readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_0.001-ep_10-seq_128_bs-16
    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_0.001-ep_10-seq_128_bs-16
  
  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: 1.6393
  - Bleu: 0.1929
  - Meteor: 0.3605
  
  ## 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: 16
  - eval_batch_size: 16
  - 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   | 404  | 2.1057          | 0.1016 | 0.2499 |
  | 2.6026        | 2.0   | 808  | 1.7919          | 0.1333 | 0.2893 |
  | 1.8228        | 3.0   | 1212 | 1.6738          | 0.1568 | 0.3205 |
  | 1.4557        | 4.0   | 1616 | 1.6240          | 0.1677 | 0.3347 |
  | 1.2482        | 5.0   | 2020 | 1.5976          | 0.1786 | 0.3471 |
  | 1.2482        | 6.0   | 2424 | 1.5997          | 0.1857 | 0.3539 |
  | 1.0644        | 7.0   | 2828 | 1.5959          | 0.188  | 0.3553 |
  | 0.9399        | 8.0   | 3232 | 1.6128          | 0.19   | 0.3583 |
  | 0.8668        | 9.0   | 3636 | 1.6260          | 0.1922 | 0.3593 |
  | 0.8001        | 10.0  | 4040 | 1.6393          | 0.1929 | 0.3605 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  