readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - squad
  metrics:
  - rouge
  model_index:
  - name: t5-small-finetuned-xsum-2
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: squad
        type: squad
        args: plain_text
      metric:
        name: Rouge1
        type: rouge
        value: 28.8137
  ---
  
  <!-- 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. -->
  
  # t5-small-finetuned-xsum-2
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the squad dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9536
  - Rouge1: 28.8137
  - Rouge2: 9.1265
  - Rougel: 26.0238
  - Rougelsum: 26.0217
  - Gen Len: 13.854
  
  ## 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: 2e-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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.2142        | 1.0   | 8760  | 1.9994          | 29.007  | 9.2583 | 26.2377 | 26.2356   | 13.4546 |
  | 2.1372        | 2.0   | 17520 | 1.9622          | 29.1077 | 9.445  | 26.3734 | 26.3687   | 13.6995 |
  | 2.0755        | 3.0   | 26280 | 1.9536          | 28.8137 | 9.1265 | 26.0238 | 26.0217   | 13.854  |
  
  
  ### Framework versions
  
  - Transformers 4.9.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  