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summary_cz_eurlex

This model is a fine-tuned version of t5-small on the eur-lex-sum dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8559
  • Rouge1: 0.0181
  • Rouge2: 0.0155
  • Rougel: 0.0181
  • Rougelsum: 0.0181
  • Gen Len: 19.0

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 8 6.7050 0.0181 0.0155 0.0181 0.0181 19.0
No log 2.0 16 3.3004 0.0181 0.0155 0.0181 0.0181 19.0
No log 3.0 24 2.9529 0.0181 0.0155 0.0181 0.0181 19.0
No log 4.0 32 2.8559 0.0181 0.0155 0.0181 0.0181 19.0

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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