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Synopsis_summarization_t5

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

  • Loss: 2.5656
  • Rouge1: 0.131
  • Rouge2: 0.0393
  • Rougel: 0.1193
  • Rougelsum: 0.12
  • 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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 10 2.9436 0.0943 0.0169 0.0838 0.0838 19.0
2.9817 2.0 20 2.8118 0.1009 0.0192 0.0894 0.0897 19.0
2.9817 3.0 30 2.7272 0.1062 0.0214 0.0934 0.0938 19.0
2.8136 4.0 40 2.6788 0.1086 0.0216 0.0962 0.0967 19.0
2.8136 5.0 50 2.6475 0.1107 0.0243 0.0961 0.0971 19.0
2.697 6.0 60 2.6258 0.1258 0.0312 0.1123 0.1132 19.0
2.697 7.0 70 2.6174 0.1245 0.0325 0.1108 0.1114 19.0
2.6577 8.0 80 2.6132 0.1314 0.037 0.1193 0.1198 19.0
2.6577 9.0 90 2.6049 0.128 0.0371 0.1173 0.1185 19.0
2.6347 10.0 100 2.5951 0.1294 0.0383 0.1195 0.1205 19.0
2.6347 11.0 110 2.5872 0.1294 0.0383 0.1195 0.1205 19.0
2.6063 12.0 120 2.5808 0.1296 0.0383 0.1195 0.1204 19.0
2.6063 13.0 130 2.5776 0.1296 0.0383 0.1195 0.1204 19.0
2.5979 14.0 140 2.5755 0.1302 0.0371 0.1186 0.1195 19.0
2.5979 15.0 150 2.5733 0.1302 0.0371 0.1186 0.1195 19.0
2.5841 16.0 160 2.5703 0.131 0.0393 0.1193 0.12 19.0
2.5841 17.0 170 2.5680 0.131 0.0393 0.1193 0.12 19.0
2.5672 18.0 180 2.5669 0.131 0.0393 0.1193 0.12 19.0
2.5672 19.0 190 2.5658 0.131 0.0393 0.1193 0.12 19.0
2.5716 20.0 200 2.5656 0.131 0.0393 0.1193 0.12 19.0

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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