Row 5255

Row ID: 5255 | Dataset Entry | Axioma AXP Content Repository

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I'm indeed no expert in this area. Perhaps can help you understand the problem. During the training you need to look at the dimension and size of your output layer and this layer has to have the same dimension and size as what you are using the model to predict. i.e. the predicted output from the model has to have the same shape as the output layer.

I recently had this problem, my output layer was expecting in the following (batch size, 5), i.e. my batch size was 2223 and the number of output nodes was 5.

but once I was running my 'y' values through the keras.utils.to\_categorical this was producing a target array (batch size, 5, 90) resulting in a mismatch between target (values that were produced by to\_categorical and the output layer.

Field	Value
text	I'm indeed no expert in this area. Perhaps can help you understand the problem. During the training you need to look at the dimension and size of your output layer and this layer has to have the same dimension and size as what you are using the model to predict. i.e. the predicted output from the model has to have the same shape as the output layer. I recently had this problem, my output layer was expecting in the following (batch size, 5), i.e. my batch size was 2223 and the number of outp…
label	r/neuralnetworks
dataType	comment
communityName	r/neuralnetworks
datetime	2024-04-28
username_encoded	Z0FBQUFBQm5LakwyejZybmhweE8yMDA1WTFVd2xfQWhjblpTV0dIcXFrNVZxTFZ4UVlDVFo2UUNFRVJVZmxmc1lkSVQ0S2o5cHEweGYwMzlZTm1SV3dic2taT0I2YUJuakRZcm1yc0Z4d2RuRC1vdnFVZm4ydTg9
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Raw Record

{
  "text": "I'm indeed no expert in this area. Perhaps can help you understand the problem.  During the training you need to look at the dimension and size of your output layer and this layer has to have the same dimension and size as what you are using the model to predict.  i.e. the predicted output from the model has to have the same shape as the output layer.  \n\nI recently had this problem, my output layer was expecting in the following (batch size, 5), i.e. my batch size was 2223 and the number of output nodes was 5. \n\nbut once I was running my 'y' values through the keras.utils.to\\_categorical this was producing a target array (batch size, 5, 90) resulting in a mismatch between target (values that were produced by to\\_categorical and the output layer.",
  "label": "r/neuralnetworks",
  "dataType": "comment",
  "communityName": "r/neuralnetworks",
  "datetime": "2024-04-28",
  "username_encoded": "Z0FBQUFBQm5LakwyejZybmhweE8yMDA1WTFVd2xfQWhjblpTV0dIcXFrNVZxTFZ4UVlDVFo2UUNFRVJVZmxmc1lkSVQ0S2o5cHEweGYwMzlZTm1SV3dic2taT0I2YUJuakRZcm1yc0Z4d2RuRC1vdnFVZm4ydTg9",
  "url_encoded": "Z0FBQUFBQm5Lak9GMm82NHB3THNNeXZTeExpSExKU29wZlo0OFNrRF9pY2lORkR1T05YUjhhNEhwdFlXN2tUTVFKei1CMS1nbG0wRTNXdDBfdlpwWEV4TlJjV1dIRmpSLWFacUlGM2xqZGZQMnpwTHFvM3k2LU9GSkNsWDJXcUF2WDFlZ1JXT2lfVTNxMko3WElRNGlGeVNBUl9RU2xDMFVRc25Cb1FMaEtKSTM3d29uQkJIVG9iQ001elJNVENBMUJfMWl0cGV2ZmFqUWtOUnlUNk11REtGTDAtT0o0ZTB6Ym1CUGpHWVMtc3JfSVMwMmNjeEhnMD0="
}

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Entry Information

Entry ID: 5255
Repository: Axioma AXP
Dataset: arrmlet/reddit_dataset_36
Total Entries: 100,000