classification-hate-speech-DE-14-twit

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

  • Loss: 3.0647
  • F1 macro: 0.4076
  • Weighted: 0.5816
  • Balanced accuracy: 0.5560

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 14

Training results

Training Loss Epoch Step Validation Loss F1 macro Weighted Balanced accuracy
1.2717 1.0 152 1.1413 0.3986 0.6607 0.4780
0.7363 2.0 304 1.2159 0.3829 0.6075 0.4706
0.2523 3.0 456 1.4802 0.3994 0.6380 0.4901
0.1209 4.0 608 1.9894 0.4200 0.6130 0.5900
0.0201 5.0 760 2.7075 0.3731 0.5537 0.5221
0.0052 6.0 912 2.4151 0.4301 0.6211 0.5905
0.0012 7.0 1064 3.2430 0.3791 0.5228 0.5470
0.0014 8.0 1216 2.7395 0.4054 0.6010 0.5485
0.001 9.0 1368 2.6392 0.4167 0.6052 0.5505
0.0005 10.0 1520 2.8755 0.4049 0.5893 0.5546
0.0005 11.0 1672 2.7610 0.4152 0.6027 0.5560
0.0009 12.0 1824 3.0945 0.4011 0.5710 0.5511
0.0003 13.0 1976 3.1262 0.4003 0.5687 0.5506
0.0004 14.0 2128 3.0647 0.4076 0.5816 0.5560

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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