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metadata
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: flanT5Base-riksIdentification-trained
    results: []

flanT5Base-riksIdentification-trained

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

  • Loss: 1.5288
  • Rouge1: 40.8854
  • Rouge2: 22.6821
  • Rougel: 36.0638
  • Rougelsum: 36.8444
  • Gen Len: 18.7778

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: 3e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 60 1.9165 39.1847 20.771 35.3702 35.7857 18.3148
No log 2.0 120 1.8308 40.7152 21.7447 36.6752 37.1989 18.6296
No log 3.0 180 1.7769 40.7843 22.2581 36.3515 36.9362 18.7407
No log 4.0 240 1.7355 39.8099 21.8843 35.5563 36.0749 18.9444
No log 5.0 300 1.6971 41.3752 23.8678 36.8792 37.3489 18.7037
No log 6.0 360 1.6690 41.2441 23.4026 36.4348 37.067 18.9074
No log 7.0 420 1.6327 40.9744 23.6697 36.3964 36.9935 18.9074
No log 8.0 480 1.6214 41.3833 23.796 36.7591 37.4926 18.9815
1.7877 9.0 540 1.5955 40.9415 23.3711 36.2089 36.8672 18.7407
1.7877 10.0 600 1.5821 41.1759 23.362 36.5208 37.2207 18.7963
1.7877 11.0 660 1.5687 41.5582 23.575 36.4706 37.1927 18.9074
1.7877 12.0 720 1.5685 41.5293 23.2829 36.7273 37.468 18.8148
1.7877 13.0 780 1.5503 40.6781 21.9403 35.725 36.3384 18.9444
1.7877 14.0 840 1.5454 40.4918 22.3652 35.7063 36.3163 18.9815
1.7877 15.0 900 1.5364 41.6247 23.5637 36.9036 37.4561 18.8704
1.7877 16.0 960 1.5344 41.1763 23.2285 36.2463 36.6802 18.8704
1.3826 17.0 1020 1.5303 40.4807 21.8633 35.5338 36.2185 18.8519
1.3826 18.0 1080 1.5288 40.8854 22.6821 36.0638 36.8444 18.7778
1.3826 19.0 1140 1.5306 40.739 22.393 35.9189 36.4907 18.9815
1.3826 20.0 1200 1.5291 40.739 22.393 35.9189 36.4907 18.9815

Framework versions

  • Transformers 4.52.3
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1