readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_1e-3-ep_20-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_1e-3-ep_20-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: 1.6391
  - Bleu: 18.9112
  - Meteor: 0.3583
  
  ## 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: 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  | 1.8793          | 13.9958 | 0.2988 |
  | No log        | 2.0   | 404  | 1.7154          | 15.2332 | 0.3136 |
  | 1.6109        | 3.0   | 606  | 1.6615          | 16.4394 | 0.3279 |
  | 1.6109        | 4.0   | 808  | 1.6292          | 17.1368 | 0.3375 |
  | 1.2855        | 5.0   | 1010 | 1.6205          | 17.7174 | 0.3451 |
  | 1.2855        | 6.0   | 1212 | 1.6246          | 17.9786 | 0.3478 |
  | 1.2855        | 7.0   | 1414 | 1.6178          | 18.3294 | 0.3515 |
  | 1.0144        | 8.0   | 1616 | 1.6195          | 18.6155 | 0.3556 |
  | 1.0144        | 9.0   | 1818 | 1.6320          | 18.7035 | 0.3565 |
  | 0.8814        | 10.0  | 2020 | 1.6391          | 18.9112 | 0.3583 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  