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XLM_RoBERTa-Offensive-Language-Detection-8-langs-new

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

  • Loss: 0.8276
  • Micro F1: 0.8721
  • Macro F1: 0.8604
  • Accuracy: 0.8721

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Framework versions

  • Transformers 4.36.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.13.1
  • Tokenizers 0.15.0
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