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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-intro-verizon
    results: []

distilbert-base-uncased-finetuned-intro-verizon

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: 0.0400
  • Accuracy: 1.0
  • F1: 1.0

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.3753 1.0 3 0.2877 1.0 1.0
0.278 2.0 6 0.2253 1.0 1.0
0.2366 3.0 9 0.1788 1.0 1.0
0.1721 4.0 12 0.1433 1.0 1.0
0.1531 5.0 15 0.1173 1.0 1.0
0.117 6.0 18 0.0980 1.0 1.0
0.108 7.0 21 0.0841 1.0 1.0
0.0916 8.0 24 0.0737 1.0 1.0
0.0843 9.0 27 0.0656 1.0 1.0
0.0701 10.0 30 0.0594 1.0 1.0
0.0683 11.0 33 0.0546 1.0 1.0
0.0599 12.0 36 0.0508 1.0 1.0
0.058 13.0 39 0.0478 1.0 1.0
0.0512 14.0 42 0.0454 1.0 1.0
0.0523 15.0 45 0.0437 1.0 1.0
0.0515 16.0 48 0.0423 1.0 1.0
0.0468 17.0 51 0.0413 1.0 1.0
0.0472 18.0 54 0.0406 1.0 1.0
0.0479 19.0 57 0.0401 1.0 1.0
0.0474 20.0 60 0.0400 1.0 1.0

Framework versions

  • Transformers 4.16.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2