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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: distilbert-finetuned-lr1e-05-epochs50
    results: []

distilbert-finetuned-lr1e-05-epochs50

This model is a fine-tuned version of distilbert-base-cased-distilled-squad on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 4.5477

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: 1e-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: 50

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 10 4.0110
No log 2.0 20 3.3394
No log 3.0 30 3.1992
No log 4.0 40 2.9902
No log 5.0 50 2.9628
No log 6.0 60 2.9346
No log 7.0 70 2.9844
No log 8.0 80 2.9660
No log 9.0 90 2.9239
No log 10.0 100 3.0764
No log 11.0 110 3.1964
No log 12.0 120 3.2409
No log 13.0 130 3.3191
No log 14.0 140 3.3747
No log 15.0 150 3.5559
No log 16.0 160 3.6678
No log 17.0 170 3.6692
No log 18.0 180 3.7116
No log 19.0 190 3.6768
No log 20.0 200 3.7929
No log 21.0 210 3.8766
No log 22.0 220 3.8967
No log 23.0 230 3.8982
No log 24.0 240 3.9140
No log 25.0 250 3.9563
No log 26.0 260 3.9702
No log 27.0 270 3.9615
No log 28.0 280 4.0481
No log 29.0 290 4.1172
No log 30.0 300 4.2297
No log 31.0 310 4.3585
No log 32.0 320 4.3186
No log 33.0 330 4.2844
No log 34.0 340 4.2662
No log 35.0 350 4.3037
No log 36.0 360 4.4106
No log 37.0 370 4.4208
No log 38.0 380 4.3877
No log 39.0 390 4.4133
No log 40.0 400 4.4798
No log 41.0 410 4.4925
No log 42.0 420 4.4595
No log 43.0 430 4.4402
No log 44.0 440 4.4379
No log 45.0 450 4.4711
No log 46.0 460 4.4953
No log 47.0 470 4.5282
No log 48.0 480 4.5400
No log 49.0 490 4.5472
0.4112 50.0 500 4.5477

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3