readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_1e-05-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_1e-05-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: 2.9022
  - Bleu: 0.0284
  - Meteor: 0.1159
  
  ## 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: 1e-05
  - 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  | 3.2021          | 0.0126 | 0.0683 |
  | No log        | 2.0   | 404  | 3.0749          | 0.0219 | 0.0958 |
  | 3.559         | 3.0   | 606  | 3.0147          | 0.0252 | 0.1059 |
  | 3.559         | 4.0   | 808  | 2.9738          | 0.0262 | 0.1094 |
  | 3.2602        | 5.0   | 1010 | 2.9476          | 0.027  | 0.1113 |
  | 3.2602        | 6.0   | 1212 | 2.9309          | 0.0278 | 0.1138 |
  | 3.2602        | 7.0   | 1414 | 2.9153          | 0.0278 | 0.1139 |
  | 3.1839        | 8.0   | 1616 | 2.9083          | 0.0285 | 0.116  |
  | 3.1839        | 9.0   | 1818 | 2.9041          | 0.0284 | 0.1158 |
  | 3.1574        | 10.0  | 2020 | 2.9022          | 0.0284 | 0.1159 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  