readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-base-finetuned-qg-medium-hard-qns
    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-base-finetuned-qg-medium-hard-qns
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5919
  - Rouge1: 38.6117
  - Rouge2: 21.3082
  - Rougel: 35.7294
  - Rougelsum: 35.4192
  
  ## 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: 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | No log        | 1.0   | 73   | 1.8640          | 31.2085 | 11.6418 | 26.1137 | 26.2911   |
  | No log        | 2.0   | 146  | 1.6488          | 29.6798 | 10.9223 | 26.7442 | 26.9736   |
  | No log        | 3.0   | 219  | 1.6045          | 33.6703 | 11.7038 | 30.167  | 29.9192   |
  | No log        | 4.0   | 292  | 1.5812          | 36.6758 | 17.748  | 33.739  | 33.4974   |
  | No log        | 5.0   | 365  | 1.5879          | 33.3704 | 16.4099 | 31.7658 | 31.3874   |
  | No log        | 6.0   | 438  | 1.5786          | 34.1216 | 14.9588 | 30.9584 | 30.9277   |
  | 1.7533        | 7.0   | 511  | 1.5804          | 34.8267 | 15.7046 | 32.0877 | 31.9317   |
  | 1.7533        | 8.0   | 584  | 1.5861          | 33.2539 | 12.728  | 30.551  | 30.2299   |
  | 1.7533        | 9.0   | 657  | 1.5911          | 38.4406 | 20.5922 | 36.4267 | 36.0426   |
  | 1.7533        | 10.0  | 730  | 1.5827          | 33.3421 | 16.0455 | 29.974  | 29.5357   |
  | 1.7533        | 11.0  | 803  | 1.5834          | 42.3363 | 24.6712 | 40.4291 | 40.0842   |
  | 1.7533        | 12.0  | 876  | 1.5889          | 33.268  | 15.5319 | 30.6942 | 30.4347   |
  | 1.7533        | 13.0  | 949  | 1.5911          | 42.1265 | 23.1983 | 39.5768 | 39.2304   |
  | 1.2341        | 14.0  | 1022 | 1.5926          | 35.0279 | 15.825  | 32.0736 | 32.0093   |
  | 1.2341        | 15.0  | 1095 | 1.5912          | 38.362  | 17.6108 | 35.3148 | 35.0558   |
  | 1.2341        | 16.0  | 1168 | 1.5919          | 38.6117 | 21.3082 | 35.7294 | 35.4192   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  