readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-large-finetune-keyword-to-text-generation
    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-large-finetune-keyword-to-text-generation
  
  This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.1471
  - Rouge1: 2.175
  - Rouge2: 0.3661
  - Rougel: 1.7927
  - Rougelsum: 1.7951
  - Gen Len: 15.3252
  
  ## Model description
  
  This model is designed to generate text from a single keyword. This project is intended to be used for generating vocabulary questions for ed-tech applications. 
  
  NOTE!: Be sure to use the 'summarize: ' prefix before the word that you would like to un-summarize.
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 3.3083        | 1.0   | 3000  | 3.1706          | 2.1498 | 0.331  | 1.7579 | 1.761     | 16.6826 |
  | 3.2121        | 2.0   | 6000  | 3.1403          | 2.1555 | 0.3409 | 1.7659 | 1.769     | 16.208  |
  | 3.1286        | 3.0   | 9000  | 3.1300          | 2.1577 | 0.3511 | 1.7703 | 1.7733    | 15.9009 |
  | 3.0567        | 4.0   | 12000 | 3.1282          | 2.183  | 0.3584 | 1.7895 | 1.7909    | 15.7135 |
  | 2.9953        | 5.0   | 15000 | 3.1293          | 2.1589 | 0.3525 | 1.776  | 1.7781    | 15.678  |
  | 2.9483        | 6.0   | 18000 | 3.1308          | 2.1645 | 0.3556 | 1.7824 | 1.784     | 15.425  |
  | 2.9009        | 7.0   | 21000 | 3.1358          | 2.1622 | 0.3622 | 1.7848 | 1.7877    | 15.3348 |
  | 2.8752        | 8.0   | 24000 | 3.1387          | 2.1716 | 0.36   | 1.7936 | 1.7963    | 15.5296 |
  | 2.835         | 9.0   | 27000 | 3.1454          | 2.1806 | 0.3658 | 1.7941 | 1.7966    | 15.4625 |
  | 2.8352        | 10.0  | 30000 | 3.1471          | 2.175  | 0.3661 | 1.7927 | 1.7951    | 15.3252 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  