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mt5-small_test_35

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7383
  • Rouge1: 43.9482
  • Rouge2: 38.4156
  • Rougel: 42.6232
  • Rougelsum: 42.674
  • Bleu: 33.3469
  • Gen Len: 12.4725
  • Meteor: 0.4016
  • True negatives: 70.997
  • False negatives: 11.8271
  • Cosine Sim: 0.7532

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: 16
  • eval_batch_size: 16
  • seed: 9
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Bleu Gen Len Meteor True negatives False negatives Cosine Sim
2.4524 1.0 175 0.9783 17.6419 14.587 17.1176 17.1329 6.1296 7.3271 0.1531 75.7704 59.8602 0.3786
1.1433 1.99 350 0.8448 38.9957 33.2414 37.7868 37.8653 27.5883 12.3274 0.3526 60.3625 17.236 0.6954
0.9381 2.99 525 0.8067 42.4146 36.3126 40.964 41.0427 31.5838 13.0716 0.3833 59.6375 11.1801 0.7425
0.8116 3.98 700 0.7712 43.8741 37.8446 42.3785 42.4778 33.1873 13.0574 0.3982 61.9335 9.5238 0.7586
0.7218 4.98 875 0.7439 43.1579 37.3057 41.7059 41.8024 32.5124 12.7853 0.3931 65.8006 11.2836 0.7498
0.6461 5.97 1050 0.7254 39.9226 34.552 38.7033 38.7665 27.9936 11.4675 0.3638 77.9456 18.5041 0.7003
0.5852 6.97 1225 0.7290 44.131 38.3527 42.7974 42.8549 33.6955 12.7811 0.4026 67.855 10.3778 0.7599
0.5421 7.96 1400 0.7248 44.5368 38.7443 43.2111 43.2976 34.1121 12.7875 0.4071 67.5529 10.4037 0.7637
0.5026 8.96 1575 0.7383 43.9482 38.4156 42.6232 42.674 33.3469 12.4725 0.4016 70.997 11.8271 0.7532

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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