Edit model card

bert-large-cased-sigir-LR10-1-prepend-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: 0.8946

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: 4e-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
3.8237 1.0 1 2.8391
3.6537 2.0 2 3.8003
1.9566 3.0 3 2.6997
1.0962 4.0 4 2.4019
2.7754 5.0 5 1.0750
2.2666 6.0 6 3.7118
1.33 7.0 7 2.3186
2.1846 8.0 8 2.0246
2.5284 9.0 9 2.0090
1.9864 10.0 10 3.3644
1.8111 11.0 11 2.5410
1.6821 12.0 12 1.2586
1.491 13.0 13 1.4496
1.9611 14.0 14 1.7305
1.4182 15.0 15 1.7722
2.0556 16.0 16 1.2964
0.9024 17.0 17 2.0762
1.5746 18.0 18 2.7421
1.2275 19.0 19 2.1911
1.6938 20.0 20 3.0756

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
Downloads last month
1
Inference API
Examples
Mask token: [MASK]
This model can be loaded on Inference API (serverless).