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MTL-bert-base-uncased-ww

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: 2.5261

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
3.2964 1.0 99 2.9560
3.0419 2.0 198 2.8336
2.8979 3.0 297 2.8009
2.8815 4.0 396 2.7394
2.8373 5.0 495 2.6813
2.741 6.0 594 2.6270
2.6877 7.0 693 2.5216
2.6823 8.0 792 2.5485
2.6326 9.0 891 2.5690
2.5976 10.0 990 2.6336
2.6009 11.0 1089 2.5919
2.5615 12.0 1188 2.4264
2.5826 13.0 1287 2.5562
2.5693 14.0 1386 2.5529
2.5494 15.0 1485 2.5300

Framework versions

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