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bert-covid-17

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metadata
license: mit
base_model: hung200504/bert-squadv2
tags:
  - generated_from_trainer
model-index:
  - name: bert-covid-17
    results: []

bert-covid-17

This model is a fine-tuned version of hung200504/bert-squadv2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7620

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
4.8507 0.01 5 1.7050
2.5037 0.03 10 1.1213
0.0842 0.04 15 1.4939
2.8332 0.06 20 1.4768
1.2692 0.07 25 1.2021
0.2025 0.08 30 1.1680
2.51 0.1 35 1.2461
1.1259 0.11 40 1.1270
1.0897 0.13 45 1.0785
1.3906 0.14 50 1.1147
0.927 0.15 55 1.1139
0.3758 0.17 60 1.3199
1.1277 0.18 65 1.3911
1.0594 0.2 70 1.3420
1.2825 0.21 75 1.2110
0.808 0.23 80 1.1443
1.5312 0.24 85 0.9526
2.018 0.25 90 0.9191
1.5825 0.27 95 1.3486
1.1372 0.28 100 0.9432
1.7199 0.3 105 0.8875
1.6011 0.31 110 0.9181
1.2766 0.32 115 0.8318
1.1237 0.34 120 0.8442
0.5508 0.35 125 0.9121
1.4098 0.37 130 0.9341
0.6475 0.38 135 1.0059
0.935 0.39 140 1.0911
0.9492 0.41 145 1.0617
1.0106 0.42 150 0.8882
0.8134 0.44 155 0.8288
0.58 0.45 160 0.8277
0.9716 0.46 165 0.8748
1.7163 0.48 170 0.9919
1.5798 0.49 175 0.8783
0.4907 0.51 180 0.8564
0.5704 0.52 185 1.1316
0.6746 0.54 190 1.2307
1.3695 0.55 195 1.0486
0.4738 0.56 200 0.9003
1.4755 0.58 205 0.8812
2.2741 0.59 210 0.8017
1.2088 0.61 215 0.7571
0.7497 0.62 220 0.7528
1.2208 0.63 225 0.7363
0.9775 0.65 230 0.7547
1.0131 0.66 235 0.7881
0.5256 0.68 240 0.8114
0.9784 0.69 245 0.8149
1.512 0.7 250 0.7748
0.0092 0.72 255 0.8031
0.4212 0.73 260 0.8552
1.401 0.75 265 0.8860
1.9551 0.76 270 0.8160
1.2076 0.77 275 0.7408
0.348 0.79 280 0.7252
0.6292 0.8 285 0.7186
0.8604 0.82 290 0.7170
0.8213 0.83 295 0.7139
0.5231 0.85 300 0.7190
0.7271 0.86 305 0.7393
0.3221 0.87 310 0.7759
1.0033 0.89 315 0.8094
0.1807 0.9 320 0.8364
1.9334 0.92 325 0.8349
1.2876 0.93 330 0.8080
0.8867 0.94 335 0.7826
0.6698 0.96 340 0.7800
1.2023 0.97 345 0.7761
1.4764 0.99 350 0.7647
0.3514 1.0 355 0.7620

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1