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xlm-roberta-large-xnli-finetuned-mnli-SJP

This model is a fine-tuned version of joeddav/xlm-roberta-large-xnli on the swiss_judgment_prediction dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3456
  • Accuracy: 0.7957

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: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 5 1.8460 0.7956
No log 2.0 10 1.3456 0.7957
No log 3.0 15 1.2799 0.7957
No log 4.0 20 1.2866 0.7957
No log 5.0 25 1.3162 0.7956

Framework versions

  • Transformers 4.20.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train tuni/xlm-roberta-large-xnli-finetuned-mnli-SJP

Evaluation results