readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-asqa-ob
    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-asqa-ob
  
  This model is a fine-tuned version of [google/t5-small-ssm-nq](https://huggingface.co/google/t5-small-ssm-nq) on the [ASQA](https://huggingface.co/datasets/din0s/asqa) dataset without context (closed book).
  It achieves the following results on the evaluation set:
  - Loss: 2.8099
  - Rouge1: 0.1493
  - Rouge2: 0.0837
  - Rougel: 0.1272
  - Rougelsum: 0.1270
  
  ## 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: 0.0005
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 3.8208        | 1.0   | 710  | 2.7856          | 0.1267 | 0.0644 | 0.1086 | 0.1084    |
  | 3.0532        | 2.0   | 1420 | 2.6247          | 0.1321 | 0.0721 | 0.1145 | 0.1144    |
  | 2.5656        | 3.0   | 2130 | 2.5062          | 0.1399 | 0.0773 | 0.1213 | 0.1213    |
  | 2.3806        | 4.0   | 2840 | 2.5004          | 0.1431 | 0.0805 | 0.1243 | 0.1241    |
  | 2.157         | 5.0   | 3550 | 2.5008          | 0.1455 | 0.0808 | 0.1255 | 0.1254    |
  | 2.0458        | 6.0   | 4260 | 2.5313          | 0.1510 | 0.0846 | 0.1303 | 0.1301    |
  | 1.914         | 7.0   | 4970 | 2.5298          | 0.1585 | 0.0885 | 0.1361 | 0.1358    |
  | 1.7479        | 8.0   | 5680 | 2.5832          | 0.1508 | 0.0844 | 0.1292 | 0.1291    |
  | 1.6875        | 9.0   | 6390 | 2.5928          | 0.1493 | 0.0834 | 0.1281 | 0.1279    |
  | 1.574         | 10.0  | 7100 | 2.6364          | 0.1591 | 0.0885 | 0.1364 | 0.1363    |
  | 1.4554        | 11.0  | 7810 | 2.6978          | 0.1513 | 0.0849 | 0.1295 | 0.1295    |
  | 1.3909        | 12.0  | 8520 | 2.8099          | 0.1493 | 0.0837 | 0.1272 | 0.1270    |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.12.1+cu102
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  