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roberta-petco-filtered_annotated-ctr

This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0023
  • Mse: 0.0023
  • Rmse: 0.0477
  • Mae: 0.0361
  • R2: 0.4149
  • Accuracy: 0.75

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: 2e-05
  • train_batch_size: 10
  • eval_batch_size: 10
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Mse Rmse Mae R2 Accuracy
0.0137 1.0 24 0.0049 0.0049 0.0702 0.0533 -0.2657 0.55
0.0079 2.0 48 0.0042 0.0042 0.0647 0.0533 -0.0751 0.5
0.0074 3.0 72 0.0026 0.0026 0.0505 0.0388 0.3441 0.6833
0.006 4.0 96 0.0041 0.0041 0.0638 0.0544 -0.0467 0.5167
0.0061 5.0 120 0.0027 0.0027 0.0519 0.0409 0.3082 0.7
0.0054 6.0 144 0.0025 0.0025 0.0503 0.0399 0.3498 0.7
0.0052 7.0 168 0.0038 0.0038 0.0615 0.0469 0.0298 0.5833
0.0074 8.0 192 0.0027 0.0027 0.0522 0.0412 0.3000 0.65
0.0049 9.0 216 0.0028 0.0028 0.0530 0.0392 0.2781 0.7333
0.0052 10.0 240 0.0028 0.0028 0.0526 0.0401 0.2885 0.7
0.0035 11.0 264 0.0033 0.0033 0.0572 0.0438 0.1587 0.7
0.0039 12.0 288 0.0034 0.0034 0.0581 0.0455 0.1340 0.65
0.0031 13.0 312 0.0026 0.0026 0.0512 0.0375 0.3267 0.75
0.0043 14.0 336 0.0023 0.0023 0.0477 0.0361 0.4149 0.75
0.0044 15.0 360 0.0027 0.0027 0.0524 0.0397 0.2944 0.7333
0.0033 16.0 384 0.0024 0.0024 0.0485 0.0356 0.3948 0.7833
0.0031 17.0 408 0.0033 0.0033 0.0575 0.0437 0.1517 0.6667
0.0033 18.0 432 0.0026 0.0026 0.0508 0.0373 0.3370 0.7667
0.0031 19.0 456 0.0033 0.0033 0.0571 0.0447 0.1624 0.6667
0.0035 20.0 480 0.0029 0.0029 0.0538 0.0410 0.2562 0.6667

Framework versions

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