readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  - longt5
  - summarization
  model-index:
  - name: longt5-mediasum
    results:
    - task:
        type: summarization
        name: Summarization
      dataset:
        name: xsum
        type: xsum
        config: default
        split: test
      metrics:
      - name: ROUGE-1
        type: rouge
        value: 22.7044
        verified: true
      - name: ROUGE-2
        type: rouge
        value: 5.616
        verified: true
      - name: ROUGE-L
        type: rouge
        value: 18.0111
        verified: true
      - name: ROUGE-LSUM
        type: rouge
        value: 18.1554
        verified: true
      - name: loss
        type: loss
        value: 2.1656227111816406
        verified: true
      - name: gen_len
        type: gen_len
        value: 18.3527
        verified: true
    - task:
        type: summarization
        name: Summarization
      dataset:
        name: cnn_dailymail
        type: cnn_dailymail
        config: 3.0.0
        split: test
      metrics:
      - name: ROUGE-1
        type: rouge
        value: 21.1522
        verified: true
      - name: ROUGE-2
        type: rouge
        value: 8.1315
        verified: true
      - name: ROUGE-L
        type: rouge
        value: 16.6625
        verified: true
      - name: ROUGE-LSUM
        type: rouge
        value: 19.3603
        verified: true
      - name: loss
        type: loss
        value: 1.899269700050354
        verified: true
      - name: gen_len
        type: gen_len
        value: 17.853
        verified: true
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # longt5-mediasum
  
  This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0129
  
  ## 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: 12
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.66          | 1.0   | 1667 | 2.0643          |
  | 2.472         | 2.0   | 3334 | 2.0241          |
  | 2.3574        | 3.0   | 5001 | 2.0129          |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0a0+17540c5
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  