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Mohamedd123321
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Tokenization-large

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xlm-roberta
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Tokenization-large

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: 0.7947

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.1853 1.0 14289 0.9966
0.9826 2.0 28578 0.8565
0.8465 3.0 42867 0.7947

Framework versions

  • Transformers 4.56.0
  • Pytorch 2.8.0+cu129
  • Datasets 5.0.0
  • Tokenizers 0.22.0
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