readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_0.0001-ep_30-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_0.0001-ep_30-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: 1.7399
  - Bleu: 0.1512
  - Meteor: 0.3113
  
  ## 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: 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu   | Meteor |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
  | No log        | 1.0   | 404   | 2.7159          | 0.0379 | 0.1409 |
  | 3.1207        | 2.0   | 808   | 2.4769          | 0.0518 | 0.1728 |
  | 2.7244        | 3.0   | 1212  | 2.3261          | 0.0667 | 0.1988 |
  | 2.4735        | 4.0   | 1616  | 2.2345          | 0.0783 | 0.2172 |
  | 2.3206        | 5.0   | 2020  | 2.1375          | 0.0876 | 0.2305 |
  | 2.3206        | 6.0   | 2424  | 2.0815          | 0.0952 | 0.241  |
  | 2.1735        | 7.0   | 2828  | 2.0141          | 0.1027 | 0.2506 |
  | 2.0667        | 8.0   | 3232  | 1.9810          | 0.1107 | 0.2603 |
  | 1.9851        | 9.0   | 3636  | 1.9394          | 0.1157 | 0.2664 |
  | 1.9022        | 10.0  | 4040  | 1.9124          | 0.1205 | 0.2721 |
  | 1.9022        | 11.0  | 4444  | 1.8832          | 0.1239 | 0.2776 |
  | 1.8341        | 12.0  | 4848  | 1.8702          | 0.1287 | 0.2835 |
  | 1.7756        | 13.0  | 5252  | 1.8432          | 0.1328 | 0.2881 |
  | 1.7389        | 14.0  | 5656  | 1.8327          | 0.1338 | 0.2898 |
  | 1.6861        | 15.0  | 6060  | 1.8225          | 0.1372 | 0.2934 |
  | 1.6861        | 16.0  | 6464  | 1.8020          | 0.1391 | 0.2956 |
  | 1.647         | 17.0  | 6868  | 1.7913          | 0.14   | 0.2973 |
  | 1.6145        | 18.0  | 7272  | 1.7842          | 0.1434 | 0.302  |
  | 1.585         | 19.0  | 7676  | 1.7746          | 0.144  | 0.3015 |
  | 1.554         | 20.0  | 8080  | 1.7699          | 0.1442 | 0.3028 |
  | 1.554         | 21.0  | 8484  | 1.7654          | 0.1462 | 0.3051 |
  | 1.5332        | 22.0  | 8888  | 1.7573          | 0.147  | 0.3062 |
  | 1.5109        | 23.0  | 9292  | 1.7537          | 0.1489 | 0.3083 |
  | 1.4981        | 24.0  | 9696  | 1.7507          | 0.1493 | 0.3089 |
  | 1.4834        | 25.0  | 10100 | 1.7445          | 0.1501 | 0.3094 |
  | 1.4732        | 26.0  | 10504 | 1.7427          | 0.1502 | 0.3095 |
  | 1.4732        | 27.0  | 10908 | 1.7414          | 0.1502 | 0.3102 |
  | 1.4623        | 28.0  | 11312 | 1.7417          | 0.1511 | 0.3111 |
  | 1.4601        | 29.0  | 11716 | 1.7405          | 0.1512 | 0.3114 |
  | 1.4543        | 30.0  | 12120 | 1.7399          | 0.1512 | 0.3113 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  