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predict-perception-bertino-cause-object

This model is a fine-tuned version of indigo-ai/BERTino on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0766
  • R2: 0.8216

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: 0.0001
  • 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: 47

Training results

Training Loss Epoch Step Validation Loss R2
0.6807 1.0 14 0.4011 0.0652
0.3529 2.0 28 0.2304 0.4631
0.1539 3.0 42 0.0596 0.8611
0.0853 4.0 56 0.1600 0.6272
0.066 5.0 70 0.1596 0.6280
0.0563 6.0 84 0.1146 0.7330
0.0777 7.0 98 0.1010 0.7646
0.0299 8.0 112 0.0897 0.7910
0.0311 9.0 126 0.0832 0.8061
0.0274 10.0 140 0.0988 0.7697
0.0262 11.0 154 0.1048 0.7557
0.0204 12.0 168 0.0615 0.8566
0.0254 13.0 182 0.0742 0.8270
0.0251 14.0 196 0.0923 0.7850
0.0149 15.0 210 0.0663 0.8456
0.0141 16.0 224 0.0755 0.8241
0.0112 17.0 238 0.0905 0.7891
0.0108 18.0 252 0.0834 0.8057
0.0096 19.0 266 0.0823 0.8082
0.0073 20.0 280 0.0825 0.8078
0.0092 21.0 294 0.0869 0.7974
0.0075 22.0 308 0.0744 0.8266
0.0075 23.0 322 0.0825 0.8078
0.0062 24.0 336 0.0797 0.8144
0.0065 25.0 350 0.0793 0.8152
0.007 26.0 364 0.0840 0.8043
0.0067 27.0 378 0.0964 0.7753
0.0064 28.0 392 0.0869 0.7976
0.0063 29.0 406 0.0766 0.8215
0.0057 30.0 420 0.0764 0.8219
0.0057 31.0 434 0.0796 0.8145
0.0054 32.0 448 0.0853 0.8012
0.0044 33.0 462 0.0750 0.8253
0.0072 34.0 476 0.0782 0.8179
0.006 35.0 490 0.0867 0.7979
0.0054 36.0 504 0.0819 0.8092
0.0047 37.0 518 0.0839 0.8045
0.0043 38.0 532 0.0764 0.8221
0.0039 39.0 546 0.0728 0.8303
0.0041 40.0 560 0.0755 0.8241
0.0038 41.0 574 0.0729 0.8301
0.0034 42.0 588 0.0781 0.8180
0.0038 43.0 602 0.0762 0.8224
0.0032 44.0 616 0.0777 0.8189
0.0035 45.0 630 0.0776 0.8191
0.0037 46.0 644 0.0765 0.8217
0.0036 47.0 658 0.0766 0.8216

Framework versions

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