readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_1e-4-ep_10-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-mpst-id-en-lr_1e-4-ep_10-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: 2.4108
  - Bleu: 5.8803
  - Meteor: 0.1857
  
  ## 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: 0.0001
  - 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu   | Meteor |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | No log        | 1.0   | 101  | 2.8898          | 2.8643 | 0.1158 |
  | No log        | 2.0   | 202  | 2.7574          | 3.5561 | 0.1355 |
  | No log        | 3.0   | 303  | 2.6672          | 4.1558 | 0.1509 |
  | No log        | 4.0   | 404  | 2.5927          | 4.5156 | 0.1593 |
  | 2.9931        | 5.0   | 505  | 2.5319          | 4.9528 | 0.1673 |
  | 2.9931        | 6.0   | 606  | 2.4832          | 5.2665 | 0.1728 |
  | 2.9931        | 7.0   | 707  | 2.4505          | 5.4822 | 0.1778 |
  | 2.9931        | 8.0   | 808  | 2.4290          | 5.7456 | 0.1829 |
  | 2.9931        | 9.0   | 909  | 2.4147          | 5.8499 | 0.185  |
  | 2.6176        | 10.0  | 1010 | 2.4108          | 5.8803 | 0.1857 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  