readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-ted-id-en-lr_1e-3-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-3-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: 1.6505
  - Bleu: 18.2883
  - Gen Len: 16.2262
  - Meteor: 0.3649
  
  ## 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: 0.001
  - 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len | Meteor |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:------:|
  | 2.4121        | 1.0   | 625   | 1.7491          | 12.8148 | 16.6354 | 0.293  |
  | 1.9046        | 2.0   | 1250  | 1.5805          | 15.2033 | 16.2966 | 0.3249 |
  | 1.7145        | 3.0   | 1875  | 1.4995          | 16.1248 | 16.363  | 0.3378 |
  | 1.5134        | 4.0   | 2500  | 1.4677          | 16.5428 | 16.3165 | 0.3442 |
  | 1.4192        | 5.0   | 3125  | 1.4495          | 17.0497 | 16.2708 | 0.3508 |
  | 1.3584        | 6.0   | 3750  | 1.4328          | 17.4935 | 16.3636 | 0.3515 |
  | 1.3161        | 7.0   | 4375  | 1.4375          | 17.6288 | 16.2925 | 0.3553 |
  | 1.2355        | 8.0   | 5000  | 1.4354          | 17.8579 | 16.3658 | 0.3581 |
  | 1.1749        | 9.0   | 5625  | 1.4395          | 18.063  | 16.3039 | 0.3595 |
  | 1.1464        | 10.0  | 6250  | 1.4489          | 18.2212 | 16.2542 | 0.3614 |
  | 1.1117        | 11.0  | 6875  | 1.4535          | 18.0255 | 16.2545 | 0.361  |
  | 1.0608        | 12.0  | 7500  | 1.4656          | 18.3451 | 16.2774 | 0.3624 |
  | 1.0179        | 13.0  | 8125  | 1.4685          | 18.3879 | 16.2881 | 0.3647 |
  | 0.9986        | 14.0  | 8750  | 1.4824          | 18.3278 | 16.2391 | 0.3643 |
  | 0.9716        | 15.0  | 9375  | 1.4983          | 18.4478 | 16.2554 | 0.3649 |
  | 0.9355        | 16.0  | 10000 | 1.5088          | 18.5089 | 16.2369 | 0.3655 |
  | 0.9027        | 17.0  | 10625 | 1.5139          | 18.2406 | 16.2369 | 0.3644 |
  | 0.8845        | 18.0  | 11250 | 1.5294          | 18.2969 | 16.2133 | 0.3634 |
  | 0.8659        | 19.0  | 11875 | 1.5457          | 18.4358 | 16.2142 | 0.365  |
  | 0.8378        | 20.0  | 12500 | 1.5733          | 18.3323 | 16.2447 | 0.3645 |
  | 0.8138        | 21.0  | 13125 | 1.5718          | 18.1424 | 16.2048 | 0.3634 |
  | 0.798         | 22.0  | 13750 | 1.5802          | 18.3342 | 16.2394 | 0.3633 |
  | 0.7878        | 23.0  | 14375 | 1.5854          | 18.3571 | 16.2472 | 0.3651 |
  | 0.7656        | 24.0  | 15000 | 1.6036          | 18.1945 | 16.2403 | 0.3644 |
  | 0.7445        | 25.0  | 15625 | 1.6124          | 18.2537 | 16.2328 | 0.3645 |
  | 0.7406        | 26.0  | 16250 | 1.6291          | 18.3761 | 16.1935 | 0.3658 |
  | 0.7284        | 27.0  | 16875 | 1.6328          | 18.2859 | 16.2504 | 0.3644 |
  | 0.7149        | 28.0  | 17500 | 1.6389          | 18.2636 | 16.2413 | 0.3645 |
  | 0.7059        | 29.0  | 18125 | 1.6463          | 18.304  | 16.2271 | 0.3652 |
  | 0.7038        | 30.0  | 18750 | 1.6505          | 18.2883 | 16.2262 | 0.3649 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  