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t5-conversation-summ

This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3003
  • Rouge1: 54.4662
  • Rouge2: 29.9033
  • Rougel: 44.7615
  • Rougelsum: 50.1037
  • Gen Len: 29.4487

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.2898 1.0 3683 0.3003 54.4662 29.9033 44.7615 50.1037 29.4487

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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Finetuned from

Dataset used to train mdizak/t5-conversation-summ-rust

Evaluation results