CoolFace
Modelpublic

yimiwang/roberta-petco-fullemailbody-ctr

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
0likes13downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

roberta-petco-fullemailbody-ctr

This model is a fine-tuned version of yimiwang/bert-petco-emailbody-ctr on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0032
  • —Mse: 0.0032
  • —Rmse: 0.0568
  • —Mae: 0.0421
  • —R2: 0.3701

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 1e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossMseRmseMaeR2
0.00731.0150.00440.00440.06600.04900.1516
0.00642.0300.00420.00420.06470.05110.1826
0.00563.0450.00460.00460.06810.04970.0951
0.00414.0600.00370.00370.06110.04520.2723
0.00435.0750.00390.00390.06250.04600.2390
0.00346.0900.00350.00350.05920.04490.3155
0.00317.01050.00360.00360.05970.04760.3040
0.0038.01200.00350.00350.05880.04700.3255
0.00299.01350.00380.00380.06170.04520.2582
0.002310.01500.00370.00370.06090.04690.2767
0.002311.01650.00350.00350.05930.04440.3135
0.002112.01800.00400.00400.06330.04670.2179
0.002413.01950.00340.00340.05850.04490.3327
0.002414.02100.00330.00330.05720.04340.3620
0.00215.02250.00320.00320.05680.04210.3701
0.001916.02400.00340.00340.05810.04260.3425
0.00217.02550.00350.00350.05940.04390.3123
0.001618.02700.00330.00330.05730.04260.3609
0.001819.02850.00330.00330.05730.04240.3603
0.001720.03000.00320.00320.05700.04230.3674

Framework versions

  • —Transformers 4.38.2
  • —Pytorch 2.2.1+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2