the process of doing some ablation tests to my current IMU only architecture over the next week, but I remember some random attempts of incorporating LSTM also not working. Same thing for any sort of attention usage, but I will revisit both.",
      "votes": 2
    },
    {
      "id": 3246734,
      "postDate": "2025-07-11T12:30:52.803Z",
      "content": "<p>Long-term dependency causes overfit on the imu data.</p>",
      "rawMarkdown": "Long-term dependency causes overfit on the imu data."
    },
    {
      "id": 3236979,
      "postDate": "2025-06-30T19:38:07.923Z",
      "content": "<p>I think using gru after cnn does help me in my model</p>",
      "rawMarkdown": "I think using gru after cnn does help me in my model",
      "replies": [
        {
          "id": 3236989,
          "postDate": "2025-06-30T19:48:18.343Z",
          "content": "<p>BTW, did you reach 0.84 with imu only model?</p>",
          "rawMarkdown": "BTW, did you reach 0.84 with imu only model?",
          "replies": [
            {
              "id": 3237581,
              "postDate": "2025-07-01T07:16:57.063Z",
              "content": "<p>nope, IMU only 0.82 for now</p>",
              "rawMarkdown": "nope, IMU only 0.82 for now",
              "votes": 3
            },
            {
              "id": 3237645,
              "postDate": "2025-07-01T07:58:49.323Z",
              "content": "<p>Unbelievable, that still so high.😂</p>",
              "rawMarkdown": "Unbelievable, that still so high.😂"
            },
            {
              "id": 3237686,
              "postDate": "2025-07-01T08:32:44.030Z",
              "rawMarkdown": "",
              "isDeleted": true
            },
            {
              "id": 3237687,
              "postDate": "2025-07-01T08:33:00.570Z",
              "content": "<p>if it's not a secret, is it single model or ensemble?</p>",
              "rawMarkdown": "if it's not a secret, is it single model or ensemble?"
            },
            {
              "id": 3237688,
              "postDate": "2025-07-01T08:33:34.537Z",
              "content": "<p>single model</p>",
              "rawMarkdown": "single model",
              "votes": 1
            },
            {
              "id": 3237759,
              "postDate": "2025-07-01T09:36:35.733Z",
              "content": "<p>so, features other than imu are of no use at all?</p>",
              "rawMarkdown": "so, features other than imu are of no use at all?"
            }
          ]
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 3235922,
      "author_name": "Jan Brederecke",
      "author_url": "",
      "post_date": "2025-06-29T18:58:53.460000",
      "content": "<p>Same here, whenever I add anything rnn or attention related to my cnn architecture, performance decreases. 🥸</p>",
      "votes": 3,
      "replies": []
    },
    {
      "id": 3235495,
      "author_name": "Ogurtsov",
      "author_url": "",
      "post_date": "2025-06-29T10:05:15.330000",
      "content": "<p>I use LSTM-based models and will try to beat it with attention-based ones and 1D CNN.</p>",
      "votes": 4,
      "replies": [
        {
          "id": 3246430,
          "author_name": "Jack",
          "author_url": "",
          "post_date": "2025-07-10T23:37:55.697000",
          "content": "<p>Hey hey, any results to share from your attention and CNN experiments? </p>",
          "votes": 0,
          "replies": [
            {
              "id": 3246531,
              "author_name": "Ogurtsov",
              "author_url": "",
              "post_date": "2025-07-11T05:23:07.213000",
              "content": "<p>Attention is on par with LSTM!</p>",
              "votes": 1,
              "replies": []
            },
            {
              "id": 3246726,
              "author_name": "Jack",
              "author_url": "",
              "post_date": "2025-07-11T12:06:08.883000",
              "content": "<p>Thanks for the response. Are you using an implementation that's different from public notebooks? I'll revisit my testing with attention. </p>",
              "votes": 0,
              "replies": []
            },
            {
              "id": 3246743,
              "author_name": "Ogurtsov",
              "author_url": "",
              "post_date": "2025-07-11T12:44:51.137000",
              "content": "<p>I don't even remember any public notebook with pure attention-based architecture.</p>",
              "votes": 0,
              "replies": []
            },
            {
              "id": 3246792,
              "author_name": "Jack",
              "author_url": "",
              "post_date": "2025-07-11T14:41:30.640000",
              "content": "<p>Are you using attention pooling? I'm pretty sure the biggest improvements I can make to my models relate to pooling before class predictions. </p>",
              "votes": 0,
              "replies": []
            }
          ]
        }
      ]
    },
    {
      "id": 3236191,
      "author_name": "Vaishnavi Mudaliar",
      "author_url": "",
      "post_date": "2025-06-30T04:03:32.913000",
      "content": "<p>i tried using attention and my score dropped too!</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 3235459,
      "author_name": "Andrei Zamfir",
      "author_url": "",
      "post_date": "2025-06-29T09:26:31.620000",
      "content": "<p>Hello, I am in the process of doing some ablation tests to my current IMU only architecture over the next week, but I remember some random attempts of incorporating LSTM also not working. Same thing for any sort of attention usage, but I will revisit both.</p>",
      "votes": 2,
      "replies": []
    },
    {
      "id": 3246734,
      "author_name": "Tom",
      "author_url": "",
      "post_date": "2025-07-11T12:30:52.803000",
      "content": "<p>Long-term dependency causes overfit on the imu data.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 3236979,
      "author_name": "menglei",
      "author_url": "",
      "post_date": "2025-06-30T19:38:07.923000",
      "content": "<p>I think using gru after cnn does help me in my model</p>",
      "votes": 0,
      "replies": [
        {
          "id": 3236989,
          "author_name": "menglei",
          "author_url": "",
          "post_date": "2025-06-30T19:48:18.343000",
          "content": "<p>BTW, did you reach 0.84 with imu only model?</p>",
          "votes": 0,
          "replies": [
            {
              "id": 3237581,
              "author_name": "Ryenhails",
              "author_url": "",
              "post_date": "2025-07-01T07:16:57.063000",
              "content": "<p>nope, IMU only 0.82 for now</p>",
              "votes": 3,
              "replies": []
            },
            {
              "id": 3237645,
              "author_name": "menglei",
              "author_url": "",
              "post_date": "2025-07-01T07:58:49.323000",
              "content": "<p>Unbelievable, that still so high.😂</p>",
              "votes": 0,
              "replies": []
            },
            {
              "id": 3237686,
              "author_name": "",
              "author_url": "",
              "post_date": "2025-07-01T08:32:44.030000",
              "content": "",
              "votes": 0,
              "replies": []
            },
            {
              "id": 3237687,
              "author_name": "lightsource<3",
              "author_url": "",
              "post_date": "2025-07-01T08:33:00.570000",
              "content": "<p>if it's not a secret, is it single model or ensemble?</p>",
              "votes": 0,
              "replies": []
            },
            {
              "id": 3237688,
              "author_name": "Ryenhails",
              "author_url": "",
              "post_date": "2025-07-01T08:33:34.537000",
              "content": "<p>single model</p>",
              "votes": 1,
              "replies": []
            },
            {
              "id": 3237759,
              "author_name": "Vaishnavi Mudaliar",
              "author_url": "",
              "post_date": "2025-07-01T09:36:35.733000",
              "content": "<p>so, features other than imu are of no use at all?</p>",
              "votes": 0,
              "replies": []
            }
          ]
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "3235922": "Same here, whenever I add anything rnn or attention related to my cnn architecture, performance decreases. 🥸",
    "3235384": "Hi everyone, I'm currently a bit stuck with architecture iteration and finding it difficult to effectively incorporate classic temporal models like GRU/LSTM. It seems that adding any additional module to my current 1D-CNN architecture actually reduces performance on both CV and LB. Has anyone else experienced similar results?",
    "3235495": "I use LSTM-based models and will try to beat it with attention-based ones and 1D CNN.",
    "3236191": "i tried using attention and my score dropped too!",
    "3235459": "Hello, I am in the process of doing some ablation tests to my current IMU only architecture over the next week, but I remember some random attempts of incorporating LSTM also not working. Same thing for any sort of attention usage, but I will revisit both.",
    "3246734": "Long-term dependency causes overfit on the imu data.",
    "3236979": "I think using gru after cnn does help me in my model"
  }
}