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predict-perception-xlmr-blame-concept

Text Classification
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PyTorch
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xlm-roberta
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predict-perception-xlmr-blame-concept

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9414
  • Rmse: 0.7875
  • Rmse Blame::a Un concetto astratto o un'emozione: 0.7875
  • Mae: 0.6165
  • Mae Blame::a Un concetto astratto o un'emozione: 0.6165
  • R2: 0.2291
  • R2 Blame::a Un concetto astratto o un'emozione: 0.2291
  • Cos: 0.1304
  • Pair: 0.0
  • Rank: 0.5
  • Neighbors: 0.3509
  • Rsa: nan

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
  • train_batch_size: 20
  • eval_batch_size: 8
  • seed: 1996
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Rmse Rmse Blame::a Un concetto astratto o un'emozione Mae Mae Blame::a Un concetto astratto o un'emozione R2 R2 Blame::a Un concetto astratto o un'emozione Cos Pair Rank Neighbors Rsa
1.0549 1.0 15 1.2093 0.8925 0.8925 0.6659 0.6659 0.0097 0.0097 -0.3043 0.0 0.5 0.4013 nan
1.0085 2.0 30 1.2199 0.8964 0.8964 0.6494 0.6494 0.0010 0.0010 -0.1304 0.0 0.5 0.4515 nan
1.0131 3.0 45 1.1798 0.8815 0.8815 0.6412 0.6412 0.0339 0.0339 -0.2174 0.0 0.5 0.2402 nan
0.9931 4.0 60 1.1726 0.8788 0.8788 0.6370 0.6370 0.0397 0.0397 -0.1304 0.0 0.5 0.2911 nan
0.9668 5.0 75 1.1194 0.8587 0.8587 0.5925 0.5925 0.0833 0.0833 0.2174 0.0 0.5 0.3303 nan
0.8759 6.0 90 1.0776 0.8425 0.8425 0.6265 0.6265 0.1175 0.1175 0.3043 0.0 0.5 0.4190 nan
0.8787 7.0 105 1.0513 0.8321 0.8321 0.6087 0.6087 0.1391 0.1391 0.2174 0.0 0.5 0.3303 nan
0.7637 8.0 120 1.0537 0.8331 0.8331 0.6265 0.6265 0.1372 0.1372 0.2174 0.0 0.5 0.3303 nan
0.6568 9.0 135 0.9104 0.7744 0.7744 0.5887 0.5887 0.2544 0.2544 0.3043 0.0 0.5 0.3680 nan
0.6354 10.0 150 0.9055 0.7723 0.7723 0.6222 0.6222 0.2585 0.2585 0.1304 0.0 0.5 0.3987 nan
0.5107 11.0 165 1.0173 0.8186 0.8186 0.6168 0.6168 0.1669 0.1669 0.2174 0.0 0.5 0.3303 nan
0.4598 12.0 180 0.9155 0.7765 0.7765 0.6284 0.6284 0.2503 0.2503 0.1304 0.0 0.5 0.3987 nan
0.3815 13.0 195 0.9255 0.7808 0.7808 0.6140 0.6140 0.2421 0.2421 0.1304 0.0 0.5 0.3987 nan
0.3303 14.0 210 0.8506 0.7485 0.7485 0.6076 0.6076 0.3035 0.3035 0.0435 0.0 0.5 0.2862 nan
0.2799 15.0 225 1.0272 0.8226 0.8226 0.6699 0.6699 0.1588 0.1588 0.0435 0.0 0.5 0.2862 nan
0.2998 16.0 240 0.9969 0.8103 0.8103 0.6461 0.6461 0.1836 0.1836 0.0435 0.0 0.5 0.2862 nan
0.3131 17.0 255 0.9066 0.7727 0.7727 0.5849 0.5849 0.2576 0.2576 0.2174 0.0 0.5 0.3303 nan
0.2234 18.0 270 0.8741 0.7588 0.7588 0.5953 0.5953 0.2842 0.2842 0.2174 0.0 0.5 0.3303 nan
0.2481 19.0 285 1.0022 0.8125 0.8125 0.6549 0.6549 0.1793 0.1793 0.0435 0.0 0.5 0.2862 nan
0.2333 20.0 300 0.9238 0.7801 0.7801 0.6180 0.6180 0.2435 0.2435 0.0435 0.0 0.5 0.2862 nan
0.2407 21.0 315 0.9868 0.8062 0.8062 0.6457 0.6457 0.1919 0.1919 0.0435 0.0 0.5 0.2862 nan
0.2122 22.0 330 0.9514 0.7916 0.7916 0.6204 0.6204 0.2209 0.2209 0.0435 0.0 0.5 0.2862 nan
0.2162 23.0 345 0.9227 0.7796 0.7796 0.6053 0.6053 0.2444 0.2444 0.1304 0.0 0.5 0.3509 nan
0.1739 24.0 360 0.9147 0.7762 0.7762 0.5979 0.5979 0.2510 0.2510 0.1304 0.0 0.5 0.3509 nan
0.2084 25.0 375 0.9645 0.7970 0.7970 0.6296 0.6296 0.2102 0.2102 0.0435 0.0 0.5 0.2862 nan
0.1702 26.0 390 0.9587 0.7946 0.7946 0.6279 0.6279 0.2149 0.2149 0.0435 0.0 0.5 0.2862 nan
0.2146 27.0 405 0.9519 0.7918 0.7918 0.6273 0.6273 0.2205 0.2205 0.0435 0.0 0.5 0.2862 nan
0.1645 28.0 420 0.9398 0.7868 0.7868 0.6181 0.6181 0.2304 0.2304 0.0435 0.0 0.5 0.2862 nan
0.2052 29.0 435 0.9492 0.7907 0.7907 0.6228 0.6228 0.2227 0.2227 0.0435 0.0 0.5 0.2862 nan
0.147 30.0 450 0.9414 0.7875 0.7875 0.6165 0.6165 0.2291 0.2291 0.1304 0.0 0.5 0.3509 nan

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Evaluation results

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