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distilroberta-base-rb156k

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

  • Loss: 1.2509

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: 7.2115e-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
  • lr_scheduler_warmup_ratio: 0.12
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.779 1.0 8994 1.6188
1.6848 2.0 17988 1.5515
1.6376 3.0 26982 1.5219
1.6208 4.0 35976 1.5021
1.6025 5.0 44970 1.4949
1.5731 6.0 53964 1.4753
1.5512 7.0 62958 1.4579
1.5305 8.0 71952 1.4457
1.5159 9.0 80946 1.4308
1.4967 10.0 89940 1.4212
1.4761 11.0 98934 1.4081
1.4607 12.0 107928 1.3979
1.4512 13.0 116922 1.3896
1.4394 14.0 125916 1.3816
1.431 15.0 134910 1.3755
1.4226 16.0 143904 1.3639
1.4032 17.0 152898 1.3608
1.3992 18.0 161892 1.3544
1.3909 19.0 170886 1.3446
1.3809 20.0 179880 1.3428
1.3701 21.0 188874 1.3320
1.3574 22.0 197868 1.3276
1.3586 23.0 206862 1.3216
1.3521 24.0 215856 1.3180
1.3371 25.0 224850 1.3134
1.3334 26.0 233844 1.3083
1.3261 27.0 242838 1.3042
1.316 28.0 251832 1.2971
1.3061 29.0 260826 1.2931
1.3057 30.0 269820 1.2903
1.2997 31.0 278814 1.2802
1.288 32.0 287808 1.2784
1.2876 33.0 296802 1.2737
1.2778 34.0 305796 1.2703
1.2695 35.0 314790 1.2636
1.268 36.0 323784 1.2597
1.2606 37.0 332778 1.2583
1.254 38.0 341772 1.2547
1.2516 39.0 350766 1.2491
1.2506 40.0 359760 1.2501

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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