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Training complete
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metadata
license: apache-2.0
base_model: google/mt5-small
tags:
  - summarization
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: mt5-small-finetuned_samsum_summarization_model
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: validation
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 39.9323

mt5-small-finetuned_samsum_summarization_model

This model is a fine-tuned version of google/mt5-small on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9328
  • Rouge1: 39.9323
  • Rouge2: 18.0293
  • Rougel: 34.3611
  • Rougelsum: 37.3087

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: 5.6e-05
  • train_batch_size: 14
  • eval_batch_size: 14
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
4.5012 1.0 1050 2.1992 34.6608 14.0886 29.8674 32.1737
2.6852 2.0 2100 2.1014 38.1793 16.0747 32.5426 35.4332
2.4933 3.0 3150 2.0319 38.4414 16.4993 32.6973 35.8539
2.3933 4.0 4200 1.9910 39.2966 17.1718 33.5556 36.802
2.3273 5.0 5250 1.9764 39.7619 17.7287 33.9838 37.1345
2.2783 6.0 6300 1.9503 39.9351 17.8312 34.2641 37.2625
2.2543 7.0 7350 1.9350 39.9551 17.918 34.3361 37.2039
2.2383 8.0 8400 1.9328 39.9323 18.0293 34.3611 37.3087

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0