bert-30 / README.md
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metadata
license: cc-by-4.0
base_model: deepset/bert-base-cased-squad2
tags:
  - generated_from_trainer
model-index:
  - name: bert-30
    results: []

bert-30

This model is a fine-tuned version of deepset/bert-base-cased-squad2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 10.2691

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss
11.3132 0.09 5 12.3055
11.4109 0.18 10 12.2292
10.9744 0.27 15 12.1547
11.0771 0.36 20 12.0814
11.0342 0.45 25 12.0101
11.0327 0.55 30 11.9396
10.2954 0.64 35 11.8706
10.8979 0.73 40 11.8043
10.432 0.82 45 11.7386
10.3023 0.91 50 11.6747
10.0494 1.0 55 11.6128
10.2273 1.09 60 11.5521
10.3139 1.18 65 11.4931
10.5075 1.27 70 11.4349
10.0234 1.36 75 11.3790
10.4276 1.45 80 11.3238
10.1397 1.55 85 11.2699
10.0675 1.64 90 11.2174
9.8835 1.73 95 11.1665
10.0738 1.82 100 11.1169
9.6112 1.91 105 11.0687
9.9186 2.0 110 11.0227
9.8411 2.09 115 10.9779
9.6506 2.18 120 10.9342
9.7831 2.27 125 10.8916
9.8835 2.36 130 10.8509
9.4752 2.45 135 10.8111
9.8176 2.55 140 10.7731
9.3628 2.64 145 10.7369
9.819 2.73 150 10.7017
9.572 2.82 155 10.6681
9.522 2.91 160 10.6356
9.6874 3.0 165 10.6046
9.6037 3.09 170 10.5750
9.5624 3.18 175 10.5468
9.2702 3.27 180 10.5202
9.1347 3.36 185 10.4947
9.8154 3.45 190 10.4706
9.4045 3.55 195 10.4475
9.2453 3.64 200 10.4262
9.1087 3.73 205 10.4062
8.985 3.82 210 10.3875
9.0054 3.91 215 10.3705
9.4764 4.0 220 10.3545
9.13 4.09 225 10.3401
9.4397 4.18 230 10.3272
9.0841 4.27 235 10.3153
9.5885 4.36 240 10.3048
9.4137 4.45 245 10.2958
9.1068 4.55 250 10.2878
9.1388 4.64 255 10.2816
8.8014 4.73 260 10.2763
8.9782 4.82 265 10.2727
9.222 4.91 270 10.2701
9.292 5.0 275 10.2691

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1