model

This model is a fine-tuned version of xlm-roberta-base on the Europarl language detection dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0237
  • Accuracy: 0.9967
  • F1: 0.9967

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 256
  • eval_batch_size: 512
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 821 0.0270 0.9965 0.9965
0.2372 2.0 1642 0.0237 0.9967 0.9967

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3
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Dataset used to train simoneteglia/xlm-roberta-europarl-language-detection

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