Row 65183

Row ID: 65183 | Dataset Entry | Axioma AXP Content Repository

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I think in the original paper they used a function similar to MSE loss but a little bit different. but I saw an implementation by DeepFindr where he used L1 loss and got some good results. I also wanna train it with MSE loss one more time to see if it makes a difference

FieldValue
text I think in the original paper they used a function similar to MSE loss but a little bit different. but I saw an implementation by DeepFindr where he used L1 loss and got some good results. I also wanna train it with MSE loss one more time to see if it makes a difference
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-23
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url_encoded Z0FBQUFBQm5Lak9zWEpnV0xOc3JSZmFmcVpvdEo1NFZSN3ZKV2pVblNuclQtVVRNWGdoTFh4WDRfVWFNWUJ5OVlrMGZNbHZJb1pCd1dpUmVwN1lUSC1vTGFJWXF2ZVMxclBWelRwRGQ3UUYxbHA3ZU03VUNIcWwzZUNtZTcxZ3liQTFEZDMxcTFVUFlJb3FJQlhUSkdZQVJzaWlWcTREMERaeEswSlNPbktXTV9Udkk5c0hUZXB6UkZoTkhzYnVrLWRiUXlHNXBYQUV4WUFoQjRfNXBoZEtRdlhoRVRNdkkwYlJiT3NwYjNfTDJGY0RaZXRiYUhQRT0=

Raw Record

{
  "text": "I think in the original paper they used a function similar to MSE loss but a little bit different. but I saw an implementation by DeepFindr where he used L1 loss and got some good results. I also wanna train it with MSE loss one more time to see if it makes a difference",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1iRkVQdFc4RElicXB5UGh1UGloTGdiSkVRb1VKc0pPVlNaRURzNHA3R1VSN29nX3Z6TFhqVWpNZlRSNmVvdkFqTUF4Vm82VkJvTS1iWkhKMUpzc09CT1E9PQ==",
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}
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