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token

This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • eval_loss: 3.8536
  • eval_runtime: 1.2985
  • eval_samples_per_second: 471.307
  • eval_steps_per_second: 6.931
  • epoch: 1.9028
  • step: 16600

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: 70
  • eval_batch_size: 70
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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