my_T5_summarization_model

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

  • Loss: 1.9477
  • Rouge1: 0.2277
  • Rouge2: 0.1286
  • Rougel: 0.1988
  • Rougelsum: 0.1988
  • 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: 16
  • eval_batch_size: 16
  • seed: 42
  • 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
2.156 1.0 5348 2.0181 0.2264 0.1267 0.1971 0.1972 19.0
2.1095 2.0 10696 1.9737 0.227 0.1276 0.1977 0.1978 19.0
2.0867 3.0 16044 1.9545 0.2277 0.1285 0.1987 0.1988 19.0
2.0577 4.0 21392 1.9477 0.2277 0.1286 0.1988 0.1988 19.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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Dataset used to train dmen24/my_T5_summarization_model

Evaluation results