readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-base-finetuned-qg-context-dataset-2
    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-context-dataset-2
  
  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: 1.5958
  - Rouge1: 37.1698
  - Rouge2: 15.8177
  - Rougel: 33.3329
  - Rougelsum: 33.0872
  
  ## 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   | 1.8700          | 30.0504 | 9.8379  | 24.0514 | 24.1584   |
  | No log        | 2.0   | 146  | 1.6264          | 34.715  | 12.71   | 27.825  | 27.7697   |
  | No log        | 3.0   | 219  | 1.5904          | 33.9221 | 10.688  | 29.5483 | 29.5388   |
  | No log        | 4.0   | 292  | 1.5623          | 36.5544 | 14.8003 | 31.6295 | 31.4603   |
  | No log        | 5.0   | 365  | 1.5463          | 34.071  | 13.189  | 30.1517 | 30.3325   |
  | No log        | 6.0   | 438  | 1.5539          | 37.7324 | 15.5312 | 33.3968 | 33.2518   |
  | 1.5099        | 7.0   | 511  | 1.5643          | 32.5168 | 11.2479 | 27.4951 | 27.4425   |
  | 1.5099        | 8.0   | 584  | 1.5653          | 39.5646 | 17.9528 | 35.4095 | 35.2042   |
  | 1.5099        | 9.0   | 657  | 1.5679          | 39.333  | 17.0059 | 34.9131 | 34.7696   |
  | 1.5099        | 10.0  | 730  | 1.5757          | 37.5046 | 16.2468 | 32.5031 | 32.4012   |
  | 1.5099        | 11.0  | 803  | 1.5738          | 37.601  | 16.4592 | 33.5804 | 33.1352   |
  | 1.5099        | 12.0  | 876  | 1.5894          | 42.1889 | 19.3169 | 37.8273 | 37.7312   |
  | 1.5099        | 13.0  | 949  | 1.5929          | 38.5814 | 17.0896 | 34.4696 | 34.3629   |
  | 1.015         | 14.0  | 1022 | 1.5922          | 36.6392 | 16.8083 | 32.6318 | 32.4199   |
  | 1.015         | 15.0  | 1095 | 1.5948          | 34.6707 | 15.7198 | 30.319  | 30.3403   |
  | 1.015         | 16.0  | 1168 | 1.5958          | 37.1698 | 15.8177 | 33.3329 | 33.0872   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  