readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: speller-t5-finetuned
    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. -->
  
  # speller-t5-finetuned
  
  This model is a fine-tuned version of [UrukHan/t5-russian-spell](https://huggingface.co/UrukHan/t5-russian-spell) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0737
  - Rouge1: 25.3988
  - Rouge2: 11.756
  - Rougel: 25.051
  - Rougelsum: 25.2041
  - Gen Len: 41.3929
  
  ## 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 | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 0.1861        | 0.07  | 1000  | 0.1074          | 24.351  | 9.9107  | 24.0512 | 24.1443   | 41.4375 |
  | 0.1629        | 0.14  | 2000  | 0.0918          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3839 |
  | 0.1545        | 0.21  | 3000  | 0.0898          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.2857 |
  | 0.1507        | 0.29  | 4000  | 0.0860          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3571 |
  | 0.1472        | 0.36  | 5000  | 0.0823          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3661 |
  | 0.1417        | 0.43  | 6000  | 0.0794          | 24.6565 | 10.2976 | 24.265  | 24.4006   | 41.4107 |
  | 0.1411        | 0.5   | 7000  | 0.0788          | 25.1414 | 11.3393 | 24.8541 | 24.9175   | 41.3482 |
  | 0.1395        | 0.57  | 8000  | 0.0786          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3125 |
  | 0.1318        | 0.64  | 9000  | 0.0774          | 25.2909 | 11.5882 | 24.981  | 25.0772   | 41.3929 |
  | 0.1336        | 0.72  | 10000 | 0.0758          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3839 |
  | 0.1332        | 0.79  | 11000 | 0.0743          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3482 |
  | 0.1309        | 0.86  | 12000 | 0.0734          | 25.2394 | 11.5476 | 24.9777 | 25.0511   | 41.3393 |
  | 0.1264        | 0.93  | 13000 | 0.0737          | 25.3988 | 11.756  | 25.051  | 25.2041   | 41.3929 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  