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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased__hate_speech_offensive__train-8-5
    results: []

distilbert-base-uncased__hate_speech_offensive__train-8-5

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

  • Loss: 1.7214
  • Accuracy: 0.37

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0995 1.0 5 1.1301 0.0
1.0227 2.0 10 1.1727 0.0
1.0337 3.0 15 1.1734 0.2
0.9137 4.0 20 1.1829 0.2
0.8065 5.0 25 1.1496 0.4
0.7038 6.0 30 1.1101 0.4
0.6246 7.0 35 1.0982 0.2
0.4481 8.0 40 1.0913 0.2
0.3696 9.0 45 1.0585 0.4
0.3137 10.0 50 1.0418 0.4
0.2482 11.0 55 1.0078 0.4
0.196 12.0 60 0.9887 0.6
0.1344 13.0 65 0.9719 0.6
0.1014 14.0 70 1.0053 0.6
0.111 15.0 75 0.9653 0.6
0.0643 16.0 80 0.9018 0.6
0.0559 17.0 85 0.9393 0.6
0.0412 18.0 90 1.0210 0.6
0.0465 19.0 95 0.9965 0.6
0.0328 20.0 100 0.9739 0.6
0.0289 21.0 105 0.9796 0.6
0.0271 22.0 110 0.9968 0.6
0.0239 23.0 115 1.0143 0.6
0.0201 24.0 120 1.0459 0.6
0.0185 25.0 125 1.0698 0.6
0.0183 26.0 130 1.0970 0.6

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2
  • Tokenizers 0.10.3