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metadata
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-xsum
    results: []

t5-small-finetuned-xsum

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

  • Loss: 2.4256
  • Rouge1: 19.6262
  • Rouge2: 3.6874
  • Rougel: 17.4155
  • Rougelsum: 17.5472
  • 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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.8869 1.0 584 2.6152 17.1618 2.621 15.8121 15.8907 19.0
2.829 2.0 1168 2.5615 17.486 2.799 15.9032 15.9821 19.0
2.7721 3.0 1752 2.5222 18.2742 3.0877 16.5789 16.6729 19.0
2.7416 4.0 2336 2.4921 18.8283 3.362 16.858 16.9738 19.0
2.7063 5.0 2920 2.4690 18.6113 3.2539 16.6872 16.7919 19.0
2.6686 6.0 3504 2.4528 19.2086 3.5071 17.1746 17.2843 19.0
2.652 7.0 4088 2.4403 19.3553 3.5814 17.1871 17.2981 19.0
2.6338 8.0 4672 2.4319 19.6779 3.6693 17.4134 17.529 19.0
2.6377 9.0 5256 2.4270 19.6024 3.6557 17.3604 17.4862 19.0
2.6281 10.0 5840 2.4256 19.6262 3.6874 17.4155 17.5472 19.0

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu118
  • Datasets 2.17.0
  • Tokenizers 0.15.1