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mt5-base-finetuned-test_30483_prefix_summarize-finetuned-test_21911_prefix_summarize

This model is a fine-tuned version of emilstabil/mt5-base-finetuned-test_30483_prefix_summarize on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3442
  • Rouge1: 26.765
  • Rouge2: 7.4581
  • Rougel: 17.0907
  • Rougelsum: 24.6176
  • Gen Len: 86.94

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • 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 Gen Len
2.5963 1.25 500 2.3638 24.4676 7.3477 16.2948 22.5499 75.59
2.4234 2.5 1000 2.3433 25.3322 7.2863 16.2352 23.3304 76.8
2.3196 3.75 1500 2.3308 25.5632 7.1264 16.4164 23.4946 82.05
2.2519 5.0 2000 2.3315 25.0637 7.1123 16.1223 23.0408 74.67
2.1623 6.25 2500 2.3487 26.4375 7.3373 16.6264 24.2391 80.73
2.1145 7.5 3000 2.3376 25.703 7.2824 16.5698 23.5391 77.68
2.0668 8.75 3500 2.3416 25.5062 7.2385 16.4797 23.3875 77.94
2.0175 10.0 4000 2.3330 26.1031 7.581 16.7435 23.8668 79.52
1.9757 11.25 4500 2.3453 26.8941 7.3977 16.6922 24.4811 89.72
1.9527 12.5 5000 2.3354 27.0584 7.7057 17.3043 24.8764 83.53
1.9263 13.75 5500 2.3444 26.7263 7.5763 16.9772 24.4145 85.38
1.9072 15.0 6000 2.3393 26.6875 7.3326 16.9405 24.4442 87.55
1.8678 16.25 6500 2.3390 26.1098 7.2367 16.6426 24.0273 83.85
1.882 17.5 7000 2.3388 26.6687 7.543 17.1994 24.5235 84.56
1.8269 18.75 7500 2.3447 27.3232 7.8632 17.3518 25.1263 87.26
1.8403 20.0 8000 2.3442 26.765 7.4581 17.0907 24.6176 86.94

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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