readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: t5-base-finetuned-en-to-it-lrs-back
    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-base-finetuned-en-to-it-lrs-back
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2426
  - Bleu: 27.5339
  - Gen Len: 50.356
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 1.997         | 1.0   | 1125  | 1.8350          | 10.7997 | 58.974  |
  | 1.8185        | 2.0   | 2250  | 1.7013          | 13.8533 | 56.2727 |
  | 1.6898        | 3.0   | 3375  | 1.6177          | 16.2932 | 53.914  |
  | 1.5706        | 4.0   | 4500  | 1.5542          | 18.0621 | 53.4973 |
  | 1.5151        | 5.0   | 5625  | 1.5086          | 19.4227 | 53.6307 |
  | 1.468         | 6.0   | 6750  | 1.4707          | 20.8101 | 52.2427 |
  | 1.4313        | 7.0   | 7875  | 1.4438          | 21.7975 | 51.8    |
  | 1.383         | 8.0   | 9000  | 1.4182          | 22.4852 | 51.7193 |
  | 1.3555        | 9.0   | 10125 | 1.3991          | 23.0898 | 51.448  |
  | 1.3259        | 10.0  | 11250 | 1.3802          | 23.5277 | 51.6953 |
  | 1.3041        | 11.0  | 12375 | 1.3656          | 23.9072 | 51.1547 |
  | 1.2781        | 12.0  | 13500 | 1.3518          | 24.1772 | 51.3293 |
  | 1.2577        | 13.0  | 14625 | 1.3394          | 24.4547 | 51.6307 |
  | 1.24          | 14.0  | 15750 | 1.3312          | 24.9846 | 50.9827 |
  | 1.2198        | 15.0  | 16875 | 1.3180          | 25.1942 | 51.042  |
  | 1.2071        | 16.0  | 18000 | 1.3098          | 25.5082 | 50.6113 |
  | 1.1948        | 17.0  | 19125 | 1.3024          | 25.523  | 50.782  |
  | 1.1795        | 18.0  | 20250 | 1.2961          | 25.8367 | 50.7987 |
  | 1.1691        | 19.0  | 21375 | 1.2904          | 25.9142 | 50.6667 |
  | 1.159         | 20.0  | 22500 | 1.2824          | 26.2538 | 50.602  |
  | 1.1504        | 21.0  | 23625 | 1.2794          | 26.2023 | 50.5987 |
  | 1.1389        | 22.0  | 24750 | 1.2746          | 26.464  | 50.4593 |
  | 1.1309        | 23.0  | 25875 | 1.2694          | 26.4899 | 50.5353 |
  | 1.1185        | 24.0  | 27000 | 1.2676          | 26.8721 | 50.468  |
  | 1.1126        | 25.0  | 28125 | 1.2635          | 26.8721 | 50.4693 |
  | 1.1093        | 26.0  | 29250 | 1.2603          | 27.0334 | 50.334  |
  | 1.104         | 27.0  | 30375 | 1.2569          | 27.2444 | 50.554  |
  | 1.0988        | 28.0  | 31500 | 1.2535          | 27.2597 | 50.5367 |
  | 1.0893        | 29.0  | 32625 | 1.2509          | 27.3268 | 50.42   |
  | 1.0883        | 30.0  | 33750 | 1.2519          | 27.4412 | 50.4253 |
  | 1.0802        | 31.0  | 34875 | 1.2479          | 27.3715 | 50.4247 |
  | 1.0697        | 32.0  | 36000 | 1.2476          | 27.3871 | 50.5567 |
  | 1.0729        | 33.0  | 37125 | 1.2457          | 27.4333 | 50.418  |
  | 1.065         | 34.0  | 38250 | 1.2451          | 27.4571 | 50.4287 |
  | 1.0649        | 35.0  | 39375 | 1.2451          | 27.5448 | 50.3393 |
  | 1.0644        | 36.0  | 40500 | 1.2438          | 27.5387 | 50.2813 |
  | 1.0624        | 37.0  | 41625 | 1.2423          | 27.5011 | 50.402  |
  | 1.0617        | 38.0  | 42750 | 1.2434          | 27.5414 | 50.336  |
  | 1.0606        | 39.0  | 43875 | 1.2429          | 27.5247 | 50.3387 |
  | 1.0508        | 40.0  | 45000 | 1.2426          | 27.5339 | 50.356  |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.5.1
  - Tokenizers 0.11.0
  