readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - sacrebleu
  model-index:
  - name: t5-pegasus-finetuned_test
    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-pegasus-finetuned_test
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 6.0045
  - Sacrebleu: 0.8737
  - Rouge 1: 0.0237
  - Rouge 2: 0.0
  - Rouge L: 0.0232
  - Bleu 1: 0.1444
  - Bleu 2: 0.0447
  - Bleu 3: 0.0175
  - Bleu 4: 0.0083
  - Meteor: 0.0609
  - Gen Len: 15.098
  
  ## 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: 128
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Rouge 1 | Rouge 2 | Rouge L | Bleu 1 | Bleu 2 | Bleu 3 | Bleu 4 | Meteor | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:-------:|:-------:|:------:|:------:|:------:|:------:|:------:|:-------:|
  | No log        | 52.5  | 210  | 5.9818          | 0.9114    | 0.0229  | 0.0     | 0.0225  | 0.1424 | 0.0436 | 0.0183 | 0.0091 | 0.06   | 15.126  |
  | No log        | 70.0  | 280  | 6.0072          | 0.876     | 0.0233  | 0.0     | 0.0228  | 0.1437 | 0.0452 | 0.0177 | 0.0083 | 0.0607 | 15.088  |
  | No log        | 87.5  | 350  | 6.0017          | 0.8695    | 0.0229  | 0.0     | 0.0225  | 0.1445 | 0.0443 | 0.0175 | 0.0082 | 0.0609 | 15.12   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0.dev0
  - Pytorch 1.9.1+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  