readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - null
  model-index:
  - name: text-to-sparql-t5-small-2021-10-18_12-12
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
  ---
  
  <!-- 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. -->
  
  # text-to-sparql-t5-small-2021-10-18_12-12
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3284
  - Gen Len: 19.0
  - Bertscorer-p: 0.5420
  - Bertscorer-r: 0.0732
  - Bertscorer-f1: 0.2972
  - Sacrebleu-score: 4.8763
  - Sacrebleu-precisions: [87.2581084764241, 73.48869132519009, 64.19139944127409, 58.342420937840785]
  - Bleu-bp: 0.0697
  
  ## 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: 5e-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: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Gen Len | Bertscorer-p | Bertscorer-r | Bertscorer-f1 | Sacrebleu-score | Sacrebleu-precisions                                                         | Bleu-bp |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:------------:|:-------------:|:---------------:|:----------------------------------------------------------------------------:|:-------:|
  | 0.4209        | 1.0   | 4772 | 0.3284          | 19.0    | 0.5420       | 0.0732       | 0.2972        | 4.8763          | [87.2581084764241, 73.48869132519009, 64.19139944127409, 58.342420937840785] | 0.0697  |
  
  
  ### Framework versions
  
  - Transformers 4.10.0
  - Pytorch 1.9.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  