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longt5_xl_sfd_memsum_40

This model is a fine-tuned version of google/long-t5-tglobal-xl on the learn3r/summ_screen_memsum_oracle dataset. It achieves the following results on the evaluation set:

  • Loss: 5.2679

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • num_epochs: 40.0

Training results

Training Loss Epoch Step Validation Loss
2.5238 0.97 28 2.3147
2.1298 1.98 57 2.2837
1.7525 2.99 86 2.3335
1.2954 4.0 115 2.4995
1.0518 4.97 143 2.8326
0.7083 5.98 172 2.9095
0.5124 6.99 201 3.4108
0.4503 8.0 230 3.4459
0.3145 8.97 258 3.5216
0.2573 9.98 287 4.0127
0.213 10.99 316 3.9714
0.1682 12.0 345 3.8427
0.1396 12.97 373 4.2025
0.1363 13.98 402 4.4012
0.1148 14.99 431 4.7174
0.0907 16.0 460 4.4980
0.0942 16.97 488 4.7024
0.0765 17.98 517 4.3482
0.0799 18.99 546 4.5386
0.073 20.0 575 4.5889
0.0825 20.97 603 4.6817
0.0616 21.98 632 5.0263
0.0677 22.99 661 4.5804
0.0571 24.0 690 4.8399
0.0525 24.97 718 4.9350
0.081 25.98 747 4.6903
0.0505 26.99 776 5.0005
0.0576 28.0 805 5.0196
0.0448 28.97 833 5.1100
0.0457 29.98 862 5.0008
0.0442 30.99 891 5.5093
0.0391 32.0 920 5.4296
0.0392 32.97 948 5.2357
0.0376 33.98 977 5.2266
0.0381 34.99 1006 5.2630
0.0339 36.0 1035 5.3532
0.0377 36.97 1063 5.4443
0.0336 37.98 1092 5.0809
0.0316 38.96 1120 5.2679

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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