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bert-large-cased-sigir-LR100-0-cased-20

This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5289

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: 30
  • eval_batch_size: 30
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
7.0635 1.0 1 6.6184
7.131 2.0 2 7.0072
7.0969 3.0 3 5.8833
6.087 4.0 4 5.2094
5.8314 5.0 5 5.3317
5.1807 6.0 6 5.0294
5.0853 7.0 7 4.3234
4.5785 8.0 8 4.0070
4.0047 9.0 9 3.5287
3.5236 10.0 10 4.0761
4.2192 11.0 11 3.2353
3.6715 12.0 12 3.6203
3.4242 13.0 13 2.7801
3.1152 14.0 14 3.6127
2.9266 15.0 15 2.2571
3.4507 16.0 16 2.8120
3.0439 17.0 17 3.1393
2.6443 18.0 18 3.4350
2.8907 19.0 19 1.0329
2.8591 20.0 20 2.0586

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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