metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: bart-base-finetuned-samsum-en
    results:
      - task:
          type: text2text-generation
          name: Sequence-to-sequence Language Modeling
        dataset:
          name: samsum
          type: samsum
          args: samsum
        metrics:
          - type: rouge
            value: 46.8825
            name: Rouge1
      - task:
          type: summarization
          name: Summarization
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: test
        metrics:
          - type: rouge
            value: 45.0692
            name: ROUGE-1
            verified: true
            verifyToken: >-
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          - type: rouge
            value: 20.9049
            name: ROUGE-2
            verified: true
            verifyToken: >-
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          - type: rouge
            value: 37.3128
            name: ROUGE-L
            verified: true
            verifyToken: >-
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          - type: rouge
            value: 40.662
            name: ROUGE-LSUM
            verified: true
            verifyToken: >-
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          - type: loss
            value: 5.763935565948486
            name: loss
            verified: true
            verifyToken: >-
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          - type: gen_len
            value: 18.4921
            name: gen_len
            verified: true
            verifyToken: >-
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bart-base-finetuned-samsum-en

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

Loss: 2.3676
Rouge1: 46.8825
Rouge2: 22.0923
Rougel: 39.7249
Rougelsum: 42.9187

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.5172	1.0	300	2.1613	47.4152	22.8106	39.93	43.3639
0.3627	2.0	600	2.2771	47.2676	22.6325	40.1345	43.19
0.2466	3.0	900	2.3676	46.8825	22.0923	39.7249	42.9187

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1