Finetuned / README.md
vppvgit's picture
Update README.md
39be53d
metadata
tags:
  - generated_from_trainer
datasets:
  - null
model-index:
  - name: BibliBERT
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask

BibliBERT

This model is a fine-tuned version of dbmdz/bert-base-italian-xxl-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7784

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: 8
  • eval_batch_size: 8
  • seed: 0
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss
1.5764 1.0 16528 1.5214
1.4572 2.0 33056 1.4201
1.3787 3.0 49584 1.3728
1.3451 4.0 66112 1.3245
1.3066 5.0 82640 1.2614
1.2447 6.0 99168 1.2333
1.2172 7.0 115696 1.2149
1.2079 8.0 132224 1.1853
1.2167 9.0 148752 1.1586
1.2056 10.0 165280 1.1503
1.1307 11.0 181808 1.1224
1.1689 12.0 198336 1.1074
1.1007 13.0 214864 1.0924
1.0901 14.0 231392 1.0659
1.0667 15.0 247920 1.0650
1.0434 16.0 264448 1.0362
1.0333 17.0 280976 1.0250
1.0342 18.0 297504 1.0198
1.0059 19.0 314032 0.9950
0.9719 20.0 330560 0.9836
0.9863 21.0 347088 0.9873
0.9781 22.0 363616 0.9724
0.9369 23.0 380144 0.9599
0.9578 24.0 396672 0.9557
0.9253 25.0 413200 0.9400
0.9441 26.0 429728 0.9222
0.9138 27.0 446256 0.9140
0.882 28.0 462784 0.9045
0.864 29.0 479312 0.8880
0.8632 30.0 495840 0.9023
0.8342 32.0 528896 0.8740
0.8037 34.0 561952 0.8647
0.8119 37.0 611536 0.8358
0.8011 38.0 628064 0.8252
0.786 39.0 644592 0.8228
0.7697 41.0 677648 0.8138
0.7485 42.0 694176 0.8104
0.7689 43.0 710704 0.8018
0.7401 45.0 743760 0.7957
0.7031 47.0 776816 0.7726
0.7578 48.0 793344 0.7864
0.7298 49.0 809872 0.7775
0.707 50.0 826400 0.7784

Framework versions

  • Transformers 4.10.3
  • Pytorch 1.9.0+cu102
  • Datasets 1.12.1
  • Tokenizers 0.10.3