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language-detection-fine-tuned-on-xlm-roberta-base

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

  • Loss: 0.1642
  • Accuracy: 0.9760

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: 3e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0725 1.0 22194 0.1642 0.9760

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Dataset used to train jerryKakooza/language-detection-fine-tuned-on-xlm-roberta-base

Evaluation results