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scenario-KD-SCR-MSV-CL-D2_data-cl-massive_all_1_155

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-cl-massive_all_1_1 on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Accuracy: 0.0315
  • F1: 0.0010

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 55
  • 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 Accuracy F1
0.0 0.56 5000 nan 0.0315 0.0010
0.0 1.11 10000 nan 0.0315 0.0010
0.0 1.67 15000 nan 0.0315 0.0010
0.0 2.22 20000 nan 0.0315 0.0010
0.0 2.78 25000 nan 0.0315 0.0010
0.0 3.33 30000 nan 0.0315 0.0010
0.0 3.89 35000 nan 0.0315 0.0010
0.0 4.45 40000 nan 0.0315 0.0010
0.0 5.0 45000 nan 0.0315 0.0010
0.0 5.56 50000 nan 0.0315 0.0010
0.0 6.11 55000 nan 0.0315 0.0010
0.0 6.67 60000 nan 0.0315 0.0010
0.0 7.23 65000 nan 0.0315 0.0010
0.0 7.78 70000 nan 0.0315 0.0010
0.0 8.34 75000 nan 0.0315 0.0010
0.0 8.89 80000 nan 0.0315 0.0010
0.0 9.45 85000 nan 0.0315 0.0010
0.0 10.0 90000 nan 0.0315 0.0010
0.0 10.56 95000 nan 0.0315 0.0010
0.0 11.12 100000 nan 0.0315 0.0010
0.0 11.67 105000 nan 0.0315 0.0010
0.0 12.23 110000 nan 0.0315 0.0010
0.0 12.78 115000 nan 0.0315 0.0010
0.0 13.34 120000 nan 0.0315 0.0010
0.0 13.9 125000 nan 0.0315 0.0010
0.0 14.45 130000 nan 0.0315 0.0010
0.0 15.01 135000 nan 0.0315 0.0010
0.0 15.56 140000 nan 0.0315 0.0010
0.0 16.12 145000 nan 0.0315 0.0010
0.0 16.67 150000 nan 0.0315 0.0010
0.0 17.23 155000 nan 0.0315 0.0010
0.0 17.79 160000 nan 0.0315 0.0010
0.0 18.34 165000 nan 0.0315 0.0010
0.0 18.9 170000 nan 0.0315 0.0010
0.0 19.45 175000 nan 0.0315 0.0010
0.0 20.01 180000 nan 0.0315 0.0010
0.0 20.56 185000 nan 0.0315 0.0010
0.0 21.12 190000 nan 0.0315 0.0010
0.0 21.68 195000 nan 0.0315 0.0010
0.0 22.23 200000 nan 0.0315 0.0010
0.0 22.79 205000 nan 0.0315 0.0010
0.0 23.34 210000 nan 0.0315 0.0010
0.0 23.9 215000 nan 0.0315 0.0010
0.0 24.46 220000 nan 0.0315 0.0010
0.0 25.01 225000 nan 0.0315 0.0010
0.0 25.57 230000 nan 0.0315 0.0010
0.0 26.12 235000 nan 0.0315 0.0010
0.0 26.68 240000 nan 0.0315 0.0010
0.0 27.23 245000 nan 0.0315 0.0010
0.0 27.79 250000 nan 0.0315 0.0010
0.0 28.35 255000 nan 0.0315 0.0010
0.0 28.9 260000 nan 0.0315 0.0010
0.0 29.46 265000 nan 0.0315 0.0010

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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