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Mohamedd123321
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Tokenization-large-last

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xlm-roberta
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Tokenization-large-last

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: 0.8002

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: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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
1.197 1.0 14289 1.0180
0.9916 2.0000 28577 0.8641
0.8583 3.0000 42866 0.8002

Framework versions

  • Transformers 4.56.0
  • Pytorch 2.8.0+cu129
  • Datasets 5.0.1
  • Tokenizers 0.22.0
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