readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-ted-id-en-lr_1e-2-ep_30-seq_128-bs_64
    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. -->
  
  # nmt-ted-id-en-lr_1e-2-ep_30-seq_128-bs_64
  
  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: 2.0751
  - Bleu: 16.4354
  - Gen Len: 16.3492
  - Meteor: 0.3448
  
  ## 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: 0.01
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len | Meteor |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:------:|
  | 3.2366        | 1.0   | 625   | 2.4442          | 7.3157  | 16.9063 | 0.2192 |
  | 2.5208        | 2.0   | 1250  | 2.0785          | 11.3311 | 16.0768 | 0.2869 |
  | 2.1936        | 3.0   | 1875  | 1.8995          | 12.4756 | 16.4486 | 0.2934 |
  | 1.872         | 4.0   | 2500  | 1.8241          | 13.9295 | 16.3092 | 0.3163 |
  | 1.7185        | 5.0   | 3125  | 1.7624          | 14.3797 | 16.3602 | 0.3213 |
  | 1.6177        | 6.0   | 3750  | 1.7049          | 15.2549 | 16.3835 | 0.3304 |
  | 1.5355        | 7.0   | 4375  | 1.7059          | 15.7225 | 16.3599 | 0.3346 |
  | 1.388         | 8.0   | 5000  | 1.6864          | 15.4343 | 16.4646 | 0.3308 |
  | 1.2741        | 9.0   | 5625  | 1.6899          | 16.2174 | 16.3215 | 0.3428 |
  | 1.216         | 10.0  | 6250  | 1.6831          | 16.1891 | 16.2815 | 0.3451 |
  | 1.1486        | 11.0  | 6875  | 1.7137          | 16.3811 | 16.3451 | 0.3435 |
  | 1.0426        | 12.0  | 7500  | 1.7490          | 16.3482 | 16.3791 | 0.343  |
  | 0.9509        | 13.0  | 8125  | 1.7674          | 16.3318 | 16.469  | 0.3436 |
  | 0.9072        | 14.0  | 8750  | 1.8084          | 16.4721 | 16.3064 | 0.3452 |
  | 0.857         | 15.0  | 9375  | 1.8414          | 16.4244 | 16.3718 | 0.3472 |
  | 0.7696        | 16.0  | 10000 | 1.8829          | 16.3755 | 16.3816 | 0.3446 |
  | 0.7066        | 17.0  | 10625 | 1.9325          | 16.4635 | 16.3957 | 0.3459 |
  | 0.6718        | 18.0  | 11250 | 1.9980          | 16.3287 | 16.3124 | 0.3431 |
  | 0.6364        | 19.0  | 11875 | 2.0211          | 16.5732 | 16.3558 | 0.3456 |
  | 0.5835        | 20.0  | 12500 | 2.0751          | 16.4354 | 16.3492 | 0.3448 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  