readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_0.0001-ep_10-seq_128_bs-32
    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_0.0001-ep_10-seq_128_bs-32
  
  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: 2.2914
  - Bleu: 0.0708
  - Meteor: 0.2054
  
  ## 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: 32
  - eval_batch_size: 32
  - 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   | 202  | 2.8210          | 0.0313 | 0.1235 |
  | No log        | 2.0   | 404  | 2.6712          | 0.0398 | 0.1478 |
  | 3.0646        | 3.0   | 606  | 2.5543          | 0.0483 | 0.1661 |
  | 3.0646        | 4.0   | 808  | 2.4735          | 0.0537 | 0.1751 |
  | 2.6866        | 5.0   | 1010 | 2.4120          | 0.0591 | 0.1855 |
  | 2.6866        | 6.0   | 1212 | 2.3663          | 0.0618 | 0.1906 |
  | 2.6866        | 7.0   | 1414 | 2.3324          | 0.0667 | 0.1993 |
  | 2.5034        | 8.0   | 1616 | 2.3098          | 0.0684 | 0.2023 |
  | 2.5034        | 9.0   | 1818 | 2.2969          | 0.0696 | 0.2042 |
  | 2.4271        | 10.0  | 2020 | 2.2914          | 0.0708 | 0.2054 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  