bert-25 / README.md
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bert-cased
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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-25
    results: []

bert-25

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: 10.9150

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
11.2284 0.18 5 12.3262
10.9876 0.36 10 12.2748
11.1442 0.54 15 12.2245
10.9113 0.71 20 12.1755
10.8104 0.89 25 12.1267
10.6362 1.07 30 12.0793
10.8187 1.25 35 12.0330
10.7052 1.43 40 11.9875
10.6594 1.61 45 11.9432
10.6863 1.79 50 11.8997
10.7858 1.96 55 11.8569
10.626 2.14 60 11.8158
10.4246 2.32 65 11.7756
10.3939 2.5 70 11.7359
10.7641 2.68 75 11.6970
10.341 2.86 80 11.6597
10.3492 3.04 85 11.6228
10.797 3.21 90 11.5867
10.3496 3.39 95 11.5514
10.1967 3.57 100 11.5177
10.4702 3.75 105 11.4843
10.3715 3.93 110 11.4521
10.1039 4.11 115 11.4213
10.1126 4.29 120 11.3915
9.9939 4.46 125 11.3625
10.1773 4.64 130 11.3342
10.062 4.82 135 11.3068
10.2641 5.0 140 11.2806
10.2323 5.18 145 11.2554
10.037 5.36 150 11.2309
10.0938 5.54 155 11.2069
9.8816 5.71 160 11.1845
10.124 5.89 165 11.1625
9.873 6.07 170 11.1416
9.7348 6.25 175 11.1220
9.9028 6.43 180 11.1028
9.997 6.61 185 11.0846
9.9333 6.79 190 11.0676
9.9954 6.96 195 11.0511
10.311 7.14 200 11.0356
9.7617 7.32 205 11.0213
10.0068 7.5 210 11.0075
9.6182 7.68 215 10.9949
9.7642 7.86 220 10.9835
9.8524 8.04 225 10.9728
9.7615 8.21 230 10.9630
9.7559 8.39 235 10.9542
9.5819 8.57 240 10.9461
9.5843 8.75 245 10.9392
10.05 8.93 250 10.9331
10.0722 9.11 255 10.9276
9.665 9.29 260 10.9233
9.7631 9.46 265 10.9197
9.7963 9.64 270 10.9172
9.9692 9.82 275 10.9155
9.885 10.0 280 10.9150

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1