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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: switch-base-16-finetuned-samsum
    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: 47.2139
widget:
  - text: |-
      Sid: Wanna catch a movie?
      Annie: sure what do you have in mind?
      Sid; the Aquaman? :D
      Annie: haha isn't it a bit childish
      Sid: noooooo I mean yes but it's the highest grossing movie this week
      Annie: seriously?
      Sid: yeah?
      Annie: okay let's see what the fuss is all about

Switch Transformer (base-16) fine-tuned om samsum for conversation summarization

This model is a fine-tuned version of google/switch-base-16 on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4434
  • Rouge1: 47.2139
  • Rouge2: 23.3399
  • Rougel: 39.8364
  • Rougelsum: 43.2592
  • Gen Len: 16.9194

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.846 1.0 3683 1.4857 45.9134 22.4258 38.9716 42.6169 17.0623
1.5734 2.0 7366 1.4346 47.574 24.2967 40.3749 44.2636 17.3790
1.38 3.0 11049 1.4277 47.9915 24.9077 40.658 44.5301 17.1406
1.2388 4.0 14732 1.4223 48.3444 25.4061 41.2776 45.0434 16.9254
1.1629 5.0 18415 1.4372 48.5991 25.5464 41.3726 45.0784 16.9890

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.7.1
  • Tokenizers 0.13.2