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t5-base-finetuned-samsum-v2

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

  • Loss: 1.4881
  • Rouge1: 44.5129
  • Rouge2: 20.9037
  • Rougel: 37.3032
  • Rougelsum: 41.2293
  • Gen Len: 16.7482

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.6551 1.0 1841 1.4881 44.5129 20.9037 37.3032 41.2293 16.7482

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train amagzari/t5-base-finetuned-samsum-v2

Evaluation results