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MTL-distilbert-base-uncased

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

  • Loss: 2.0874

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: 7
  • eval_batch_size: 7
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.5593 1.0 99 2.3163
2.4346 2.0 198 2.2918
2.3377 3.0 297 2.2345
2.2953 4.0 396 2.1463
2.2296 5.0 495 2.1761
2.2235 6.0 594 2.0721
2.1878 7.0 693 2.1460
2.1569 8.0 792 2.0856
2.1455 9.0 891 2.1039
2.1391 10.0 990 2.1112
2.1056 11.0 1089 2.0694
2.1076 12.0 1188 2.0501
2.0919 13.0 1287 2.0484
2.0669 14.0 1386 2.0342
2.0595 15.0 1485 2.0802

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Evaluation results