distilbert-base-uncased-finetuned-himani_auto-text-gen

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

  • Loss: 2.7913

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss
4.8212 1.0 30 2.9480
4.0493 2.0 60 1.9459
3.5449 3.0 90 3.1831
3.6318 4.0 120 4.5427
3.4761 5.0 150 4.6722
2.9815 6.0 180 5.4563
3.1247 7.0 210 3.6281
2.9715 8.0 240 4.5996
2.8263 9.0 270 3.7812
2.3001 10.0 300 4.1159
2.656 11.0 330 4.0686
2.5122 12.0 360 3.4073
1.8478 13.0 390 3.1591
2.5157 14.0 420 3.4517
2.0329 15.0 450 2.5513
2.2727 16.0 480 3.1985
1.591 17.0 510 2.7810
1.81 18.0 540 4.5671
2.0059 19.0 570 2.9868
1.8184 20.0 600 5.4829

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.2
  • Tokenizers 0.13.3
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