readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-rahul-summariza
    results: []
  ---
  
  <!-- 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-rahul-summariza
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7002
  - Rouge1: 29.5043
  - Rouge2: 23.832
  - Rougel: 27.5786
  - Rougelsum: 28.404
  - Gen Len: 19.0
  
  ## 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: 8
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.123         | 1.0   | 16   | 0.8258          | 27.2788 | 21.3634 | 25.7114 | 26.7324   | 19.0    |
  | 0.9067        | 2.0   | 32   | 0.7539          | 28.873  | 23.5401 | 27.2337 | 27.939    | 19.0    |
  | 0.8137        | 3.0   | 48   | 0.7280          | 29.1767 | 23.6599 | 27.7065 | 28.3569   | 19.0    |
  | 0.7872        | 4.0   | 64   | 0.7230          | 29.0451 | 23.4597 | 27.2762 | 28.1324   | 19.0    |
  | 0.7338        | 5.0   | 80   | 0.7133          | 29.4821 | 23.8113 | 27.4912 | 28.326    | 19.0    |
  | 0.6913        | 6.0   | 96   | 0.7101          | 29.4237 | 23.8523 | 27.4109 | 28.2418   | 19.0    |
  | 0.6679        | 7.0   | 112  | 0.7097          | 29.4237 | 23.8523 | 27.4109 | 28.2418   | 19.0    |
  | 0.6963        | 8.0   | 128  | 0.7046          | 29.4237 | 23.8523 | 27.4109 | 28.2418   | 19.0    |
  | 0.6223        | 9.0   | 144  | 0.7052          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.6494        | 10.0  | 160  | 0.7019          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.616         | 11.0  | 176  | 0.7010          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.6058        | 12.0  | 192  | 0.7028          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.5964        | 13.0  | 208  | 0.6996          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.5958        | 14.0  | 224  | 0.6997          | 29.4237 | 23.7633 | 27.493  | 28.3362   | 19.0    |
  | 0.57          | 15.0  | 240  | 0.6996          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  | 0.5714        | 16.0  | 256  | 0.6998          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  | 0.5648        | 17.0  | 272  | 0.6999          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  | 0.5258        | 18.0  | 288  | 0.7005          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  | 0.5692        | 19.0  | 304  | 0.7001          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  | 0.5708        | 20.0  | 320  | 0.7002          | 29.5043 | 23.832  | 27.5786 | 28.404    | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  