fine_tuned_model_balanced_512_tokens_it

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

  • Loss: 0.7007
  • Accuracy: 0.7771

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 96 0.6889 0.6736
No log 2.0 192 0.7007 0.7771

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu118
  • Datasets 2.17.0
  • Tokenizers 0.15.1
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Dataset used to train mhmmterts/fine_tuned_model_balanced_512_tokens_it

Evaluation results