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distilbert-base-uncased-finetuned-natural-questions

This model is a fine-tuned version of distilbert-base-uncased on the natural_questions dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6267

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss
2.0532 1.0 5104 0.2393
1.8912 2.0 10208 0.2284
1.7854 3.0 15312 0.2357
1.6856 4.0 20416 0.2487
1.5918 5.0 25520 0.2743
1.5067 6.0 30624 0.2586
1.4323 7.0 35728 0.2763
1.365 8.0 40832 0.2753
1.3162 9.0 45936 0.3200
1.281 10.0 51040 0.3127
1.308 11.0 57104 0.2947
1.241 12.0 62208 0.2941
1.1391 13.0 67312 0.3103
1.0334 14.0 72416 0.3694
0.9538 15.0 77520 0.3658
0.8749 16.0 82624 0.4009
0.8154 17.0 87728 0.3672
0.7533 18.0 92832 0.3675
0.7079 19.0 97936 0.4611
0.6658 20.0 103040 0.4222
0.595 21.0 108144 0.4095
0.5765 22.0 113248 0.4400
0.5259 23.0 118352 0.5109
0.4804 24.0 123456 0.4711
0.4389 25.0 128560 0.5072
0.4034 26.0 133664 0.5363
0.374 27.0 138768 0.5460
0.3434 28.0 143872 0.5627
0.3181 29.0 148976 0.5657
0.2971 30.0 154080 0.5819
0.275 31.0 159184 0.5649
0.2564 32.0 164288 0.6087
0.2431 33.0 169392 0.6137
0.2289 34.0 174496 0.6123
0.2151 35.0 179600 0.5979
0.2041 36.0 184704 0.6196
0.1922 37.0 189808 0.6191
0.1852 38.0 194912 0.6313
0.1718 39.0 200016 0.6234
0.1718 39.81 204160 0.6267

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0
  • Datasets 1.18.4
  • Tokenizers 0.11.6
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Dataset used to train datarpit/distilbert-base-uncased-finetuned-natural-questions