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MTL-bert-base-uncased

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

  • Loss: 1.9283

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
2.4409 1.0 99 2.1982
2.2905 2.0 198 2.1643
2.1974 3.0 297 2.1168
2.15 4.0 396 2.0023
2.0823 5.0 495 2.0199
2.0752 6.0 594 1.9061
2.0408 7.0 693 1.9770
1.9984 8.0 792 1.9322
1.9933 9.0 891 1.9167
1.9806 10.0 990 1.9652
1.9436 11.0 1089 1.9308
1.9491 12.0 1188 1.9064
1.929 13.0 1287 1.8831
1.9096 14.0 1386 1.8927
1.9032 15.0 1485 1.9117

Framework versions

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