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xnli_m_bert_only_sw

This model is a fine-tuned version of bert-base-multilingual-cased on the xnli dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5193
  • Accuracy: 0.6289

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: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8323 1.0 3068 0.8640 0.6217
0.7614 2.0 6136 0.7812 0.6598
0.6875 3.0 9204 0.8466 0.6394
0.6065 4.0 12272 0.8354 0.6538
0.5219 5.0 15340 0.8810 0.6550
0.4317 6.0 18408 0.9880 0.6554
0.3532 7.0 21476 1.1403 0.6390
0.2893 8.0 24544 1.1935 0.6390
0.2351 9.0 27612 1.3805 0.6390
0.1928 10.0 30680 1.5193 0.6289

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.13.0
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train semindan/xnli_m_bert_only_sw

Evaluation results