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predict-perception-bert-cause-none

This model is a fine-tuned version of dbmdz/bert-base-italian-xxl-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6269
  • Rmse: 1.2763
  • Rmse Cause::a Spontanea, priva di un agente scatenante: 1.2763
  • Mae: 1.0431
  • Mae Cause::a Spontanea, priva di un agente scatenante: 1.0431
  • R2: -1.4329
  • R2 Cause::a Spontanea, priva di un agente scatenante: -1.4329
  • Cos: -0.3913
  • Pair: 0.0
  • Rank: 0.5
  • Neighbors: 0.3371
  • 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 Cause::a Spontanea, priva di un agente scatenante Mae Mae Cause::a Spontanea, priva di un agente scatenante R2 R2 Cause::a Spontanea, priva di un agente scatenante Cos Pair Rank Neighbors Rsa
0.994 1.0 15 0.7156 0.8465 0.8465 0.7809 0.7809 -0.0701 -0.0701 -0.1304 0.0 0.5 0.2971 nan
0.9757 2.0 30 0.7096 0.8429 0.8429 0.7666 0.7666 -0.0611 -0.0611 0.0435 0.0 0.5 0.2515 nan
1.0086 3.0 45 0.7779 0.8825 0.8825 0.7981 0.7981 -0.1632 -0.1632 -0.0435 0.0 0.5 0.2899 nan
0.9127 4.0 60 0.8158 0.9038 0.9038 0.8171 0.8171 -0.2199 -0.2199 -0.2174 0.0 0.5 0.2975 nan
0.8555 5.0 75 0.7691 0.8775 0.8775 0.8121 0.8121 -0.1501 -0.1501 -0.2174 0.0 0.5 0.3299 nan
0.8702 6.0 90 0.7818 0.8848 0.8848 0.7781 0.7781 -0.1691 -0.1691 0.0435 0.0 0.5 0.2515 nan
0.76 7.0 105 0.8377 0.9158 0.9158 0.7985 0.7985 -0.2526 -0.2526 0.0435 0.0 0.5 0.2515 nan
0.6997 8.0 120 0.9065 0.9527 0.9527 0.8370 0.8370 -0.3555 -0.3555 -0.2174 0.0 0.5 0.3147 nan
0.5963 9.0 135 1.0611 1.0308 1.0308 0.8396 0.8396 -0.5867 -0.5867 -0.0435 0.0 0.5 0.2645 nan
0.5413 10.0 150 1.1724 1.0835 1.0835 0.8649 0.8649 -0.7532 -0.7532 -0.0435 0.0 0.5 0.2645 nan
0.4994 11.0 165 1.1471 1.0717 1.0717 0.8857 0.8857 -0.7154 -0.7154 -0.2174 0.0 0.5 0.3271 nan
0.4208 12.0 180 1.2136 1.1024 1.1024 0.9392 0.9392 -0.8148 -0.8148 -0.2174 0.0 0.5 0.3169 nan
0.316 13.0 195 1.3499 1.1626 1.1626 0.9395 0.9395 -1.0187 -1.0187 -0.2174 0.0 0.5 0.3271 nan
0.2893 14.0 210 1.4229 1.1937 1.1937 0.9608 0.9608 -1.1278 -1.1278 -0.3043 0.0 0.5 0.3269 nan
0.235 15.0 225 1.4699 1.2132 1.2132 0.9785 0.9785 -1.1981 -1.1981 -0.0435 0.0 0.5 0.2865 nan
0.2397 16.0 240 1.5492 1.2455 1.2455 1.0005 1.0005 -1.3167 -1.3167 -0.0435 0.0 0.5 0.2655 nan
0.1973 17.0 255 1.5541 1.2474 1.2474 1.0165 1.0165 -1.3239 -1.3239 -0.0435 0.0 0.5 0.2655 nan
0.1793 18.0 270 1.4966 1.2242 1.2242 1.0058 1.0058 -1.2380 -1.2380 -0.3043 0.0 0.5 0.3437 nan
0.16 19.0 285 1.4977 1.2246 1.2246 1.0140 1.0140 -1.2396 -1.2396 -0.3913 0.0 0.5 0.3371 nan
0.1501 20.0 300 1.5751 1.2558 1.2558 1.0254 1.0254 -1.3553 -1.3553 -0.3913 0.0 0.5 0.3371 nan
0.1342 21.0 315 1.7011 1.3051 1.3051 1.0681 1.0681 -1.5438 -1.5438 -0.2174 0.0 0.5 0.2715 nan
0.137 22.0 330 1.5557 1.2481 1.2481 1.0393 1.0393 -1.3263 -1.3263 -0.3043 0.0 0.5 0.3437 nan
0.11 23.0 345 1.5475 1.2448 1.2448 1.0320 1.0320 -1.3141 -1.3141 -0.3913 0.0 0.5 0.3371 nan
0.1106 24.0 360 1.6006 1.2660 1.2660 1.0452 1.0452 -1.3936 -1.3936 -0.3913 0.0 0.5 0.3297 nan
0.1013 25.0 375 1.5907 1.2621 1.2621 1.0368 1.0368 -1.3787 -1.3787 -0.3043 0.0 0.5 0.2929 nan
0.0863 26.0 390 1.6436 1.2829 1.2829 1.0496 1.0496 -1.4578 -1.4578 -0.3043 0.0 0.5 0.2929 nan
0.0929 27.0 405 1.6000 1.2658 1.2658 1.0341 1.0341 -1.3927 -1.3927 -0.3043 0.0 0.5 0.3245 nan
0.0829 28.0 420 1.6277 1.2767 1.2767 1.0422 1.0422 -1.4341 -1.4341 -0.3913 0.0 0.5 0.3371 nan
0.0884 29.0 435 1.6324 1.2785 1.2785 1.0436 1.0436 -1.4411 -1.4411 -0.3913 0.0 0.5 0.3371 nan
0.0896 30.0 450 1.6269 1.2763 1.2763 1.0431 1.0431 -1.4329 -1.4329 -0.3913 0.0 0.5 0.3371 nan

Framework versions

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