readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-finetuned-qa-google-en-question_v1
    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-qa-google-en-question_v1
  
  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: 3.1358
  - Rouge1: 49.6232
  - Rouge2: 26.4156
  - Rougel: 46.9194
  - Rougelsum: 46.8814
  - Gen Len: 13.5795
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 0.27  | 100  | 3.5967          | 43.7809 | 21.3303 | 41.6782 | 41.6869   | 12.9745 |
  | No log        | 0.53  | 200  | 3.4539          | 45.7744 | 22.9574 | 43.4412 | 43.4249   | 13.416  |
  | No log        | 0.8   | 300  | 3.3771          | 47.1053 | 24.1406 | 44.6092 | 44.6051   | 13.386  |
  | No log        | 1.06  | 400  | 3.3229          | 47.5933 | 24.7048 | 45.086  | 45.1266   | 13.4725 |
  | 3.6954        | 1.33  | 500  | 3.2851          | 47.8847 | 24.7439 | 45.322  | 45.3243   | 13.5975 |
  | 3.6954        | 1.6   | 600  | 3.2570          | 48.1836 | 25.3062 | 45.6641 | 45.6346   | 13.5955 |
  | 3.6954        | 1.86  | 700  | 3.2321          | 48.7604 | 25.7254 | 46.1789 | 46.1537   | 13.476  |
  | 3.6954        | 2.13  | 800  | 3.2140          | 48.7518 | 25.639  | 46.2817 | 46.2343   | 13.5855 |
  | 3.6954        | 2.39  | 900  | 3.1963          | 49.0046 | 25.8439 | 46.4097 | 46.3732   | 13.6855 |
  | 3.3928        | 2.66  | 1000 | 3.1844          | 49.3227 | 26.0336 | 46.7032 | 46.6402   | 13.557  |
  | 3.3928        | 2.93  | 1100 | 3.1736          | 49.4069 | 26.0619 | 46.691  | 46.6406   | 13.5475 |
  | 3.3928        | 3.19  | 1200 | 3.1630          | 49.4614 | 26.1224 | 46.7679 | 46.7416   | 13.614  |
  | 3.3928        | 3.46  | 1300 | 3.1556          | 49.7542 | 26.4413 | 47.0601 | 47.0201   | 13.625  |
  | 3.3928        | 3.72  | 1400 | 3.1500          | 49.4097 | 26.1732 | 46.7324 | 46.6833   | 13.6795 |
  | 3.3144        | 3.99  | 1500 | 3.1440          | 49.5359 | 26.3478 | 46.8079 | 46.7769   | 13.604  |
  | 3.3144        | 4.26  | 1600 | 3.1406          | 49.8245 | 26.5312 | 47.1247 | 47.0744   | 13.552  |
  | 3.3144        | 4.52  | 1700 | 3.1378          | 49.6884 | 26.4023 | 46.9501 | 46.9063   | 13.5785 |
  | 3.3144        | 4.79  | 1800 | 3.1358          | 49.6232 | 26.4156 | 46.9194 | 46.8814   | 13.5795 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  