readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: flan-t5-base-xsum-swe
    results: []
  
  inference:
    parameters:
      temperature: 0.7
      min_length: 30
      max_length: 120
  
  ---
  
  <!-- 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. -->
  
  # flan-t5-base-xsum-swe
  
  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4174
  - Rouge1: 20.3004
  - Rouge2: 6.2309
  - Rougel: 17.5863
  - Rougelsum: 17.5827
  - Gen Len: 18.9998
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 1.8384        | 1.0   | 12751 | 1.6491          | 19.0409 | 5.1339 | 16.3642 | 16.3725   | 19.0    |
  | 1.6806        | 2.0   | 25502 | 1.5189          | 19.882  | 5.7451 | 17.1187 | 17.1233   | 19.0    |
  | 1.5961        | 3.0   | 38253 | 1.4575          | 20.237  | 6.1009 | 17.4642 | 17.4647   | 18.9998 |
  | 1.5556        | 4.0   | 51004 | 1.4268          | 20.2998 | 6.2217 | 17.5423 | 17.541    | 18.9998 |
  | 1.5429        | 5.0   | 63755 | 1.4174          | 20.3004 | 6.2309 | 17.5863 | 17.5827   | 18.9998 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  