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bert-base-uncased-issues-128

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: 1.2436

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: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss
2.1037 1.0 291 1.6976
1.6309 2.0 582 1.5133
1.4962 3.0 873 1.3515
1.3944 4.0 1164 1.3300
1.3308 5.0 1455 1.2333
1.2835 6.0 1746 1.3543
1.2308 7.0 2037 1.3045
1.2023 8.0 2328 1.3405
1.1662 9.0 2619 1.2236
1.1389 10.0 2910 1.1759
1.1279 11.0 3201 1.1468
1.1096 12.0 3492 1.1844
1.0896 13.0 3783 1.2305
1.0762 14.0 4074 1.2072
1.0721 15.0 4365 1.2287
1.0638 16.0 4656 1.2436

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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