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t5-small-finetuned-SLM-slp

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3216
  • Rouge1: 0.0
  • Rouge2: 0.0
  • Rougel: 0.0
  • Rougelsum: 0.0
  • Gen Len: 0.0

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: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 18 1.3069 0.0 0.0 0.0 0.0 0.0
No log 2.0 36 0.9637 0.0 0.0 0.0 0.0 0.0
No log 3.0 54 0.8700 0.0 0.0 0.0 0.0 0.0
No log 4.0 72 0.8496 0.0 0.0 0.0 0.0 0.0
No log 5.0 90 0.8265 0.0 0.0 0.0 0.0 0.0
No log 6.0 108 0.7646 0.0 0.0 0.0 0.0 0.0
No log 7.0 126 0.7115 0.0 0.0 0.0 0.0 0.0
No log 8.0 144 0.6772 0.0 0.0 0.0 0.0 0.0
No log 9.0 162 0.6396 0.0 0.0 0.0 0.0 0.0
No log 10.0 180 0.6141 0.0 0.0 0.0 0.0 0.0
No log 11.0 198 0.5893 0.0 0.0 0.0 0.0 0.0
No log 12.0 216 0.5606 0.0 0.0 0.0 0.0 0.0
No log 13.0 234 0.5402 0.0 0.0 0.0 0.0 0.0
No log 14.0 252 0.5238 0.0 0.0 0.0 0.0 0.0
No log 15.0 270 0.5037 0.0 0.0 0.0 0.0 0.0
No log 16.0 288 0.4876 0.0 0.0 0.0 0.0 0.0
No log 17.0 306 0.4726 0.0 0.0 0.0 0.0 0.0
No log 18.0 324 0.4586 0.0 0.0 0.0 0.0 0.0
No log 19.0 342 0.4458 0.0 0.0 0.0 0.0 0.0
No log 20.0 360 0.4337 0.0 0.0 0.0 0.0 0.0
No log 21.0 378 0.4201 0.0 0.0 0.0 0.0 0.0
No log 22.0 396 0.4115 0.0 0.0 0.0 0.0 0.0
No log 23.0 414 0.4016 0.0 0.0 0.0 0.0 0.0
No log 24.0 432 0.3860 0.0 0.0 0.0 0.0 0.0
No log 25.0 450 0.3783 0.0 0.0 0.0 0.0 0.0
No log 26.0 468 0.3731 0.0 0.0 0.0 0.0 0.0
No log 27.0 486 0.3657 0.0 0.0 0.0 0.0 0.0
0.9036 28.0 504 0.3559 0.0 0.0 0.0 0.0 0.0
0.9036 29.0 522 0.3504 0.0 0.0 0.0 0.0 0.0
0.9036 30.0 540 0.3474 0.0 0.0 0.0 0.0 0.0
0.9036 31.0 558 0.3439 0.0 0.0 0.0 0.0 0.0
0.9036 32.0 576 0.3402 0.0 0.0 0.0 0.0 0.0
0.9036 33.0 594 0.3345 0.0 0.0 0.0 0.0 0.0
0.9036 34.0 612 0.3316 0.0 0.0 0.0 0.0 0.0
0.9036 35.0 630 0.3303 0.0 0.0 0.0 0.0 0.0
0.9036 36.0 648 0.3270 0.0 0.0 0.0 0.0 0.0
0.9036 37.0 666 0.3249 0.0 0.0 0.0 0.0 0.0
0.9036 38.0 684 0.3231 0.0 0.0 0.0 0.0 0.0
0.9036 39.0 702 0.3220 0.0 0.0 0.0 0.0 0.0
0.9036 40.0 720 0.3216 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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