readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-small-herblabels
    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-herblabels
  
  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: 0.4823
  - Rouge1: 3.0759
  - Rouge2: 1.0495
  - Rougel: 3.0758
  - Rougelsum: 3.0431
  - Gen Len: 18.9716
  
  ## 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: 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | No log        | 1.0   | 264  | 1.6010          | 2.4276 | 0.5658 | 2.3546 | 2.3099    | 18.9091 |
  | 2.5052        | 2.0   | 528  | 1.0237          | 2.9016 | 0.3395 | 2.8221 | 2.783     | 18.9673 |
  | 2.5052        | 3.0   | 792  | 0.7793          | 2.962  | 0.3091 | 2.9375 | 2.8786    | 18.9588 |
  | 1.1552        | 4.0   | 1056 | 0.6530          | 2.98   | 0.4375 | 2.9584 | 2.8711    | 18.9588 |
  | 1.1552        | 5.0   | 1320 | 0.5863          | 3.0023 | 0.5882 | 2.987  | 2.9155    | 18.9588 |
  | 0.8659        | 6.0   | 1584 | 0.5428          | 3.0576 | 0.8019 | 3.0494 | 2.9989    | 18.9716 |
  | 0.8659        | 7.0   | 1848 | 0.5145          | 3.0808 | 0.9476 | 3.0719 | 3.0237    | 18.9716 |
  | 0.747         | 8.0   | 2112 | 0.4962          | 3.0748 | 1.0032 | 3.0683 | 3.0359    | 18.9716 |
  | 0.747         | 9.0   | 2376 | 0.4856          | 3.0702 | 1.0196 | 3.0665 | 3.0328    | 18.9716 |
  | 0.6987        | 10.0  | 2640 | 0.4823          | 3.0759 | 1.0495 | 3.0758 | 3.0431    | 18.9716 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  