kaixkhazaki's picture
End of training
ed7f99a verified
metadata
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
datasets:
  - mlsum
metrics:
  - rouge
model-index:
  - name: flan-t5-base-turkish-summarisation
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: mlsum
          type: mlsum
          config: tu
          split: validation
          args: tu
        metrics:
          - name: Rouge1
            type: rouge
            value: 17.7215

flan-t5-base-turkish-summarisation

This model is a fine-tuned version of google/flan-t5-base on the mlsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2759
  • Rouge1: 17.7215
  • Rouge2: 11.6449
  • Rougel: 17.1215
  • Rougelsum: 17.0317
  • Gen Len: 20.0

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.5856 0.0802 200 1.3164 18.0769 11.7482 17.3132 17.32 20.0
1.4888 0.1604 400 1.2901 17.6893 11.6682 16.9148 16.8964 20.0
1.4787 0.2407 600 1.2827 17.5252 11.5143 16.8586 16.8281 20.0
1.488 0.3209 800 1.2637 17.8913 11.7712 17.1369 17.0949 20.0
1.4105 0.4011 1000 1.2759 17.7215 11.6449 17.1215 17.0317 20.0

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.2.2
  • Datasets 3.2.0
  • Tokenizers 0.21.0