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-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_1e-05-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: 2.8391
  - Bleu: 0.0308
  - Meteor: 0.1222
  
  ## 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: 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  | 3.1172          | 0.0194 | 0.0879 |
  | 3.6071        | 2.0   | 808  | 2.9990          | 0.0251 | 0.1066 |
  | 3.2935        | 3.0   | 1212 | 2.9471          | 0.027  | 0.1118 |
  | 3.1963        | 4.0   | 1616 | 2.9105          | 0.0281 | 0.1145 |
  | 3.1602        | 5.0   | 2020 | 2.8873          | 0.0286 | 0.1168 |
  | 3.1602        | 6.0   | 2424 | 2.8686          | 0.0293 | 0.1187 |
  | 3.1194        | 7.0   | 2828 | 2.8547          | 0.0301 | 0.1204 |
  | 3.0906        | 8.0   | 3232 | 2.8464          | 0.0306 | 0.1214 |
  | 3.0866        | 9.0   | 3636 | 2.8408          | 0.0307 | 0.1221 |
  | 3.0672        | 10.0  | 4040 | 2.8391          | 0.0308 | 0.1222 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  