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t5-small-finetuned-xsum-updated

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

  • Loss: 2.0767
  • Rouge1: 33.2945
  • Rouge2: 12.0165
  • Rougel: 26.9804
  • Rougelsum: 26.9729
  • Gen Len: 18.7853

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: 0.0001
  • 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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.5219 1.0 12753 2.3054 30.4745 9.435 24.263 24.2522 18.823
2.4191 2.0 25506 2.2385 31.2305 10.0552 24.9345 24.9254 18.7562
2.3564 3.0 38259 2.1961 31.8234 10.6556 25.6109 25.6023 18.7708
2.3028 4.0 51012 2.1692 32.2053 11.0513 26.0184 26.0056 18.772
2.2737 5.0 63765 2.1452 32.3716 11.1779 26.1423 26.1363 18.7731
2.2432 6.0 76518 2.1304 32.5413 11.2517 26.2119 26.2098 18.8007
2.2266 7.0 89271 2.1193 32.8983 11.5683 26.5995 26.5958 18.8108
2.1863 8.0 102024 2.1058 32.9046 11.6564 26.6466 26.6473 18.8008
2.1583 9.0 114777 2.0987 32.9622 11.7285 26.7161 26.7116 18.7798
2.1653 10.0 127530 2.0900 33.1259 11.8525 26.8461 26.8419 18.7999
2.1403 11.0 140283 2.0880 33.0949 11.8135 26.7863 26.7765 18.7629
2.1212 12.0 153036 2.0825 33.1671 11.8939 26.9072 26.8982 18.7825
2.1021 13.0 165789 2.0793 33.1375 11.9119 26.8466 26.8386 18.8076
2.0877 14.0 178542 2.0774 33.2516 11.9574 26.9391 26.9327 18.7989
2.0984 15.0 191295 2.0767 33.2945 12.0165 26.9804 26.9729 18.7853

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Dataset used to train mdaffarudiyanto/t5-small-finetuned-xsum-updated

Evaluation results